– Using your authority as a parent or boss is a great tactic to get your family or team aligned during an emergency. But if it becomes your go-to strategy, it will soon have counterproductive effects.

– If you are such a good liar that your lies have a 1% chance of getting caught, lying can be an effective tactic to get out of a difficult situation. But if it becomes your strategy, and you lie once a week, you have a 99.5% chance of getting caught over a decade.

– Binge eating or binge watching YouTube shorts might be a great tactic to manage a moment of extreme anxiety. But if it becomes your strategy to manage below-average moods, your life will soon contain growing problems and dissatisfaction.

The point is that growing beyond a certain point requires solving root-cause problems and acquiring long-term assets such as skills, relationships, and trust.

Tactics that do not help with either can be used as a one-off when you are in a tight spot, but should not become your long-term strategy.

Is there any “shortcut” you apply at work or in your life that helps you avoid facing a problem or overcome a lack of skills, relationships, or trust? If so, are you using it as a “rare one-off” or is it becoming your go-to strategy?

In the latter case, the key is to think not whether using it once makes sense (it probably does, at least in the short term and at least from an emotional landscape point of view, otherwise you would not do it), but rather consider the long-term consequences of you using it over and over. A typical example is avoiding thinking about your problems. This is a fine tactic to get through a particularly stressful day. However, if you never face your problems, every day will soon become stressful.

Once you have identified a short-term tactic that you should stop using as your go-to strategy, here are two questions that might help find a better long-term alternative. What root problem can you tolerate for the moment, but would not be able to tolerate for the rest of your life? What changes should you make, and what skills or relationships should you build to overcome it?

Note: In my book “Winning Long-Term Games,” I explain how people get stuck in life when they adopt effective short-term tactics as long-term strategies, and I explore in much deeper detail, with more extensive examples and more practical solutions.

Examples of circularity

The best way to understand circularity is through some examples:

– On the one hand, high IQ is associated with higher education and higher-paying jobs. On the other hand, school exams and job interviews contain IQ tests – not actual IQ tests, but questions that are better measures of the candidate's IQ than their job-related abilities. Hence, there is a circularity: part of the reason high-IQ people have higher-paying jobs is that we designed exams and job interviews to be IQ tests.

– In finance, when a stock rises in price, it often triggers mechanisms that cause more traders to want to buy it, further increasing its price. The fact that the price is both outcome and cause is a circularity.

– Have you noticed, when studying history, how exceptional it is that the good guys always win in the end? Victors write the history books, and historians belong to the winners. This creates circularity: those being measured (the winners) are the same doing the measurement.

– On the 8th of January 2025, the New York Times titled "Meta [Facebook's holding company] says fact-checkers were the problem. But fact-checkers rule that false." Fact-checkers ruling on themselves creates an obvious circularity.

These examples show that modernity is full of circularities: contexts in which those doing the measuring and those being measured overlap significantly, or when the act of measurement itself influences the outcome.

Is circularity bad?

Circularity is not always bad, though it often is, especially when we are unaware of it. For example, in science and truth-seeking, circularity makes correlations appear as causations. In finance, it might mislead traders into believing an asset is better or more stable than it actually is, causing them to enter trades whose risk they do not understand. Hence, the importance of detecting circularity: to prevent costly mistakes.

Partial circularity

Note that circularity is not a binary property, either fully present or fully absent; often, circularity is only partial. For example, finance is full of circularities, because current prices influence future ones, as highlighted by the fact that some traders buy a stock for the sole reason that it has risen. However, circularity is seldom total, for past prices are only one of the factors considered in evaluating an asset, and estimations of intrinsic value matter, too.

How to detect circularity?

Here are two tests useful to detect circularity:

1. Given two metrics A and B, does the act of measuring A influence B? For example, in the case of IQ and life outcomes, the question is not only whether A (one’s IQ) influences B (their life outcomes), but also whether the act of measuring A (administering tests that, directly or indirectly, measure IQ) influences B (life outcomes). In this case, it does, for school tests and job interview tests have an obvious effect on one’s access to good schools and good jobs.

2. Given a metric, who defines how it should be measured, and were they selected based on that same metric? For example, to some extent, it can be said that academicians are both those who decide who is smart and are selected for being smart, leading to at least some partial circularity in the definition of smartness.

A positive answer to either of the points above indicates circularity.

Note: A reader submitted the topic of this article. If you also have questions you would like me to answer, let me know!

This is a textbook example of Wittgenstein’s Ruler: when you use a flawed measuring stick, the results reveal more about your instrument than what you’re trying to measure. A study that treats MLB games as necessities tells us more about the researchers than about the living standards of Americans.

That said, a reader asked me how I would define the Minimal Quality of Life. That’s a good question requiring a thoughtful answer, hence this blog post.

Principles to define the Minimal Quality of Life

Let’s begin by discussing a few guiding principles.

First, Minimal Quality of Life should be defined in achievable terms, without containing zero-sum elements. Statements like “Everyone has the right to live in the most desirable city” or “Everyone deserves a top-tier degree” are self-defeating because these goods derive their value from scarcity. If we made degrees a human right, everyone would want a PhD to stand out. It’s a game we cannot win, and hence we shouldn’t play.

This principle has practical implications. For example, the “higher education” component of quality of life should mean “access to high-quality learning content and affordable certification that doesn’t require physical attendance,” not “the right to attend prestigious universities.” Similarly, while everyone should have access to decent housing, no one can claim an inherent right to live in the specific locations that everyone else also wants, since this is mathematically impossible.

Secondly, Minimal Quality of Life should be defined by access to goods and services, not dollar amounts. Consider housing as an example: if the average house costs $500,000 but the average family has only $200,000, we might assume each family needs an additional $300,000 to live well. However, simply giving everyone $300,000 wouldn't solve the underlying problem. Without building more housing, we would still have fewer dwellings than families, meaning some families would remain priced out regardless of their wealth. The real solution is to build enough housing for everyone.

This means we should resist defining Minimal Quality of Life through minimum wage or wealth targets, and instead focus on whether we’re producing sufficient goods and services for everyone’s basic needs.

Thirdly, a definition of Minimal Quality of Life should remain truly minimal. By definition, this standard won’t satisfy most people. If it did, we’d call it Good Quality of Life instead. But why focus on minimal rather than good standards? I address this question in the following section.

Minimal vs Good Quality of Life

Imagine we were to define the Minimal Hotel. Most people would agree on the requirements: a safe shelter, a clean room with a bed and linens, access to a clean bathroom, and electrical outlets. Maybe a few would disagree, but most would agree. Building a Minimal Hotel would be relatively cheap. We could easily, as a society, build a Minimal Hotel for everyone.

Now, try defining a Good Hotel. Some would demand bathtubs, others sofas, still others restaurants or fitness centers. To satisfy everyone's definition of “Good,” we would need to include every amenity anyone considers necessary. The resulting hotel would be prohibitively expensive—impossible to provide for everyone without requiring more labor than society is willing to supply.

This last point is critical. Since building hotels and their furniture requires human labor and society’s work capacity has limits, universal access to Good Hotels is only possible through variety: many different hotels, each excelling in some areas while being basic in others, allowing people to choose the trade-offs that matter most to them. All would still have to meet Minimal standards, obviously, but none would satisfy everyone's definition of “Good.”

Hence, it makes more sense to measure Minimum Quality of Life and ensure everyone has a path to what qualifies as Good for them, rather than to measure a Good Quality of Life consisting of goods and services which not everyone is willing to make sacrifices for, or wouldn’t consider necessary if it weren’t for the fact that most people around them have it too.

So, what should be included in the definition of Minimal Quality of Life?

A definition of Minimal Quality of Life

First, I would include all basic human rights, particularly non-physical ones: equal treatment under the law, free speech, occupational choice, democratic participation, and similar fundamental freedoms.

Secondly, I would include all basic survival needs: shelter, food, medical care, and similar essentials. But in what quantity and quality? Since we’re defining Minimal Quality of Life rather than Good Quality of Life, I would include only what 95% of able-bodied people consider worth working for. If more than 5% of people wouldn’t willingly work to obtain something, it’s likely beyond what counts as truly minimal.

Thirdly, I would include access to genuine paths for upward mobility. While some people may decline opportunities that require effort in exchange for improving their condition, society should ensure these pathways exist and are truly actionable. This means more than just providing access to, e.g., quality education, which is relatively straightforward in the internet age. The greater challenge is ensuring people are aware of these opportunities and, crucially, believe they can realistically leverage them.

Fourth, I would include nothing else. The benefits of expanding this definition are outweighed by the costs of diluting our focus. Our attention is better spent ensuring the first three categories are not only fulfilled, but fulfilled well enough to meaningfully improve lives and efficiently enough so that we can fulfill them for everyone.

This last point is of paramount importance. Just last week, in an essay about Cultural Subsidies, I wrote: “precisely because culture should be a common good, it is paramount to keep its costs low and cut unnecessary expenses [so that we can produce enough culture with our limited time and work].” Similarly, it is precisely because guaranteeing a Minimal Quality of Life for everyone is so important that we should ensure we achieve it as cheaply and efficiently as possible, without deluding ourselves that it is possible to do it while keeping costs high and production inefficient.

Don’t get me wrong. I'm not lowering my ambitions for what society can achieve. Rather, I'm arguing that as long as we fail to guarantee these three fundamental requirements for everyone, it makes little sense to prioritize anything else. Moreover, it is precisely by fixing our failure to do so that we also fix the structural problems that would enable society to achieve more ambitious objectives.

This phenomenon, in which most opera theater revenue comes from subsidies instead of the audience, is quite common in Europe. In my hometown of Turin, Italy, public subsidies are $163 per ticket sold, and public subsidies represent 58% of revenue (tickets are 17%, and the rest is mostly private subsidies).[^2] In Paris, public subsidies represent 57% of the revenue of the Bastille Opera.[^3]

Despite all these subsidies, attendance remains low. For example, last year, Turin’s opera theater only filled 74% of the places available – and that in spite of subsidies lowering the average ticket price from 204€ down to 41€ (an 80% discount).

The problem is not a lack of subsidies but an excess of costs. If my local opera theater managed to cut costs by 10%, tickets could be 20€ (assuming constant subsidies). If we believe that dropping the ticket prices from 40€ a piece to 20€ a piece would help fill that 26% of empty seats, a reasonable guess by all means, the breakeven ticket price could be further dropped to 16€. And if my local opera managed to cut costs by 20%, tickets could be free. That would be fantastic!

There is a common argument that culture is a common good, just like education and healthcare, and therefore should be subsidized. I agree with it! But precisely because culture should be a common good, it is paramount to keep its costs low and cut unnecessary expenses.

Too often, we see culture subsidies as a false dichotomy, where either we give enough money to theaters and museums to cover all their costs, or they will close. However, this neglects that while some costs are necessary (some employees, utilities, etc.), others are unnecessary (other employees, some frivolities, etc), and it is paramount to ensure the former are funded while the latter are defunded. It is also critical to ensure that the theater and museums are well-managed and run efficiently. The idea that culture should be a basic good is incompatible with theaters and museums being badly managed and paying unnecessary wages.

This is particularly relevant since public subsidies are a finite quantity. The more we fund unnecessary expenses in one theater, the fewer theaters we can fund. (And the more we fund unnecessary expenses in theaters, the fewer schools and hospitals we can fund.) It is precisely because culture is important that we should care about how efficiently subsidies are used.

Hence, we shall review the income statements and operating expenses of all recipients of public subsidies carefully and make these subsidies conditional on the recipient removing unnecessary costs.

Unless we do that, we will get less culture despite spending more on it.

Footnotes:

[^1]: 40M CHF of subsidies for a total audience of 90k, which is 444 CHF per person, or 541 USD. Source: the 2021 audit of Geneva’s opera theater.

[^2]: 21.7M€ of subsidies for 151k tickets sold. Source: the 2024 balance sheet,

[^3]: Source: their 2023 financial statement.

We often think we should wait to commit until we find something worth committing to. But sometimes, it's the commitment itself that creates the worth.

This doesn't mean you should commit blindly to anything. Rather, it means there's a limit to how good something can feel before you commit to it. Commitment is often what transforms something good into something great.

This principle extends not only to the choice of one’s residence but also to romantic relationships, friendships, careers, and hobbies. Waiting for perfection before committing can be counterproductive, because it is precisely commitment that creates the conditions for an option to become exceptional.

Related: my article on long-term commitment and its application to social media.

Games in which there can be only one winner are cruel, for it doesn’t matter how talented you are, how long you train, and how much you sacrifice; as long as someone else does the same, it becomes a coin toss, and you might be left with nothing.

The lesson? Choose games where there can be multiple winners. This is a more important consideration than how good your strategy is or how determined you are; for in a game where there can only be one winner, these might not matter at all.

I wrote this sentence in my latest book, “Winning Long-Term Games.” The idea is that everything that matters in the short term is urgent, but in the long term, you will forget the urgent tasks you worked on, and everything that will have mattered are the important-yet-not-urgent activities, such as building skills, trust, or relationships.

Of course, it is important not to take this to any excess. Of course, you cannot fully avoid working on the urgent. And often, important tasks are also urgent. Yet, the point remains. Unless you spend at least part of your time working on important-yet-not-urgent activities, you will find yourself unable to grow beyond a certain point.

But why is it so hard to work on the important-not-yet-urgent?

The naive answer would be that, similarly to the marshmallow test, it’s about delayed gratification. However, unlike the marshmallow test, you are not alone in the experiment room. Instead, all around you, others are eating the marshmallow and the media are celebrating those eating it the fastest. It turns out that the hard part is not delayed gratification but the feeling of falling behind.

In particular, the hard part is the feeling that, if today you didn’t get out of the day as much as someone else did, then you’re falling behind, and you should catch up as soon as possible. This is a dangerous belief because it will make you feel bad every day you don’t produce as much as others, and every day you don’t party or vacation as hard as others. As a result, you will feel like you have no time to work on the important, be it important for your professional life or your personal one.

If this is your bottleneck, here are two things you can do about it:

Carefully select who you spend time with or follow online. Remove those who constantly make you feel like you're falling behind, leaving you frantically trying to catch up while neglecting the important-yet-not-urgent.

Whenever you work on something important-yet-not-urgent, such as building skills, relationships, or trust, immediately give yourself a big pat on the back. It is crucial that you feel like you have made progress; otherwise, you will revert to spending all your time on the urgent.

By all means, none of these are necessary. But if you examine how you spent the past week and notice that you neglected the important-yet-not-urgent, you might want to try putting them into practice.

I have worked on such projects in the quality of an external consultant brought in to help with the task, and here are some tips and tricks I’ve learned along the way.

First of all, what are Managerial Capabilities, and why are they important?

The term “Managerial Capabilities” refers to an organization’s ability to maximize employee effectiveness by developing internal talent, providing clear guidance, sustaining engagement and motivation, and effectively addressing underperformance. A Managerial Capabilities Assessment focuses on whether managers have the required competencies and whether the managerial culture and benchmarks across the organization are conducive to excellence or mediocrity. Its output is a set of recommendations on how to increase managerial capabilities by acting on both individuals and culture.

Managerial Capabilities are of paramount importance, for even a company with a perfect strategy and great product-market fit might only realize part of its potential if its employees are poorly managed. Similarly, even in more mature markets, how well managers run operations and develop talent is often the difference between survival and death, or between barely making it and becoming highly profitable.

After a change in top management, it is often tempting to focus on strategic efforts rather than on improving internal managerial capabilities, as everyone is busy and under the impression that there is not enough time to do both. But why is there so little time, and why do things take so long? Often, the reason is insufficient Managerial Capabilities, and improving them might actually be the fastest way to help achieve other strategic goals.

How do you measure Managerial Capabilities?

It is paramount to avoid using methods that scale, such as surveys or large data collection, for they are unreliable and suffer from the same blind spots you’re trying to uncover. For example, a common reason some team meetings are run poorly is that the people involved do not know what a well-run meeting looks like. In that case, a survey that asks how well meetings are run might collect positive feedback even in teams whose meetings have a large opportunity for improvement. A second reason that surveys are not very effective is that, when they surface problems, they do not reveal their root cause, with the risk that the findings are misinterpreted and the wrong solution selected.

A much better tool to measure Managerial Capabilities is to run a series of short one-on-one interviews with people at all levels of the organization: a few top managers, a few middle managers, a few line supervisors, and a few line employees. Only in a one-on-one setting can a competent interviewer dig deep enough to uncover root causes and receive honest answers with full context.

The main reason companies often prefer surveys to interviews is that the former are perceived as more time- and cost-efficient, and more comprehensive. But this is often not the case. Running a company-wide survey takes time to prepare, run, and collect the results, and requires the involvement of many people across the organization. It is faster and cheaper to task a single expert (such as myself) to run a few interviews with a few top managers, middle managers, supervisors, and line employees. Moreover, expert interviews can dig far deeper than a survey ever can, providing a more accurate assessment of root causes and thus becoming a more reliable base on which to take action.

Another reason companies often prefer surveys is that they are the only realistic way to achieve full coverage of the whole organization. However, this is often unnecessary. It only takes a few interviews for an expert to have a good idea of the most significant problems and opportunities affecting the organization. He might not discover all the problems affecting all locations of the company, but neither can a survey, because the most important problems and opportunities require digging deeper than a superficial survey could.

In addition to one-on-one interviews, a competent Managerial Capabilities Assessment Expert would also spend a bit of time attending internal meetings to see how they are run. Do progress update meetings help derisk projects? Do Monday Morning team meetings help attendees have a clearer idea of what to work on during the week? Are problems surfaced or hidden under the rug? Is everyone’s time used effectively? These are questions that can only be answered by observing such meetings directly.

What to look for during one-on-one interviews

First, a few things to keep in mind while planning the interviews:

1. Dig deep, not broadly. You don’t have to schedule many interviews (a solid starting point for a company of, say, a few thousand employees is 3-5 top managers, 3-5 middle managers, 3-5 supervisors, and 3-5 employees; three days should suffice), and you do not have to cover everything in each interview, but you do have to dig deep. Uncovering a single problem and understanding exactly what is going on is much better than uncovering ten problems superficially – the latter gives a larger impression of progress, but the change initiatives it sparks are less likely to be effective, whereas solving a single problem well often leads to many indirect improvements.

2. Discuss what does happen instead of what should happen. For example, do not discuss processes but what people do; and do not discuss theoretical organizational structure, but instead discuss actual interactions.

3. Focus on habits over people. Of course, during the interviews, it is important to uncover particularly dysfunctional people in the organization who should be terminated or particularly talented ones who should be given more responsibilities. That said, an excessive focus on individuals has limited effectiveness beyond these low-hanging fruits. Instead, a competent interviewer should surface not only people-related problems and opportunities, but also culture-related and process-related ones (and the latter should relate not only to product-related processes but also to how meetings are run and people are managed).

4. The point of these interviews is not to catch anyone wrong but rather to uncover structural problems and opportunities. The interviewer’s attitude should be collaborative instead of adversarial to reflect that.

5. During each interview, indirectly collect information about the layers above and below the interviewee. Do not ask about their boss directly, or at least do not rely on their answers in this regard, for they might be tainted by social considerations. Instead, use the interviewee’s answers about their own job to infer whether their manager provides them with enough clarity and whether they provide enough clarity to their subordinates (if applicable).

That said, here is a non-exhaustive list of some of the things a competent Managerial Capabilities Assessment Expert would look for during one-on-one interviews with managers, supervisors, and line employees.

• Can they explain what doing their job well looks like? (Depending on their role, probe whether they are able to explain this for their own job and/or their subordinates.)

• Can they explain who is impacted by them doing their job well, and do their eyes light up as they do so?

• What tasks within their team seem to take unnecessarily long?

• What does their boss not know that they should know about?

• What do they wish their team understood that they do not understand yet?

• When there is more to do than time to do it, how do they prioritize?

• What was the last problem they escalated, and what happened as a result?

• If they were in charge of their department, what changes would they make?

Of course, this list is non-exhaustive, and the interviewer should adapt what they ask on the fly based on the information uncovered so far and following the principle of “dig deep, not broad.”

Experience, experience, experience

It would seem that running the one-on-one interviews only requires good interviewing skills. However, an interviewer who is competent at interviewing but lacks direct management experience might not be able to spot mediocrity. For example, it is easy to notice a complete lack of clarity, but is the interviewer able to assess when a response merely indicates superficial clarity or a deep one? Similarly, is the interviewer able to assess whether Monday Morning meetings are run not merely well but also greatly (and do they know what it would take to transition to the latter?)

Hence, it is important to ensure that the interviewers have a good benchmark for what great management looks like and are able to dig beyond the surface.

Managerial Capabilities Assessment Outcomes

The assessment will likely reveal a few low-hanging problems and opportunities that can be addressed relatively easily and usually at the organizational level (a few people to replace, a few people to shuffle around, and a few atomic changes to existing processes and policies). Everything else should be acted upon under the following assumptions:

• Change will be elastic unless deliberately designed to be plastic: the former reverts to its previous form as soon as pressure is released, and the latter lasts through time. It’s of paramount importance that any initiative is implemented in a way that will result in plastic change.

• Plastic change requires everyone’s direct supervisor to be committed to it. It doesn’t matter how well you roll out a change initiative; employees do not spend effort on what their supervisor doesn’t care about.

• Plastic change requires critical mass. You can remind everyone once a month that they should do something differently, and they might not change during their whole career; or you can remind them a few times a day, and they will change in a week.

• Plastic change requires immediate feedback that efforts aren’t going to waste. If you ask people to do things differently, but when they do, they do not receive immediate feedback that their supervisor noticed, they will wonder whether their efforts are going to waste, and will soon revert to their original behavior. Note: immediate means immediate; not “at the end of the week.”

• Critical mass requires shrinking the scope of change so that managers and supervisors have the bandwidth to follow up on it at least daily (and can do so in a way that’s effective and not merely superficial).

Of course, there are exceptions, but in general, you will do better assuming the five points above are always relevant rather than believing you might get away with ignoring them.

Conclusions

This was a brief overview of how I conduct Managerial Capabilities Assessments and some of the lessons I’ve learned along the way.

For any enquiries, you can get in touch with me at Luca-Dellanna.com/contact.

In the democratic version of Orwell’s Animal Farm, the pigs maintain control by turning all elections into a choice between two pigs wearing ties of different colors.

They trick the other animals into focusing their energy on the wrong goal: getting their preferred party elected instead of preventing pigs from being elected altogether.

The greatest threat to democracy is not dictators (they are merely a symptom), but voters losing sight of what truly matters.

II

Voters lose their focus when they believe that winning the next election is more important than electing a competent government.

This happens when voters view a particular issue as a life-or-death situation and allow this perception to lower their standards for what they expect from representatives, including their own. In their urgency to ensure their party wins, they tolerate incompetent and corrupt candidates, overlook their mistakes, support their flawed policies, and abandon the fight for truth and competence.

If this occurred for just one election, the damage might be limited. But when every election is framed as a matter of life or death, and voters progressively accept worse and worse behavior, the quality of government rapidly deteriorates.

III

The problem with government quality deteriorating is not only that citizens become poorer and receive worse public services, but also that it increases the likelihood that dissatisfied voters switch sides, even when the opposition runs terrible candidates.

Compromising on standards to help your party succeed may win the next election, but ultimately leads to losing future ones – and then you get incompetent and polarized political opponents in power. A disaster.

This is why it’s never worthwhile to lower your standards for your party’s candidates, even when preventing the opposition from winning feels like a matter of life or death.

Rationale

I

Polarization is not just political differences or heated debate. It’s the belief that the opposing group poses such a danger that it justifies adopting unethical behavior against them: insulting, lying, cheating, suspending due process, collective punishment, and so on.

II

Polarization is fear-driven but not irrational. Its logic is that the other group is so dangerous that extreme measures are justified to limit their influence and negative impact.

However, adopting extreme measures makes one’s own group appear unreasonable and dangerous, thereby justifying extreme measures from the opposition.

Therefore, polarization is always mutual.

III

If polarization weren’t mutual, it would be an effective tool for advancing political goals. However, since polarized behavior from one group triggers similar responses from others, it gradually erodes societal trust and institutional effectiveness. As a result, governing becomes more difficult even if one wins the elections, and society suffers even if one gets to pass their favorite policies.

For example, if someone sees environmental neglect as a life-or-death risk, wanting to use any method to raise awareness is comprehensible. However, if these methods alienate most of the population, it becomes increasingly difficult, if not impossible, to gain the broader societal support required to improve the environment at scale.

Therefore, it is paramount never to let virtuous ends justify polarized means.

IV

Under a short enough time horizon, using polarizing tactics always makes sense, and under a long enough time horizon, it never does.

For example, using censorship against a wannabe dictator is a good idea to prevent his rise to power. The question is whether normalizing censorship makes it easier for another wannabe dictator to rise to power.

So, of course, there are good arguments for why the use of polarizing tactics brings good short-term outcomes. The question is whether the long-term effect is positive, and the answer is inevitably negative.

Escalation

I

Polarization begins when someone expresses a belief that’s perceived as dangerous by the outgroup, and his ingroup fails to dissociate from him. For example, when someone makes a racist comment, and his community members do not call him out on it.

This silence makes the entire ingroup appear dangerous to the outgroup.

II

The perceived dangerousness of a group stems from two factors: (1) the group harbors unethical individuals, and (2) the group seems unwilling or unable to call them out or hold them accountable.

A third factor often exacerbates this: when the group conspicuously celebrates their unity, including unity with those unethical individuals.

III

There are several reasons the ingroup may be unwilling to police its members who do or say unethical things:

They justify it as “tit for tat.”

They view the person making such statements as “that weird guy” and cannot imagine others would take them seriously or consider them representative of the whole group's beliefs.

They are already so polarized that they believe they face a life-or-death situation where it is paramount to stick together and offer no vulnerability to their political opponents. Whether these three behaviors are justified is irrelevant. What matters is whether they invite similar behavior from the other group.

IV

And yet, the very people who believe (1), (2), and (3) above often fail to extend the same benefit of the doubt to the outgroup. When someone from the outgroup says something polarizing, they take it at face value. When “that weird guy” from the other group says something dangerous, they present it as if coming from a respected representative who speaks for the entire group.

V

These behaviors intensify polarization and make all groups more likely to engage in further polarizing actions and polarizing rhetoric. A race to the bottom where even the winners lose.

Temptations

I

Because polarization is always mutual, it cannot be resolved through polarizing actions.

For instance, censoring a political opponent only deepens polarization, as a portion of the population will view the censorship as unjustified and, consequently, perceive the censors themselves as the real threat.

II

It is paramount to resist the temptation to say, “The other side exaggerates and misrepresents, so we are justified to do the same” – as the saying goes, an eye for an eye, and the world goes blind.

III

It is paramount to resist the temptation to call for censorship. Not only is focusing on what people say rarely the best approach to address hate speech (enforcing existing laws against criminal actions would put most hateful individuals behind bars anyway, with far less collateral damage to free speech), but censorship itself is polarizing and invites retaliatory censorship against you.

IV

It is paramount to resist the temptation to claim, “The other side is so dangerous, we must stop them at all costs.” Is the entire opposing side truly dangerous, or just certain members? And if only some are dangerous, is exaggeration really the most effective way to get their side to distance themselves from these individuals?

Accurately representing the dangers posed by specific individuals often makes a more compelling argument that can garner broader support than exaggeration ever could.

V

It is paramount to resist the temptation to say, “If we do not exaggerate and misrepresent, we will lose the elections.” If you resort to exaggeration and misrepresentation, you will get pigs elected, regardless of the color of their tie.

Not only will electing a pig make you miserable even if they share your party colors, but it will increase the chances of your party losing subsequent elections, as dissatisfied voters switch to the other side.

Depolarization

I

The first step to reduce polarization is to recognize that one's political opponents consist of two distinct groups, reasonable individuals and unreasonable ones, and to avoid conflating the two.

Then, limit unnecessary engagement with the unreasonable ones, especially on social media, as interacting with these individuals is precisely what might tempt you to say or do polarizing things.

And when you do engage with the unreasonable, always treat them as individuals and never do or say things implying you believe everyone in their community is unreasonable.

II

The second step to reduce polarization is to always address specific individuals when criticizing behavior from the opposing group, and never misrepresent or exaggerate their actions. Any generalization will inevitably be perceived as polarizing.

III

The third step to reduce polarization is to always address the reasonable members of the opposing group when proposing policies, explicitly listening to their concerns and addressing them without dismissing them. This approach not only decreases polarization but also helps craft better and more widely acceptable policies that are more likely to be implemented and sustained.

This stands in direct contrast to what most of us do when proposing policies: addressing our own group, who already supports them and needs no further convincing – and in the meantime, antagonizing the opposing group, whose support we need for the policy to be effectively implemented and resist the next election cycle.

IV

The fourth step to reduce polarization is to focus on the strongest argument for or against a policy rather than exploring the second-strongest, third-strongest, and weaker points.

The further down the list of arguments one goes, the less solid they become, and the more public discussion will fixate on the most divisive details.

V

The fifth step to reduce polarization is to consistently call out unreasonable behavior from one’s own side. Failing to do so not only encourages more such behavior, but can be interpreted by the opposing group as tacit approval – and nothing seems more threatening than an unreasonable individual gathering widespread support.

VI

The sixth step to reduce polarization is to consistently call out exaggerations and misrepresentations, both from people belonging to the other side and our own – in particular from our own, for not calling out our unreasonable allies is the easiest way to make our whole group look dangerous.

VII

The seventh and final step to reduce polarization is to consistently emphasize that polarization is always mutual. That terrible president? They rose to power because of mutual polarization. That lack of trust in institutions? It occurred because of mutual polarization.

Even when one side bears more responsibility than the other, we must all address polarization as a shared problem. Failing to do so is not only polarizing in itself, but will lead even the less culpable group to justify unethical behavior.

VIII

The more the term “mutual polarization” enters the public discourse, the more we will all realize what is going on, and the more we will avoid using solutions that are themselves polarizing.

Hypocrisy

I

Reducing polarization to zero is clearly impossible. This doesn’t mean it cannot be significantly diminished.

II

Even the most dedicated adherents of this manifesto will occasionally say or do something polarizing. Critics will inevitably point this out: “You ask us not to polarize, but you did it yourself that time. You’re a hypocrite.”

But hypocrisy is overrated. If only the perfect were allowed to call out others, then no one could call out anyone, and the world would quickly descend into mediocrity, chaos, and impunity.

The only path toward mutual improvement is to allow the imperfect to call out others.

III

Polarization is a coordination problem. When we encounter something polarizing, we feel compelled to respond with polarizing actions. But if we all stopped engaging in polarizing behavior simultaneously, we wouldn’t feel this compulsion.

Committing to a goal even when others are out of sync is the only way to initiate coordination.

First, a disclaimer. I have never worked on large physical infrastructure projects. So, I will answer with my experience with other types of business projects with multiple stakeholder teams. That said, let’s answer the two questions.

Assessing Communication Quality

The single most effective way to track the quality of communication between stakeholders is to make, now and then, direct observations: attend calls, read emails, etc., and check whether the communication is honest and direct, whether problems are surfaced and addressed or hidden until it's too late, whether people are proactive or reactive, etc.

Give particular attention to whether people focus on “ticking the box” or on “creating actual progress and derisking the project.” Examples of the former include progress updates that are a recap of what happened last week instead of being about possible obstacles and how to address them, problems that are raised and noted down instead of addressed, decisions that are routinely postponed to gather more information, focus on not hurting feelings instead of being upfront, etc.

Also, note whether the attitude is collaborative (“We’re all working together against the common enemy of delays, overbudgets, and low quality”) or adversarial (“We each have our agenda and they are negative-sum”).

Of course, there are other ways to track the quality of communication. Still, they are all either inferior to direct observations or complementary, and I would never use them instead of direct observations. That said, here is a short overview of them:

• Survey participants on the quality of meetings and communication. I profoundly dislike surveys because they are extremely superficial, and when they do surface problems, they seldom surface them with enough context to make them easily actionable.

• Measure response time metrics and decision velocity. This is not a terrible idea, but it does not substitute direct observations, and if you do direct observations, you will probably not need this.

• Track the rework ratio and change order frequency. In theory, this is good to track. In practice, it might invite hiding problems, and in general, it only surfaces problems once it’s too late.

• Track the ratio of issues resolved vs. escalated. Same as above.

• Using AI to analyze communication. In theory, it is good, but in practice, it only analyzes a subset of communication (the written or recorded part) and misses the rest. A better use of AI is to make sure people do not miss important information.

Assessing Stakeholder Performance

First of all, if you have never heard of the Pyramid of Risk, read this. A fundamental principle is that you should track the performance of stakeholders against all levels of the Pyramid, not only the top one, and you should make sure that good performance on one level is not sufficient; a good performance at all levels is required, otherwise things will turn sour soon. What should the levels of the pyramid represent? It depends on the project and stakeholder at hand, but as an indicative example, the top (incidents) could be no defect and delay in the deliverables, the middle (near misses) could be just about discussing small problems and ensuring they are addressed in such ways that they won’t happen again, and the bottom (behaviors) could be good communication quality, etc. It is important that you track both outcomes (lagging indicators) and behaviors (leading indicators).

Secondly, when you assess stakeholder performance during a project (not at the end), the most important question you want to discuss is, “If things continue like this, what does the trajectory for this project lead to?” It is imperative you discuss this collaboratively and not adversarially.

Thirdly, you must dig deep (and ensure that your connections in the stakeholder groups do the same). By this, I mean ensuring that:

• Conversations about progress and possible obstacles do not stay generic and superficial but instead are concrete and specific.

• People routinely check the situation first-hand instead of relying on second or third-hand information, such as reports.

If you don’t dig deep, not only will you only discover problems until damage is done (and when discussing them will get everyone on the defensive), but you (and everyone else involved) will also miss so many opportunities for improvement.

Addressing Discomfort

I know well that everything proposed here requires going out of the comfort zone.

My experience tells me it’s worth it, but that doesn’t make it any easier, of course.

So, here are some considerations that have helped me in this regard in the past:

Direct observations can feel like intrusions – but only if you start pointing out mistakes publicly during the observations themselves. You can prevent them from feeling like intrusions by doing the following: observe not with an attitude of “cathing mistakes” but of “understanding what’s going on and why people do what they do;” genuinely look more for best practices to reproduce rather than mistakes to correct (though, of course, both will surface); always discuss problems collaboratively and not adversarially; do not make problems about the other person (“you’re doing this and it’s wrong”) and instead refer to your experience in a way that makes the problem common (“in other projects, we had this problem, and to prevent this from happening again, let’s do this…”).

If you fear “looking like the bad guy,” present all the initiatives discussed in this project not like “I, Luca, believe we should do this” (which sounds arbitrary, self-serving, and unnecessary) but rather as “Projects like this are frequently a pain for everyone because of this and that problem, and one way to avoid them is doing X and Y.” Everything you do shall be done not to serve you or the project owner but to serve the project.

Half of the discomfort stems from the idea that “there is an easier way” or “you can get away with direct observations and hard conversations.” Experience teaches you mostly can’t.

Discussing problems is easy when done early, before people sink their efforts and ego into something; when done late, it inherently breeds defensiveness and blame-throwing. The more you want to avoid the latter, the earlier problems should be surfaced.

When dealing with multi-stakeholder projects, discomfort is inevitable. You can just decide whether hard conversations will take place before or after problems happen.

I hope this helps.

My curiosity aroused, and I started researching the real data of LASIK side effects. I made some interesting discoveries, which paint the “95%+ satisfaction rates” data point as highly misleading.

• In one study,[^2] 24% of patients reported eye pain six months after the operation, compared to 7% before it. Despite that, satisfaction rates were 93%, implying that at least 62% of the patients reporting that the operation created persistent eye pain still rated the operation as satisfactory. On the one hand, this indicates that patients consider the pros of LASIK to be significant, but on the other hand, it also indicates that high patient satisfaction scores cannot be taken as evidence of low risk.

• In another study,[^3] 63% of patients who developed nighttime vision problems six months after the operation would still recommend the operation to friends. Again, an indication that high patient satisfaction scores cannot be taken as evidence of low risk.

• In a third study,[^4] about 45% of patients reported new visual symptoms after surgery. Despite that, the reported dissatisfaction rates were only about 1.5%. Again, this is an indication that we shouldn’t interpret low dissatisfaction rates as evidence of low risk.

I could go on, but hopefully, you get the point. LASIK is way riskier than reported satisfaction rates imply, and anyone claiming that high satisfaction rates are evidence of low risk is a dangerous charlatan and should be called out as such.

Footnotes:

[^1]: As an anecdote, I googled "top LASIK doctors in my town", and five out of the top ten pictures of named doctors had glasses. This is of course just an anecdote, not a solid study, but you understand why it would raise my suspicion.

[^2]: Betz J, Behrens H, Harkness BM, Stutzman R, Chamberlain W, Blanco MP, Hegarty DM, Aicher SA, Galor A. Ocular Pain after Refractive Surgery: Interim Analysis of Frequency and Risk Factors. Ophthalmology. 2023 Jul;130(7):692-701. doi: 10.1016/j.ophtha.2023.02.016. Epub 2023 Feb 19. PMID: 36809816; PMCID: PMC10293021.

[^3]: Bamashmus MA, Hubaish K, Alawad M, Alakhlee H. Functional outcome and patient satisfaction after laser in situ keratomileusis for correction of myopia and myopic astigmatism. Middle East Afr J Ophthalmol. 2015 Jan-Mar;22(1):108-14. doi: 10.4103/0974-9233.148359. PMID: 25624684; PMCID: PMC4302464.

[^4]: Eydelman M, Hilmantel G, Tarver ME, Hofmeister EM, May J, Hammel K, Hays RD, Ferris F 3rd. Symptoms and Satisfaction of Patients in the Patient-Reported Outcomes With Laser In Situ Keratomileusis (PROWL) Studies. JAMA Ophthalmol. 2017 Jan 1;135(1):13-22. doi: 10.1001/jamaophthalmol.2016.4587. PMID: 27893066.

This immediately triggers defensiveness, even if the suggestion is sound.

The trick is to avoid framing feedback as “me vs you” and instead frame it as “me and you vs a common problem.”

Let’s see a trivial example. “Your presentation should include more charts” is inherently adversarial, for it implies the recipient was wrong and the manager right. Conversely, “This presentation is very important, and we cannot afford the audience not being as engaged as possible. What if we added some charts?” frames both the manager and the employee as being in a vulnerable situation that requires change – which is proposed as an improvement that does not imply fault.

Moreover, the suggestion is not framed as “I arbitrarily decided this is not enough” but rather as “external circumstances require this to be better.”

Of course, it’s crucial that none of this is a lie or exaggeration and that the manager genuinely believes in what they are saying. But this is relatively easier, for in most cases, both the manager and the employee are truly fighting the same third-party problem (a competitor, a lack of funds, etc., or even whatever adversary the company’s mission is fighting, such as “lack of access to the company’s product”).

Let’s see a second example. “You need to dress better when going to clients.” Again, this implies that the employee is wrong. Moreover, it can be perceived that the manager is unreasonably picky about the dress code. Instead, consider the alternative: “New clients do not trust us enough – and how could they, if they never heard of our products? So, it is paramount we gather all sources of trust, including a professional dress code.” Again, this clarifies the objective need for change, presents it as an improvement without implying the previous approach was necessarily wrong, and positions the manager not as an Ivory Tower almighty sage but rather as a colleague fighting in the same trenches.

The less the ego of the manager appears in the suggestion, the more the subordinate’s ego can accept it.

Download this as a PDF

Download this as a PDF

Download this as a PDF

The typical scenario unfolds like this. A team member isn't meeting expectations. Their supervisor has a vague conversation about improvement but without specific goals or timelines. The employee knows there's an issue but lacks clear direction. Three months later, little has changed, and the supervisor faces a dilemma—either terminate someone without the confidence they were given enough chances at improvement or keep an underperformer who impacts the entire team.

This situation creates three significant problems. The employee lacks a clear path for improvement. The company retains an underperforming worker for too long. And the supervisor faces an ongoing emotional burden and a no-win situation.

A better alternative is to use a framework that I call “The Trajectory.”

A better approach: the Trajectory Framework

The core objective of any Performance Improvement Plan should be to reach a fast and fair conclusion. This means giving the employee a clear, actionable plan and quickly determining one of two outcomes: either they improve to meet expectations, or they would be better served in a different role.

The keywords are “fast” and “everyone agrees.” Prolonged uncertainty benefits no one—not the company, the team, the manager, or the employees themselves, who might find greater success elsewhere.

The Trajectory Framework achieves this through a simple approach that creates clarity and alignment.

Step 1: Visualize the Improvement Path

During a one-on-one meeting, draw a simple two-axis chart on paper. The horizontal axis represents time, and the vertical axis represents performance. Mark two points:

1. The origin: the employee's current performance level

2. point in the upper-right: where they need to be in three months

Connect these points with a line—this is the improvement trajectory they need to follow.

Step 2: Set Two-Week Milestones

On your chart, find the point that represents "two weeks from now." Move upward from there until you intersect the trajectory line and mark that point. This represents where the employee should be in two weeks to stay "on track."

Define specifically and objectively what behaviors, skills, and outcomes they need to demonstrate by this checkpoint.

Step 3: Regular Check-ins and Adjustments

After two weeks, meet again to assess progress against the defined milestones:

• If on track as per the trajectory: acknowledge progress, celebrate small wins, and set the next two-week milestone.
• If not on track: collaboratively identify barriers and develop specific actions to get back on trajectory within the next two weeks.

Continue this cycle of bi-weekly check-ins. By the second or third meeting, it becomes clear to everyone whether the three-month objective is achievable – or whether the worker simply isn’t a good fit for the role.

Notes and recommendations

Some countries have specific regulations regarding Performance Improvement Plans, so consult with your HR department before implementation. You may need to adapt the timeframes or documentation to meet legal requirements.

That said, try to maintain the core principles: a continuous trajectory instead of a step function, short-term milestones instead of long-term ones, and regular check-ins.

Frequently Asked Questions

Q: How do I define milestones?

A: Ask yourself, what do I need to be able to observe in a couple of weeks to know that the worker is on track to become the kind of employee I want on my team?

From a people-improvement point of view, milestones do not have to be quantitative. Qualitative ones are also okay as long as they are specific and concrete (for example, “improve at sales” is too generic, but “learn how to ask good questions” is okay). But check with your HR partner if there are specific requirements.

Q: How do I avoid employee resistance or defensiveness?

A: Position the framework as a collaborative tool for success rather than a punitive measure. Avoid mentioning the need for improvement as coming from you (that sounds arbitrary), but instead explain that it’s required by the job and necessary for the team/organization/mission. Emphasize that clarity benefits them by providing a fair opportunity.

Q: Where do I find the time for fortnightly check-ins?

A: These meetings need not be lengthy: 15 minutes is often sufficient. That said, remember that if you don’t do these meetings, you save 15 minutes but will have to spend much more than that compensating for your worker’s underperformance in other ways.

Conclusion: From Steps to a Trajectory

By shifting from a vague improvement process to a clear trajectory with visible milestones, you transform an uncomfortable situation into a structured path forward. This approach helps you have more productive conversations, create actionable improvement plans, and reach fair conclusions quickly.

Download this as a PDF

The complex approach involves developing or purchasing specialized AI tools that integrate with existing databases and processes. This path typically requires significant investment, extensive compliance reviews, and coordination across multiple stakeholders.

The second approach consists of giving your employees access to general-purpose AI assistants (such as ChatGPT, Copilot, Gemini, or Claude) and training them to use them to improve their personal effectiveness. This method yields substantial productivity gains for knowledge workers with minimal infrastructure changes (we will see examples shortly).

While these two approaches complement each other, many organizations overlook the second one, missing huge effectiveness gains. This hesitation often stems from uncertainty about practical applications and concerns about adoption and potential errors or misuse. This short article explains how to deploy this simpler approach while avoiding most of these concerns.

Practical Applications for Immediate Impact

Let’s begin by seeing a few concrete ways in which AI assistants can help you and your team (we will cover implementation later; for now, let’s focus on the possibilities):

• Reducing stupid mistakes. AI can review communications not just for typos and similar errors but also for potential misunderstandings, likely objections, and missed action items and deadlines.

• Pre-empting failure. AI assistants excel at pre-mortems: ask the AI to imagine scenarios in which a meeting, sales call, or project might go wrong and suggest countermeasures.

• Improving soft skills. Writing clear emails is a core skill for every knowledge worker, yet it is seldom trained. Same for compiling reports, preparing proposals, and drafting presentations. AIs aren't yet good enough to complete these tasks autonomously, but they can provide feedback and opportunities for improvement.

Before we continue with a few more examples, let me highlight a key pattern. In all the examples above, AI is used not to replace a worker or automate a task but rather to help workers be more efficient, effective, or reliable – and to improve their skills. In 2025, I believe this is where the lowest-hanging fruits lie.

Let’s see a few more high-value applications:

• Decision Support: Help analyze options against criteria, identify blind spots, and expand consideration of variables and consequences.

• Process Documentation: Creating and updating standard operating procedures, training materials, and process documentation.

• Personalized Development: Generating customized learning paths, practice scenarios, and feedback – basically functioning as an on-demand professional coach.

The above are just some of the many possible use cases. Soon, more will become viable as AI assistants add capabilities and reduce error rates. As Tyler Cowen puts it, "This is the worst they will ever be."

Fighting resistance to change and getting AI adopted by your team

Here are a few common mistakes I see managers doing:

• Abstract communication. Instead of presenting AI as an all-powerful tool with generic benefits, focus on specific, immediately relevant use cases customized to your team's needs. Explain how AI can be helpful to them, not to their manager or organization.

• Adversarial framing. If you say or imply, “I, the manager, need you to abandon doing things your way and adopt this new method,” you inadvertently frame the conversation as you-vs-me, causing defensiveness. A better approach is to frame the conversation as “you and me against an external enemy,” which could be excessive workload, the competitors getting ahead, etc.

• Trying to change too much at once. If you try to get your people to use AI for too many tasks, you won’t be able to cover one well enough to convince your people it can be used successfully. Much better to focus on them adopting AI for a single use case and ensuring that it works so well that they will be eager to use it more.

Rules and Personal Judgement

Rules and procedures are useful, but, especially when it comes to AI, you also need to cultivate your people’s personal judgment so that they are able to spot eventual errors or navigate unforeseen scenarios. Thankfully, doing so is much easier than commonly thought – if you train your people not (just) by giving them procedures but also by running hypotheticals.

Hypotheticals

The fastest way to build experience and expertise in your team is to schedule a 30- to 60-minute session in which you do the following:

1. List 5-10 common and uncommon scenarios, problems, and dilemmas your team might encounter while performing a given task. (To save time, prepare this before the session.)

2. Mention the first scenario and ask your team what they would do in that situation.

3. Provide feedback, such as “Good idea, because…” or “That doesn’t consider that…” (It’s critical that, both for positive and negative feedback, you explain your reasoning thoroughly.)

4. Move to the next scenario, problem, or dilemma.

This exercise enables you to provide your team with months of experience in just a few minutes. Repeat it as long as necessary.

Hypotheticals are also a great way to prepare your team to identify eventual AI errors or hallucinations.

The importance of the first impression

There’s nothing worse than giving your team access to a powerful tool without explaining how to use it effectively: they will try it once, it won’t go particularly well, and they will lose interest.

Instead, it is paramount that their first experience goes smoothly and yields useful outcomes. Do your homework and make sure you pick a relevant use case for them to use the AI tool. Give them a few examples, show them a few good prompts, and coach them through their first use of AI. Ensuring they have a great first experience is key for effective and engaged adoption.

Conclusions

Of course, there is much more to say and do on how to identify tasks where AI assistants can help, how to get your people to use them, and how to train them to spot eventual AI errors and hallucinations. I plan to write more about it in the future.

For the moment, let me repeat some core principles:

• In addition to looking for complex and structural ways to integrate AI into your organization’s processes, also look for simple ways in which individuals can get AI assistance on their tasks and skills development.

• When introducing AI, do not discuss AI tools generically but lead with specific use cases.

• When training your team, after you give a couple of examples on how to use AI assistance, use hypotheticals to provide them with experience and increase their personal judgment.

Training your team on using AI assistants is important not just for the benefits it can yield today but also because it prepares you and your team with the skills and experience required to leverage the inevitable improvements in AI tools that will become available soon.

Want to discuss AI adoption further?

If you are a leader, manager, or supervisor, and you either already adopted AI tools or are looking to, I’d love to chat with you. You can reply to this email or use ​this link​ to schedule a short call.

Hard vs. Soft metrics

Hard metrics are quantifiable and objective—revenue generated, units produced, customer acquisition costs. Soft metrics are qualitative assessments of performance areas like meeting effectiveness, communication quality, and team collaboration.

Whenever I mention that managers should pay attention to both hard and soft metrics, I often get a divided reaction. Half of the audience nods, knowing how important discussing soft metrics is to develop talent and improve effectiveness at what would otherwise be neglected. The other half frowns, anticipating uncomfortable conversations and subjective disagreements.

However – and this is critical – this only happens if you discuss soft metrics infrequently, say, once a quarter or less. In this case, I agree: you and your subordinate will likely differ in your assessment of how well they performed against a soft metric. Even worse, if this discussion takes place during a formal performance review, the risk that it leads to defensiveness, blame, or frustration is high.

But if you discuss soft metrics frequently (at least once a month) and you do it in informal settings (say, at the end of a one-on-one meeting on another topic), the conversation will be more open and constructive.

The Superiority of Soft Metrics for Skill Development

Soft metrics are exceptional tools for developing skills and effectiveness. Allow me a basketball example: if a player struggles with scoring, setting a hard metric like "points per game" only helps if their limitation is motivation. If their shooting technique needs improvement, this metric may actually encourage counterproductive behaviors, such as taking poor-quality shots to meet their target. Conversely, a soft metric like "shot selection quality," discussed frequently after games and practices, addresses the underlying skill gap and leads to sustainable improvement.

How to Set and Evaluate Soft Metrics Effectively

Soft metrics require more definition than hard ones. When you set a hard metric like "$5M in revenue," the meaning and measurement are clear.

Conversely, when you set soft metrics, you cannot assume that your delegee knows what a good outcome means. For example, what does “running effective meetings” look like?

The key is to give examples of what the good and the bad would look like. What does it look like when meetings are run ineffectively? And what does it look like when they are run effectively?

Even better, I like to use my “bad/good/great” framework, which also includes what great performance would look like.

Finally, avoid the temptation to measure soft metrics using hard outcomes (e.g., measuring meeting effectiveness by project completion rates). While convenient, this approach fails to develop the specific skills that need improvement.

Conclusion

Complement your hard metrics with carefully selected soft metrics to support your team's development. Provide concrete examples of what bad, good, and great performance looks like for each soft metric. Most importantly, discuss performance frequently in low-pressure settings rather than saving these conversations for formal reviews.

Implement this approach consistently, and within a few months, you'll see both soft and hard metrics improve as your team develops new capabilities and greater effectiveness.

Suggested exercise: This week, identify one soft metric that would address a current challenge. Define what bad/good/great looks like, and introduce it in your next team meeting.

1. They just focus on providing a tool without also ensuring it gets used and used well.

2. They do not see supervisors (their buy-in and their leadership skills) as the #1 determinant of whether teams adopt new tools and processes.

3. They focus on using AI on a worker’s core tasks, forgetting about its ancillary ones (which are often better targets).

Let’s examine each point and provide examples and solutions.

1) Examples, examples, examples

We can divide the population into four types based on how eagerly they adopt a new tool or technology, such as AI:

• Alpha users: just give them the tool, and they will figure out how to use it.

• Early users: they need both a tool and relevant and concrete examples of how to use it.

• Late users: in addition to the above, they need to see other people like them to use the tool successfully.

• Resistant users: they won’t use the tool until forced to.

Unless you deliberately configured your hiring process to only target alpha or early users, your organization probably contains all four types.

Your AI adoption strategy should take this into account. Hence, it should not only make AI available to workers but should also give them relevant and concrete examples of how to use it, ideally in person by their direct supervisor or peers.

Note that it’s not enough to provide generic training – such as “how to use this AI tool regardless of whether you’re a project manager, salesperson, or engineer.” People need relevant and concrete examples.

As a rule of thumb, if your training material could be given to multiple roles within your organization, it’s not relevant enough and won’t drive the adoption of the new tool.

2) Get supervisor buy-in and train them on training others

People won’t change their ways just because their CEO asked them in a corporate-wide email. They need to see that their direct supervisor is actively committed to it, too.

If their supervisor doesn’t use AI, they won’t use it either.

If their supervisor doesn’t care daily about whether they use AI, they won’t care either.

Supervisors are the lynchpin of any tool or process adoption strategy.

You must work closely and frequently with them to ensure they are committed and transform this commitment into visible yet genuine actions – such as using AI themselves or coaching individuals into integrating AI into one of their sub-tasks (more on this in the next point).

Moreover, you must ensure they can do that in a way that is helpful and effective – as opposed to cringe or meddling. You cannot rely on them already knowing how to do that – you must train them.

3) Focus on subtasks

There are some jobs where AI can easily and effectively help with the main task – translators, some coders, etc. What about the rest, though?

For most jobs at the moment of writing, the core task cannot be delegated to AI yet – AI is not good enough, or maybe human touch is still a requirement, as in most sales jobs, or perhaps AI would be mostly ready, but we cannot tolerate errors. Either way, when the core task of a job cannot be delegated to AI, it is tempting to default to “therefore, that job should still be 100% performed by people.”

However, there are alternatives. What about the non-core tasks of a job? For example, a salesperson might still want to conduct sales in person but use AI for repetitive tasks, such as administrative ones, or to prepare for a sales meeting.

Or what about sub-tasks? For example, maybe you want to keep a human in the loop of a critical task, but there are parts of it that can benefit from AI.

Either way, my advice would be not to treat jobs as a monolith but rather see them as an ensemble of tasks and consider whether any subpart of it can benefit from AI – and not necessarily for full automation but either partial automation or augmentation.

What are your challenges?

I fully know that there are many more obstacles than the three I listed above – such as legal issues, ROI concerns, job security fears, lack of bandwidth, and more. I’m eager to hear about your challenges or doubts in getting AI adopted across your team or company.

If you are a leader, manager, or supervisor, I’d love to chat with you. You can use this link to schedule a short call.

Books

In 2024, I published ​"Winning Long-Term Games,"​ which is probably the book I'm the most proud of.

I also started writing a book titled "Poverty and Prosperity," which will likely see the light in 2025.

Videos

I published several videos on ​my YouTube channel​:

• ​Winning Long-Term Games​ (the recording of my 2024 VALUEx Berkshire speech)
• ​Starbucks and the contribution ladder​
• ​More effective mentorship meetings​
• ​Reproducible Success Strategies​
• ​Training Agency​

Podcast

In 2024, launched a podcast where I interview CEOs and COOs. My guests were:

• ​Mark Brooks​, COO of Permanent Equity
• ​Molson Hart​, CEO of Viahart
• ​Blake Janover​, CEO of Janover Inc.

Podcast guest appearances

Thirteen podcasts invited me as a guest in 2024.

Here is ​the full list​.

Posts

I published 28 posts in 2024. Here is ​​the full list​​, with the most popular ones pinned at the top and the option to filter them by subject.

Twitter threads

As always, I've been fairly active on Twitter. Here is ​a curated list​ of my top Twitter threads.

Work

You probably know me as an author, but my main source of income is my activity as a business consultant.

In 2024, I worked on mostly three types of activities:

• **Individual Consulting: **I work with individual CEOs and business leaders to help them develop their teams, grow their companies, and overcome bottlenecks.
• Workshops: Training leadership teams on topics such as cultural change and developing their subordinates.
• **Managerial Capabilities Assessments: **A series of interviews with a company's employees to establish problems and opportunities with how people are managed.

I plan to do more of the same in 2025.

Pandemic Preparedness

In 2024, Vitalik Buterin's Kanro Foundation supported me in producing some educational material regarding pandemic preparedness.

I have created a ​YouTube playlist​ with the videos I produced and ​an educational website​.

My revamped website

I updated ​my website​ with a few new functionalities, including a better overview of ​my books​ (faster, prettier, and displaying the reviews), all ​my courses​ in a single place, and easier to browse and filter ​posts​ and ​podcasts​.

That was it! My best wishes for a great 2025,

This tendency toward static thinking was formally identified by Italian economist Sandro Brusco in his Superfix Model. But why is it so hard to think dynamically?

I believe that the root cause is our fixation on thinking about wealth in terms of dollars. You see, the moment we introduce dollars in the conversation, we start to anchor our thinking to existing prices. We believe that if a house costs $X, if we all have $X, we can all have a house – whereas in reality, if everyone has $X more, the price of houses rises, too. We believe that if a wealthy life requires $Y, if everyone had $Y, we would all be wealthy – but that's true only if the supply of goods and services increases, too – otherwise, there will still not be enough for everyone.

A better alternative

A better alternative to thinking in terms of dollars is to think in terms of goods and services. Instead of asking ourselves how much a home should cost, let's ask ourselves how we can ensure we build enough homes for everyone. Instead of asking ourselves how much someone should earn to live a comfortable life, we should ask ourselves how we can produce enough goods and services so that everyone can have one (instead of having to bid money to access limited supplies).

If we started doing this, it would become evident which policies lead to poverty (those that disrupt the supply of goods and services) and which lead to prosperity (those that facilitate it).

Don't get me wrong. I am not naively assuming that wants are immutable. For example, even if we build enough homes to house everyone, people will complain that they cannot get a sea view. Nor am I saying we shouldn't think in terms of dollars – currencies are extremely valuable tools to facilitate trade, allocate scarce resources, and keep opportunity costs low. What I'm saying is that a large portion of the current public policy debate lacks a basic understanding of how the economy works – and with respect to that part of the discussion, forgetting about dollars and instead reasoning in terms of goods and services would produce much smarter policy-making.

Yet, chess also contains a luck component.

We know it does because if chess were solely about skill, we would expect the stronger opponent to win all games. Instead, when players are of similar ability, the stronger one only wins a small fraction of games. For example, in the latest Chess World Championships, held in 2023 in Astana, Kazakhstan, the winner only won 4 out of 18 games against the other finalist (and lost three; the rest were draws).

Imperfect Information

One reason we believe chess is a game of pure skill is that we assume perfect information. If we knew which tactics our adversary prepared against, given enough skill, we could know what the best next move is. But if we do not know which tactics our adversary studied last night, we can only guess what the best move is. The most we can do is to assign a probability, such as “I think there is only a 20% chance that my adversary studied how to defend this move, so there is an 80% chance that this is the best move.” And if the best we can do is to assign a probability to what the best move is, of course, whether we are right depends on luck – luck and skill, obviously, but not purely skill.

(If you are not convinced yet, think about the children’s game of “rock, paper, scissors.” It is a fully deterministic game, yet it’s almost all luck-based – especially if played in its “closed envelop version” that prevents using fast reflexes to “cheat.”)

Whenever there is imperfect information, there is a luck element, even in fully deterministic contexts.

It’s important to remember this. Underestimating the importance of luck is a common reason for bad decisions. Use strategies that work even if you have bad luck.

Imperfect Execution

That said, even if chess players had perfect information, there would still be a luck element.

People do not always perform at their best. Even the strongest chess player might fall sick or make a blunder, and the eventuality of that happening is at least partially due to luck.

Consider the following example, in which the strongest chess player plays two chess games against the second-strongest player. Both players play one game in full health and one game while sick. If they fall sick on the same day, the strongest player is likely to win both games, whereas if they fall sick on different days, the weakest player has a chance of winning the game on the day he is healthy, and his adversary is sick.

In this example, whether the strongest player wins one or two games is entirely due to luck – even though, of course, were he to win both games, he would 100% deserve the victory, and it would be right to attribute it solely to his skills and hard work.

Of course, it’s possible to lower the role of luck by having two players play multiple games against each other. That’s what happens in chess championships, and this is the takeaway of this post. Even in contexts overtly about skill, luck plays a role, too. Therefore, you must manage its impact, for example, by leveraging the law of large numbers and guaranteeing you can make a large number of attempts.

Skill and Luck

As the Chess Paradox demonstrated, skill being of paramount importance does not imply that luck might not be important, either.

This is important because a common reason smart people fail is that they become so focused on the importance of skill and doing things right that they forget that even if they do everything right, they might still fail.

Your strategy should allow for the possibility that you do everything right and still fail. Therefore, it should contain fail-safes such as having a plan B or ensuring that even if you lose this time, you can try again in the future.

Case study: sports

It is obvious that basketball is a game of skill. And it’s evident that the best basketball players – think about Michael Jordan, LeBron James, etc. – won because of their extreme talent and hard work.

Yet, there is a reason why the NBA finals are played in a best-of-seven format instead of in a single game. It’s because luck still matters, and playing multiple games reduces its influence.

You should consider applying a similar approach to your ventures. Reduce the impact of luck by making multiple bets – the more you make, the more the Law of Large Numbers will apply to you, and the more likely you will be to grab the rewards your skill would allow.

It never feels like a good time to perform maintenance, as there is always something more productive to do instead. Yet, you will not go far without it: eventually, your machine will break.

Maintenance never makes sense in the short term, yet it is indispensable in the long term.

Plenty of activities share this characteristic: working out, spending time with your loved ones, training employees, building a solid organizational culture, and managing risks are all activities that seem unnecessary in the short term yet are indispensable in the long term.

The root cause of the Maintenance Paradox is the deep-rooted belief that if we get the most out of each day, we will also make the most of the year.

But it just doesn’t work this way. Some actions, such as performing maintenance, have benefits that are only visible in the long term and, thus, are unaccounted for by short-term evaluations.

Short-term evaluations lead to suboptimal long-term choices.

Example: Why Managers Plateau

The Maintenance Paradox is a common root cause of why brilliant managers sometimes fail to have a brilliant career.

Managers constantly face high demands for their team’s output. So, it always feels like there’s no time for training. But unless they find the time to train their people, the situation will not improve. It actually gets worse over time as the work to be done outgrows their team’s capabilities.

The solution is to switch from short-term to long-term evaluations and realize that training is not only necessary but also makes the future easier, as people will be more efficient and effective.

Only managers who can shift from short- to long-term evaluations reliably succeed over the long term.

Summary

Improving skills, working out, resting, strengthening relationships, performing maintenance, managing risks, and taking a step back to consider the broader picture are all activities that seem like a waste of time in the short term yet are indispensable in the long term.

If you use only short-term evaluations to decide how to spend your time, you will make suboptimal choices and plateau.

Instead, use long-term evaluations. This doesn’t mean you should never take any short-term action; it means to take a mix of short- and long-term actions as optimal to sustain success over the long term.

The interaction between the two, depicted below, determines most of human behavior.

A common example

Imagine our cortex (the Planner) decides we should hit the gym. If our basal ganglia (the Gatekeeper) doesn’t like exercising, the cortex’s order doesn’t reach our motor areas, and we do not go to the gym.

What’s the result of liking an outcome but not the action that achieves it? Inaction, and thus, frustration.

The circuitry

The image below depicts a simplified schema of the actual circuitry that you would observe if you dissected a human brain. There is a pathway running from the cortex to the motor areas of our brain. Alongside it, there is an area of our brain called the basal ganglia that can inhibit the pathway, preventing the cortex’s orders from becoming actions.

This circuitry highlights a separation of roles.

The Planner (our cortex) makes plans but does not have direct access to our muscles. Hence, its plans are only suggestions.

Conversely, the Gatekeeper (our basal ganglia) cannot make plans but can block the Planner's suggestions from reaching our motor areas.

For action to happen, our cortex must suggest it, and our basal ganglia must approve it. If either is missing, we do not take that action.

Habit formation

To create new habits, we must ensure that both our cortex sends the orders we want it to send and that our basal ganglia let them reach our motor areas.

Sadly, most habit formation advice addresses the former only. It is either about making better plans or removing cues from our environment so that we do not come up with bad ideas (such as eating that bag of chips that’s on the table).

However, that’s cortex-centric advice that ignores the Gatekeeper. No wonder it’s not very effective.

Influencing the Gatekeeper

So, what causes the Gatekeeper to open or close the gate? It's simple: experiential memory. The gate opens when the suggested action is remembered to have brought positive emotions in the past.

We have already seen that the Gatekeeper cannot imagine or plan, only remember. The part of you that can imagine, plan, and consider indirect or long-term consequences is the Planner, not the Gatekeeper. Knowledge, imagination, and planning help generate good suggestions but do not guarantee execution, nor do they prevent bad ideas created by instincts.

Hence, we have two ways to influence the Gatekeeper.

First, we can try to feel emotions. If we feel a strong positive emotion when we think about doing an action, we will be more likely to do it. However, note that emotions are only associated with doing the action count, not emotions associated with the reward. That’s why it’s so hard for many people to go for a workout, even though almost everyone has positive associations with looking fitter. Only how we feel about the action counts, not the outcome. (More precisely, how we feel about the outcome only matters in the measure it creates feelings about the action.)

The second way in which we can influence the Gatekeeper is by creating new experiences that associate a positive emotion with the suggested action.

The key principle

For us to take action, our cortex must both think about it, and our basal ganglia must feel like doing it would feel good.

Hence, habit formation must speak BOTH to the Planner and the Gatekeeper:

• To the Planner: offering better knowledge, more cues for positive actions, fewer for negative ones.

• To the Gatekeeper: providing new experiences and creating new emotional associations.

We must acknowledge that our Planner (our thinking self) cannot just "convince" the Gatekeeper to change. It can only do so indirectly – by planning actions that the GK is already willing to take and having those actions create new emotional associations.

This post is a brief summary of the behavioral model I describe in one of the chapters of my book, "The Control Heuristic." Read the book to learn more about it and behavioral change.

Good long-term strategies have three properties.

1. They are sustainable. They do not require risks or sacrifices that you cannot take for long without severe consequences or that would clash with your other long-term goals.

2. They are constructive. They play iterated games and build, instead of consuming, the long-term assets that bring long-term success (such as trust, know-how, relationships, capital, etc).

3. They move towards inevitability. They proactively surface and address problems; they learn and adapt. They do not merely provide a chance of success but do what’s required to almost guarantee it.

As you can see, long-term strategies not only have a long-term time horizon but also embrace it and leverage it to achieve better and more certain outcomes than what a short-term strategy can reliably achieve.

Let’s see the three properties in greater detail.

Good long-term strategies are Sustainable

Working overtime is a great tactic to maximize this week’s productivity. Not only will you get more done, but a week of evenings spent working is unlikely to cause burnout or a divorce.

But work overtime every other week for several years in a row, and burnouts and divorces become much more likely.

Similarly, sending a sales email to your mailing list is a great tactic to increase sales. But if all you send to your mailing list is sales emails, people won’t read your emails anymore.

Some tactics are useful but shouldn’t become strategies: they are suited to short time horizons but not long ones. At most, they should be used sparingly and wisely as parts of a longer-term strategy.

This means that:

– Long-term strategies can contain risky projects, but those projects should only be risky in the sense that they might not work and never in the sense that their failure might endanger the strategy.

– Long-term strategies can use tactics that consume long-term assets (such as health and trust) but must use these tactics sparingly and alternate them to enough periods of building the assets they consume.

Good long-term strategies are Constructive

If you have three shots to throw a ball in a distant hole, it doesn’t make sense to use all three shots to attempt a hole-in-one. Instead, use the first shot to get closer to the hole so that the other two shots are more likely to go in.

Similarly, too many people fail to achieve their life goals because they spend years working on projects that are “hole-in-one shots.”

Not only do “hole-in-one” projects have low chances of success, but when they miss, they do not make the following projects more likely to succeed.

If you have a long-term horizon to achieve a goal, it doesn’t make sense to use tactics that are optimal for holes-in-one. You want to use strategies optimal for a hole-in-three. Strategies that progressively get you closer to your goal.

Ask yourself: what assets (skills, habits, relationships, resources, etc.) would make your future projects more likely to succeed?

Long-term strategies take the time to build these long-term assets, even when it doesn’t seem like a good moment to do so.

The key to success is to spend more time on important-yet-not-urgent activities than most of your peers.

Good long-term strategies are Inevitable

Many long-term strategies are variations of the following: do a few projects that might fail, but do them in such a way that failure doesn’t compromise future projects, and in such a way that even in failure, you still build know-how, trust, and relationships. If you do so, eventually, you will succeed.

As you can see, good long-term strategies often include projects that might fail, but only in the context of a strategy that cannot fail.

Do not take the “cannot fail” too literally. Whether a 100% success rate is possible is irrelevant. What matters is not to be satisfied with less than that and continuously ask yourself, “What might cause me to fail, and what can I do about it?”

Asking that question might reveal that you are taking too many risks or perhaps not enough.

It might reveal that you are going too fast, skipping steps, or perhaps that you are being too slow or complacent.

It might reveal that there is some lesson you don’t want to learn.

It might reveal that there is some help you refuse to ask.

It might reveal that you’re using the wrong strategy.

From that one question, you might learn a lot.

The point is, never treat your strategy as you would treat a tactic. You can tolerate tactics that might not work, but you cannot tolerate strategies that might fail.

After all, you only get one life. Make your strategy inevitable.

Bad long-term strategies

We have seen the three properties of good long-term strategies: they are sustainable, constructive, and make success inevitable. Now, let’s see a few red flags of having designed a bad long-term strategy:

• It is not sustainable: it might bring you some early growth but cannot sustain it over time.

• It is not constructive: it doesn’t build the long-term assets required for long-term success.

• It is not inevitable: it might lead you to success but might also not.

• It is not actionable: it has no clear next step you can work on today.

• It relies on the future not changing: it doesn’t incorporate learning and adaptation.

• It focuses on a single area of your life and neglects the rest. It might bring you to a pyrrhic victory, in which you achieve your objective, but it might still not matter because you compromised another important area of your life.

There are more red flags of a bad long-term strategy, but the above ones are the most important, and adding more to the list would dilute it and make it worse.

Note: this was an excerpt from my book, "Winning Long-Term Games."

Worse: "Here is what I want you to do…"

This approach is prone to miscommunication. You and your delegate probably have different definitions of "good enough."

Decent: "Here is what I want you to do… this is what a bad result looks like, and this is what a good result looks like."

This is better. It explicitly defines "good enough, " which makes underperformance less likely. Moreover, if the delegate does underperform, discussing it will be less awkward.

Best: "Here is what I want you to do… this is what a bad result looks like, this is what a good result looks like, and this is what a great result looks like."

This is the best approach, for it opens the door to great outcomes.

Note that it's not just about raising the bar (for example, saying: $300k in sales is bad, $500k is good, and $750k is great). It's about painting a visual representation of what a great outcome looks like. For example, imagine you tell your delegee, "If you deliver the presentation and the audience doesn't clap, it's bad; if they like it, it's good; and if they go tell their friends and colleagues, it's great." That shifts the focus from merely preparing a few slides and rehearsing them to deliberately thinking about what else must be done to make it memorable.

The two takeaways

The first takeaway is that merely highlighting what's enough and what's not enough is likely to lead to just okay outcomes, whereas highlighting the difference between good and great is more likely to lead to great outcomes.

You can use this framework not only while delegating but also while communicating and writing job descriptions.

The second takeaway is that this framework, "bad / good / great," is a fantastic tool for upskilling. You can dramatically improve someone's skills by showing them what great looks like (as opposed to just demanding improvement).

In fact, it's such a great framework that I recently developed a workshop centered around that.

It is centered around the foundational skills of people management (delegation, communication, feedback, hiring, performance management, etc.). For each skill, we will see the difference between how to do it well and at a great level.

It's useful for improving your managerial skills and, more importantly, for obtaining the tools and examples to upgrade those of your team.

It's a 2-hour group workshop held over Zoom. I keep the classes small, at a maximum of 12 people, and I teach it personally (no bait-and-switch with inexperienced facilitators).

I will hold it on January the 29th, 2025. If you cannot make it but are still interested, let me know. I also organize private workshops.

Read more about the workshop here.

Lack of clarity shows up as paralysis, busywork, demotivation, and other forms of friction

2. People believe you up to your consistency.

If you delegate a task saying it's important but then don't check whether it got done, people won't believe it was important, and won't believe you the next time you say something is important.

3. People listen to you up to your helpfulness.

If your feedback isn't helpful, people won't listen to it.

If working on the task you delegate isn't ultimately useful for your employees, guess what, they won't work for you (beyond the bare minimum to avoid getting fired)

4. People are motivated by the rewards they experienced

Financial incentives motivate more effectively people who have already experienced the pleasure of receiving a bonus.

Start with short-term achievable targets to build trust that pursuing targets is worth the effort.

5. What gets discussed, and not merely measured, gets improved.

Collecting metrics won't improve a process unless those metrics are discussed in a way that makes it clear that people won't be let off the hook until they improve (see #2: people believe you up to your consistency)

For example:

• I polish a presentation deck more than the attendance will care.

• I spend hours researching a topic that’s only tangentially related to my work.

• I get nerd-sniped and spend one hour developing a script that will save me thirty minutes.

In all three cases, I do something work-related, but for the benefit of my pure enjoyment and not of my customers. There’s nothing inherently wrong with this – as long as we correctly categorize it as hobby time and not work time.

The importance of categorizing Hobby Mode as such

I am not alone in this tendency to spend part of my work hours in hobby mode. For example, I work with an entrepreneur who has the tendency to get nerd-sniped and spends a significant portion of his work hours developing tools for his team, even though it’s not the best use of his time. We solved this by acknowledging that the time he spends doing that should be categorized as “hobby time” and boxed into some specific slot of his schedule (say, “Friday afternoons are for hobby model.”) That allows him to spend the rest of his week fully focused on supporting his team.

If one truly cared about maximizing effectiveness, they would minimize hobby mode. However, life is about more than just effectiveness. Hence, it’s okay to spend some time in hobby mode. The key is to label that correctly and to be deliberate about it.

Recognizing Hobby Mode

So, how do you recognize hobby mode? It’s tricky because it looks like work and arguably has at least some work-related value. (Here, by “hobby mode,” I do not mean time spent in hobbies unrelated to work – say, gardening – but time spent doing work-related tasks that feel like hobbies.)

The defining characteristic of hobby mode is a high opportunity cost. Your time is doing something of value, but it would create much more value if you spent it doing something else – or if you did that task more efficiently, only doing the necessary and avoiding the superfluous.

Again, I’m not saying by any means that you should maximize work mode. However, you probably need to spend at least some of your time in work mode (depending on your desired lifestyle and other ambitions), hence the need to correctly label hobby mode as such and be deliberate about how long you spend in it.

Hobby Mode and Innovation

A common counterpoint is that hobby mode helps with innovation. This is true, but that’s a good reason not to fully avoid hobby mode – not to engage with it without bounds. Again, the key is to be deliberate about the balance between work mode and hobby mode.

It’s a bit like the difference between eating and overeating. The former is healthy and enjoyable, whereas the latter is unhealthy and, frankly, not that enjoyable either. The key is not to avoid eating, obviously, but to be deliberate about it.

That’s because, even if there were no real connection between looks and humor, we'd still notice many cases where highly attractive people seem less funny than average. It's simple mathematics at work, and the following example explains why.

Let’s imagine that there is no relationship between attractiveness and funniness. If we take a random group of 100 people, both attractiveness and sense of humor will vary, as displayed in the chart below.

If you take the people who score a “10” on the attractiveness scale, their average funniness is going to be 5.5. This means that very beautiful people will be less funny than attractive – even though, and this is key, there is no relationship between the two variables, and it’s all a selection effect!

1. Managers proactively let their people know where they’re spending time and effort on the unnecessary.

2. Managers give ambitious employees tasks that are ambitious enough so that, if the employee succeeds at them, there is enough windfall to reward them with career growth.

3. Managers give early and frequent feedback. This helps workers know when they’re going off track before it’s too late. It thus prevents frustrating surprises or wasting efforts on actions that cannot be rewarded.

4. Managers help spot and fill competency gaps in their people. It’s frustrating to be assigned a task and fail because you lack the information or skill to succeed. A manager helps fill such gaps before they lead to frustration.

5. Managers make the employees’ jobs less frustrating. This includes removing excessive bureaucracy, providing adequate tools, and addressing internal disputes and friction between departments.

6. Managers proactively let their people know the hidden purpose of tedious tasks, well-knowing that the difference between tedious and demotivating is purpose.

7. Managers talk so clearly & concretely that what they mean is clear to everyone. They don’t clarify misunderstandings but prevent them.

8. Managers find for their demotivated employees small but value-adding tasks they can succeed at.

9. Managers respect their employees' time. While requiring overtime might be occasionally necessary, managers take proactive action to avoid unnecessary overtime.

10. Managers don’t give up easily on demotivated employees, understanding that demotivation is just having learned the lesson that efforts go to waste. Therefore, they find ways to direct their people’s efforts to tasks that will teach them the opposite lesson.

11. Managers give motivated employees outlets to put their motivation to use.

12. Managers interpret abstract objectives, telling each worker what concrete actions to take and why. They never mention company-wide objectives and core values without immediately afterward explaining what they mean concretely to the individuals they’re talking to.

To summarize, managers prioritize, delegate, help, explain, acknowledge, teach, and coach to ensure that their employees’ time and efforts at work are worthwhile (in terms of salary, growth, self-respect, security, or whatever resource the employee joined the company for)

I tend to agree with Cummings. In school, we spend quite some time discussing the differences between autocracies and democracies. However, we do not cover how the former arises from the latter. How does a pre-autocracy look like, and are we becoming one?

In particular, we do not cover nearly enough how we can prevent our current democracies from devolving into autocracies.

To do this, we have two instruments.

1. The first tool is called pre-mortems. It consists of imagining that the risk we are afraid of materializes in the future and then asking ourselves what the most likely pathway to that is. For example, let’s imagine that in ten years, our country became an autocracy. What might have happened? And what can we do today to prevent that?

2. The second tool is to observe how such transitions happened in the past in other countries. For example, what are some democracies that transitioned to autocracies? What mistakes did those countries commit? Is our country committing the same mistakes now?

The key to both exercises is to avoid thinking, “How likely is it to happen?” and instead focus on “If I don’t take care of this risk, eventually, it will materialize.”

Survivorship bias

It’s easy to think, “Our country is a democracy; we are better than other countries that are autocracies.”

But guess what? They also thought they were a democratic country when they were already pre-autocratic.

It’s a bit like that data point that 93% of US drivers believe they are better drivers than average. Until you get into an accident, you will think you are a better driver than average.

• Do you drive slow? You will think that that makes you a good driver.

• Do you drive fast? You will think that that makes you a good driver.

• Did you drive recklessly and almost got into an accident but managed to emergency brake at the last second? You will think that your great reflexes make you a good driver.

So, how can you know how good a driver you really are?

You can check whether your driving looks like the driving of the drivers that crashed – but not on the day they crashed, on the days before that.
If so, I’m sorry, but you might be at risk of a crash, too.

Problems grow the size they need for us to acknowledge them

If we want to avoid large problems, we shall tackle them before they grow large enough to justify taking action.

This means to regularly practice the exercises described above.
And not just in the context of our country’s governance but in all aspects of our lives.

Let’s imagine we executed our current strategy yet failed. What might be the most likely cause, and what can we do to prevent that?

How do others with the same goal as ours fail? And what can we do about it?

What does pre-failure look like? And how can we avoid that?

Contrary to common belief, thinking about these questions doesn’t bring anxiety. Instead, it is precisely what enables us to sleep well (because we know we took care of the most significant risks).

Notes

This essay was written as a chapter of my 2024 book “Winning Long-Term Games,” but got cut out at the editing stage. You can get the full book and audiobook here.

Bad: "What could I improve?"

Good: "What could I improve about the way I run weekly meetings?"

A generic question is likely to elicit generic, thus useless, answers.

Conversely, a specific question not only elicits more useful information but also helps the other person come up with suggestions.

2. Ask a question that implies there is something you could improve

Bad: "What could I improve about the way I run weekly meetings?"

Good: "What is one thing I could do better about the way I run weekly meetings?"

If you simply ask, "What could I do better?", your interlocutor will have to decide whether you really are open to criticism.

Conversely, if you ask questions such as, "What is one thing I could do better?", your interlocutor will only have to think about the suggestion, not about whether to make a suggestion at all.

3. Don't be defensive and make them feel listened to

Obviously, if you react defensively to feedback, people will stop giving it to you.

However, this does not mean that you should accept all feedback. Sometimes, you have a good reason for doing something a certain way.

The key is always to take your interlocutor seriously. Never question how a behavior of yours made them feel. Instead, acknowledge how you made them feel, and then explain transparently what will happen in the future.

Summary

Here is a brief overview of the three steps:

The result is that they limit their coaching motivation, prioritization, and accountability. While useful, this is only a small part of coaching and will only be useful if the coachee's bottleneck is motivation, prioritization, or accountability.

However, often, the coachee's problem is not one of these three but rather a lack of skills or knowledge. For example, a manager's limiting factor might be poor delegation skills or blind spots in how their industry works.

In this case, a more complete type of coaching is recommended.

What is coaching?

First of all, forget everything you know about coaching, for the term is often used for anything and nothing. For me, coaching consists of a mix of:

– Providing feedback and identifying opportunities for growth. The more specific, the better (for example, instead of “You should work on your presentation skills, say, “You should improve your diction and, in particular, get rid of the hmmm sounds”).

– Teaching how to do something well. This includes teaching what it means to do a particular task well and explaining not just what separates good from bad but also good from great.

– Roleplaying and playing hypotheticals to pre-empt mistakes, resulting in fast learning and setting the coachee up for success.

– Setting long- and short-term objectives. A coachee should end the session with a better and clearer to-do list than when they began it.

– Creating momentum by splitting large tasks into actionable bits.

– Providing accountability by demanding and reviewing progress.

Teaching frameworks I use when coaching

Here are some teaching frameworks I use when coaching.

– Bad, good, great. Given a task, role, or objective of the coachee, I explain what a bad performer would do or care about, what a good one would do or care about, and what a great one would do or care about.

– What’s too little, what’s too much, and common mistakes. This is a great framework for delegating tasks and objectives. Explain what a successfully completed task would look like, then mention what would be too little, then what would be too much, and finally, the common mistakes of people working on that task.

– Roleplay and hypotheticals. There’s nothing better than asking the coachee what they would do in a situation and providing them with some immediate feedback. It allows them to practice in a safe space and discover possible mistakes or misunderstandings without having to go through the effort and pain required by failing in the real world.

Interested in working with me?

I usually work with business leaders, managers, and entrepreneurs who want to grow their careers and organizations and believe that their bottleneck is not motivation but rather a lack of skills or context.

With my usual coaching clients, we meet over Zoom once every week or every other week for 45 minutes, for 3-6 months. For some clients with specific needs, we only meet for 2-3 sessions.

Email me for enquiries, stating your current position and career goals.

"Working with Luca was fantastic! He was straightforward and well-prepared, pinpointing numerous opportunities I had overlooked in my business plan. I wholeheartedly recommend him." – Christopher Samulliah

A core reason employees don’t receive enough training is that it is very time-consuming, and many teams are already overworked.

Moreover, most trainers “push” pre-prepared content onto the team. Because such content is pre-prepared and used to train many different teams, it cannot be very relevant to the specific team being trained today.

As a result, the team nods during the training but then goes back to their workstations and faces the same obstacles and questions it faced before – obstacles and questions that the training didn’t address in enough detail to be useful.

The solution

Here is how I deliver most of my trainings to corporate clients.

1. The training doesn’t contain any slides (even though, sometimes, I send optional pre-reading materials).

2. The training begins with me picking a topic (say, delegation), and asking the audience what problems they face in this respect.

3. Then, I address each problem in great detail. I ask them what they would do and give them feedback (“good idea, because…” or “bad idea, because…”). I explain what I would do in that situation, how I would do it, why, and what would happen if I did differently. I ask if what I said makes sense, if they see themselves doing it, or if they see any obstacle to that. This is because you cannot reliably solve people management problems by discussing them abstractly; you must discuss them concretely and in high detail.

4. Many problems are also discussed in the form of hypotheticals. I ask questions such as, “What would you do if you have an employee who refuses to take on a task,” then give them feedback on their answer, explaining why I think it would be a good idea or pre-empting possible issues.

5. We take anything between one and fifteen minutes to address each point. The objective is to discuss the obstacles in great detail to ensure that the attendees have all their doubts and reservations addressed. If I didn’t do this, the audience would nod as I spoke but would go back to their workstations unchanged.

6. A typical training session lasts 90 minutes, in which we cover 5-10 people management situations. The attendees leave changed, with better clarity on what they should do, how, and why. And they will actually do it.

7. After the session, I send the attendees an email with the most important points covered in the session. Again, this is not pre-prepared material, because it’s crucial that it addresses the exact problems this specific audience faced, using the words they use and using examples they live in their day-to-day.

Tried and tested

I have run dozens of such workshops with large multinationals from the tech, financial, and pharmaceutical sectors, and they have always proved very effective, thanks to their concreteness.

Why it works

In most trainings, the trainer talks about some procedure or framework, the attendees nod, but then go back to their workstations without anything having changed. That’s because the training didn’t address the real problems of the audience, their bottlenecks to action.

Most trainers circle around the hard questions that are what the audience needs to get answered: what do you do when there’s not enough time to do everything? What do you do when there’s a subordinate who is fully disengaged? How do you have hard conversations? How do you do it when turnover is already a problem?

Instead, my approach is all about surfacing and addressing these hard questions. It’s about acknowledging that the real world is messy and time is a major constraint. It’s about empowering managers by giving them the tools they need rather than the tools we think they need.

Moreover, I believe that it’s necessary to teach not only what the right things to do are but also how to do them right. Hence the focus on roleplay, on working on concrete examples, and on examining difficult and messy situations.

It’s an approach that produces results in the real world.

Case study #1

I recently delivered a couple of training sessions to the Finance Leadership Team of a major pharmaceutical company.

Not only the engagement during the session has been excellent (finally, a trainer that addressed their problems), but the growth in people management capabilities has been evident as well.

Case study #2

For nine years and counting, I’ve been teaching a risk management for manufacturing operations module at an Italian university.

I deliver 90% of it using hypotheticals. We go for hours with me asking questions (“what would you do on your first day…?” “what would you do to achieve X?”) and giving motivated feedback (“good idea, because…” or “bad idea, because…”). We also do plenty of roleplay, because one thing is to know at a high level what should be said, and another one is to be able to say it in a way that’s clear and convincing.

It works wonderfully. It is more active learning, covers more concrete situations, teaches know-how rather than know-what, and gets remembered better than just going through slide decks.

Example engagement

A typical engagement would look as follows.

• A first call with you, where I get information about your team and its day-to-day. Ideally, also a couple of calls with members of your team, to understand their problems.

• Two 90-minute workshops with your team, where we do hypotheticals. That’s where your people learn how to manage common situations proper of people management.

• A 30-minute one-on-one with you and each of your team members.

Such an engagement for a team of 8 people would cost around 3000€, assuming remote delivery.

I would personally run all the activities above, no bait-and-switch where less experienced consultants are involved.

All the activities above would be tailored to the situations your team face in their day-to-day, with no pre-packaged content that is irrelevant to your team’s reality.

They know metrics are crucial but incomplete without first-hand observations. Hence, they regularly visit operations, observe customers, and engage with workers at their workplaces.

This is not just because learning about the details of the business uncovers problems and opportunities (and might reveal that some metrics are collected in a way that misrepresents reality), but also because employees do not take seriously leaders who do not dig deep (“How can he know about my job if he spends all his time in meeting rooms?”).

2. Good managers front-load clarity

They do not wait for misunderstandings to happen to clarify what they mean. They are proactively clear.

They do this not only because misunderstandings are a waste of time, energy, and often money but also because misunderstandings, even when resolved, become precedents that lower the teams’ trust in their manager.

3. Good managers explain all decisions

One reason is to build skills. It is one of the most effective and time-efficient ways to increase your team’s understanding of the business.

However, a more important reason is that managers who do not explain their decisions might appear irrational to their team. This destroys trust that their manager is a leader worth following.

Similarly, businesses whose managers do not explain business decisions to their team might appear irrational or incompetent, which also destroys trust that they are worth working for.

4. Good managers play iterated games with their team

They do not delegate just to get something done but also to grow their people’s skills.

They do not give feedback just to correct a mistake but also to build trust and engagement.

They do not see interactions with their team as one-offs but as iterated games where each interaction is played not to get the most out of it but to make the next interaction better.

Good managers see trust and skills as compounding assets and relentlessly use every opportunity to build them within their team.

5. Good managers treat good performance with negative externalities as bad performance

Do employees take shortcuts, game metrics, violate core values, or destroy trust rather than build it?

Good managers dig deep (point #1) into how people achieve objectives, and do not consider an objective achieved unless it is achieved in a way that strengthens the company.

Moreover, hearing that you won’t get a bonus despite achieving your objective is frustrating. Hence, good managers are superclear since the beginning that only objectives achieved without negative externalities count (they front-load clarity, point #2).

Further reading

My two books, Best Practices for Operational Excellence and Managing Hybrid and Remote Teams, dig deeper into the concrete details and best practices business leaders can use to raise their team’s efficacy.

They represent a belief that it is worth forgoing some type of short-term opportunity because it would come with long-term costs or that it is worth paying some investment today to get a future payoff.

Because all Values come with short-term costs and long-term benefits, they only make sense over long enough time horizons. Hence, only people with long enough time horizons practice them consistently.

Of course, there are exceptions to the above: habits, peer pressure, and fear of punishment. Still, the point remains: time horizons have a massive influence on the practice of Values, for the longer the time horizon, the more sense it makes to practice the Value.

Arbitrarily-shortened time horizons

A common mistake in investing is to arbitrarily shorten your time horizon. For example, you might have 50 years to live, yet say that your time horizon is “5 to 7 years.” This is bad because it makes you take more risks than optimal (because they seem to have less time to manifest) and will make you underestimate compounding properties (for the same reason).

I see a similar mistake with “digital nomads” touring towns one after another, looking for one to commit to settling to. The problem is that if you think you’ll only stay in a town for three months, you won’t do things like building friendships with local communities that are key to enjoying a town. Arbitrarily shortening one’s time horizon might get in the way of exhibiting the Values that make life great.

Similarly, we often shoot ourselves in the foot when we wait until a romantic relationship is great to commit, whereas some level of commitment would be necessary for the Values that make a relationship great to emerge.

Lengthening time horizons

Marriage is a social technology to increase the time horizon of a commitment to make certain Values more likely to be practiced, such as Fidelity, Honest Communication, Mutual Growth, etc.

Similarly, it makes sense to ask ourselves, how can we lengthen time horizons to make Values more worthwhile?

What social technologies can we introduce for this purpose?

Yesterday, I was asked about what it means to be an adult.

I answered that to be an adult means to take responsibility and have learned how to commit.

Taking responsibility means acknowledging that one’s actions (or lack thereof) greatly impact one’s self (and others).

And learning how to commit means acknowledging that committing creates more value than retaining optionality.

"Most of the freedom I had before kids, I never used. I paid for it in loneliness, but I never used it." – Paul Graham

But why is commitment so hard?

The answer is to be found in why many people have trouble arriving to meetings on time. Punctuality is hard if we see arriving early as something to minimize. Similarly, the trick to commitment is to stop seeing optionality as something to maximize.

Don't get me wrong. Optionality and selection are still important. You shouldn't rush and you shouldn't settle. But. It is also true that building anything that matters requires time, and committing to a good but not best option produces better results than committing to the best option but too late or not fully.

Adulthood is the realization of precisely this. That commitment is not something you reserve for the optimal option but how you make good options optimal.

Who gets wealthier?

For such a small sample, a lot depends of luck. So, let's imagine there are a hundred Alices and a hundred Bobs.

Who gets wealthier?

The answer is counterintuitive

On average, the wealthiest person will be an Alice, but Bobs will be wealthier on aggregate.

Let me explain.

In the short term, Alices will grow faster. Therefore, they will accummulate more wealth than Bobs.

However, as time passes by, more and more Alices will fail. Not all, obviously, and that's why at the top we will mostly see Alices. However, these Alices at the top, are a subset of all Alices. Many more will have collapsed.

As more and more time passes by, we see the following stratification: a small top made of extra-wealthy Alices, then a large group of wealthy Bobs, and finally, a largish group of poor Alices.

Survivorship bias

When we look at the top, we only see Alices, and that might give us the wrong impression that Alice's strategy is better than Bob's.

However, if we look at the aggregate of all fund managers over the long term, Bobs accumulate more wealth than Alices. Hence, Bob's strategy is better.

As I use to say, the croupier is the only person at the casino with a money-making strategy. However, every day, he sees at least one player getting wildly wealthier than him. But he must resist the temptation to switch from his good strategy to the player's worse one.

What fund managers can learn from this

The hard part of a good long-term investing strategy is to avoid the feeling of falling behind when colleagues with riskier strategies get temporarily ahead – and especially to avoid that your clients feel like they're falling behind.

I can help you with this.

I can both reason with you on whether a long-term strategy is truly better and, perhaps more importantly, I can give you emotional stories and effective methods to convince your clients.

If you are interested, do not hesitate to contact me.

Note: this example is an excerpt from my bestselling book Winning Long-Term Games

This always backfires.

I get it, though. Bosses, investors, peers, society, and our egos set aggressive objectives, which pressure us into adopting short-term tactics. Moreover, when we look left and right and see those around us pursuing short-term objectives, we feel like we’re falling behind, which also pressures us into adopting short-term tactics.

But what then? After this objective, there will be another one, even harder to reach.

And reaching that objective will require skills we didn’t build (which require time).

The belief that pulling growth forward works is downstream the belief that if we get the most out of each day, then we also get the most out of the year. But it’s a false belief.

Long-term growth requires spending some days doing things that bring no immediate return but are necessary to enable growth beyond a certain point.

Those who skip building strong foundations grow fast until they inevitably plateau.

Don’t be tricked by their early success in believing you’re falling behind and must pull growth forward in order to keep up.

It’s almost never worth it.

The real culture war is between people who want to win (a more prosperous country) vs people who want to win the argument (more status even if it means less prosperity).

Positive-sum vs negative-sum people.

Who won the elections?

If you look within a country, it’s easy to see who won the elections. It’s either this or that party.

However, if you look from outside the country, things are different. It’s possible everyone lost the elections. That’s what happens when incompetent candidates get elected.

It’s also possible that everyone won the elections. Everyone’s better off when competent candidates get elected. Competence brings prosperity, and prosperity brings more rights – that’s why conservative, prosperous countries often have better social rights than progressive but mismanaged countries (though, obviously, this phenomenon requires a few years to play out).

Who creates environmental change?

If you look at a problem such as climate change with a short time horizon, it’s an awareness problem. The only way we can improve the environment this year is if everyone changes their habits.

However, if you look at the same problem over longer time horizons, decades, it’s a technological problem. I have a lower environmental footprint than my father, even if he was more environmentally conscious than me (the air quality in my town is much better than it was forty years ago because factories, cars, and heating pollute so much less).

Hence, the cultural war in this context isn’t who’s willing to make sacrifices for the environment vs who doesn’t, but who’s willing to improve our technology vs who doesn’t.

Who wants a solution vs who wants to be the solution.

The path forward

There have always been, and there will always be, people who want to win the argument more than they want to win full stop. People who care more about status than prosperity. More about status than the environment. More about status than everything else.

That’s this excessive ego that leads them to do so much evil. They might begin with good intentions, but then they repeatedly deliberately and malevolently ignore any shred of evidence that their actions might cause harm.

The solution is to call them out, over and over.

Every time they focus on intentions over outcomes.

Every time they focus on performance over substance.

Every time they focus on zero-sum over positive-sum solutions.

Every time they focus on winning the argument over winning full stop.

This way of thinking has a major problem, and it’s not just survivorship bias. It’s that when you study winners, it is hard to know what exactly, out of everything they did, made them win. You might study your favorite author, imitate their writing in all its details, and still fail to publish a bestseller – because writing a good book is only part of what’s required to become a successful writer.

Instead, a better approach is to study the Losers. Who wrote a great book yet failed to become a bestselling author? What obstacle did they fail to overcome, and how can you prevent the same mistake? For example, did they not learn how to produce a compelling book proposal? Did they not learn how to build an audience?

Of course, the two approaches are not mutually exclusive. You can learn from Winners and Losers.

In fact, unless you learn from both Winners and Losers, you will not know whether you’re learning lessons you can rely upon.

It won’t do you much good to learn a strategy used by winners if it’s also used by losers. Unless you truly understand both what makes the winners win and what makes the losers lose, you don’t know whether you will end up a member of the former or the latter.

History is paved with losers who did what Winners do. They did learn from the Winners but forgot to also learn from the Losers.

Don’t be like them.

Constantly ask yourself, how did people who pursued the same goal as me fail? And what can I do to avoid the same mistake?

If you do, you will realize that winning reliably is often more complex than apparent. There’s not just one thing you must do right. There are plenty of things you must do right. You must have hard and soft skills. You must be good at your craft and at building relationships. You must work hard and manage your health.

Fail to do any of them and the rest might not matter.

As many losers discovered.

And as you might learn from them.

To facilitate the understanding of this complex topic, I created a simple visual tool, which my students came to call the Dellanna Diagram.

For example, this muscle describes the reaction of our muscles when we lift some weights:

• If the weights are light, we lift them effortlessly, but nothing happens. We are in the yellow area.
• If the weights are heavy, we lift them with some effort, which triggers biological mechanisms that grow our muscles and make us stronger. We are in the green area.
• If the weights are too heavy, we injure ourselves. We are in the red area.

This diagram applies to almost every reaction people have to external stressors, problems, and feedback.

As another example, imagine your manager at work assigns you an objective:

• If the objective is too easy, you don’t learn anything. You are in the yellow area.
• If the objective is moderately hard, you learn something from it and become a better employee. You are in the green area, and that’s an antifragile reaction.
• If the objective is too hard, you might get frustrated and lose motivation, or you might even fail and lose your boss’ trust. You are in the red area, and that’s a fragile reaction.

The Dellanna Diagram is a useful tool for understanding how to become more antifragile.

Before explaining this, let me clarify a common misunderstanding. Antifragility is not the ability to merely survive problems or variations but to benefit from them.

Antifragility is not the ability to merely survive problems or variations but to benefit from them.

This is very important because if you merely aim to make yourself or your organization robust to problems, you will promote behaviors that leverage rigidity – a property that decreases antifragility. In fact, a rigid person or organization wants to minimize and avoid problems, whereas antifragile people and organizations do the opposite: they proactively surface problems in order to adapt to them.

Creating engagement

It might seem like the Dellanna Diagram of disengaged students and disengaged employees looks like the one below: problems are either too easy, triggering complacency (the yellow area), or too hard, triggering paralysis or frustration (the red area).

However, their actual diagram is like the one below. There is a green area. It’s just so small that it looks like it’s not there.

This is important because it means that there is a size of problems that is small enough to get acted upon yet significant enough so that solving it triggers learning and increased motivation.

Great teachers and great managers excel at finding the right problem to give to their disengaged students and employees, hitting them in the green area and triggering antifragility, progressively growing their skills and motivation until they become skilled and engaged.

If you are not convinced it’s possible, think about a 50-year-old person living a sedentary lifestyle. If they suddenly start going to the gym, they might believe that their body’s Dellanna Diagram only has a yellow and a red area: the weights they lift are either too light to create any muscle gain or too heavy to create pain and injury.

However, even for them, there is a right size of weights to lift that is heavy enough to hit them above after the yellow area and before the right one, triggering muscle growth but not an injury. That’s the green area.

And if they do find that size of weights and lift them, they trigger antifragility and get stronger, which means that they grow the range of weights that they can safely lift.

They grow their green area.

Becoming more antifragile

The Dellanna Diagrams are useful because they help you understand how you can become more antifragile.

How do you grow the green area?

Easy: by shifting the threshold between the yellow and the green area left or by shifting the threshold between the green and the red area right. Let’s see what it means.

Shifting the threshold between the yellow and the green area left means that problems that previously hit you in the yellow area and were ignored now hit you in the green area and trigger adaptation and strengthening. This means to start adapting to smaller problems.

Fragile organizations don’t start adapting to problems until the problem is large enough to become a priority – at which point, it’s usually too late.

Conversely, antifragile organizations understand that problems grow the size they need for you to acknowledge them, so they proactively surface small problems and adapt to them before it’s too late.

Shifting the threshold between the green and the red area right means that problems that previously hit you in the red area and caused failure now hit you in the green area instead and trigger adaptation and strengthening. This means to make yourself more resilient to large problems.

Fragile organizations overoptimize their investments, ending up with too little balance and resources to face unexpected problems.

Conversely, antifragile organizations understand that you can only adapt to problems you survive and that long-term efficiency requires capping short-term efficiency. Therefore, they always keep more resources than they need and never get in situations that might become dangerous in case of unexpected changes.

In the video below, I explain in greater detail what this means concretely, both for individuals and for organizations.

Watch video on YouTube

The way forward

I hope this introduction to antifragility and the Dellanna Diagrams helped you.

I frequently advise on how to make individuals and organizations more antifragile. If you have any questions or are interested in working with me, feel free to email me.

This is a common mistake we often make in our careers and lives. We choose what to do next based on whether it generates progress with no regard as to whether that progress leads to a dead end.

In the case of activists, engagement obtained through vandalic arts might grow their supporters today and might continue to do so tomorrow, but eventually, they will find it impossible to grow further, once they have run out of extremists to enlist and will have to begin engaging with the bulk of the population that hates vandals. Any progress obtained through short-term tactics leads to a dead end.

In the case of entrepreneurs, engagement obtained through exaggerated promises might grow their customers today and tomorrow, but eventually, they will find it impossible to grow further, after people understand they shouldn’t be trusted.

The tricky part is that short-term tactics work well in the short term. Often, they work even better than long-term tactics. However, growth obtained through short-term tactics eventually plateaus. It’s a dead end. A decoy that makes it harder to achieve your ultimate objective.

My suggestion to activists interested more in saving the planet than in scoring virtue points is to adopt some long-term thinking. The change you seek requires societal change, which you can achieve only in two ways: by being a tyrant or by being a leader that the majority of the population wants to follow. That requires creating trust, though. And the first step is to stop taking shortcuts that destroy trust.

And my suggestion to my readers is to consider what long-term assets (trust, health, relationships, etc.) you will need to achieve your long-term goals and to avoid any shortcut that consumes rather than building them.

I disagree. Observe what would happen if the arrow of time reversed. We would progressively lose tech, social rights, access to services, and abundance that we now take for granted.

For example, go back in time 30 years, and we lose smartphones and the internet. Cars get worse and more polluting. Houses get smaller and worse equipped.

This effect is even worse for the bottom parts of society. Go back in time 15 years, and access to the internet disappears, but only for the bottom ~half of society. Go back in time 60 years, and plenty of rights disappear, but only for those at the bottom of society (think about racial segregation). Go back in time 75 years, and plumbing disappears, but only in the houses of the poorest 20%.

Reversing the arrow of time seems evil, cruel, and a terrible injustice, not only making everyone’s life worse but especially worsening the lives of the bottom layers of society.

Why do we say that the world got worse, then?

Download the checklist

Here is the checklist mentioned in the video (PDF file).

Conversely, low-agency people follow the default path. When faced with an obstacle, they wait to be told what to do. Because they only work on someone else’s to-do list, they do not own their mistakes or outcomes.

Obviously, you would like your team to be high-agency.

However, most managers believe that agency is not a trainable trait and hiring is the only way to increase their team members’ agency.

They are wrong. Not on hiring – that’s still the most effective way to get higher agency people in your team – but on whether agency is trainable. It is largely trainable. You just need to know how to do it (it’s because most managers do not know how to do it that it looks untrainable).

The trick is to understand how agency works.

How agency works

"When you’re told that something is impossible, is that the end of the conversation, or does that start a second dialogue in your mind, how to get around whoever it is that’s just told you that you can’t do something?" – Eric Weinstein

That second dialogue is agency.

Having that second dialogue is an action, albeit a mental one, and like any action, it is gated by motivation.

In other words, you have this second dialogue only if you believe it’s worth having it – which depends on your previous experiences with having that second dialogue.

If someone has low agency, it’s usually because, in the past, having that second dialogue led to bad experiences.

You teach agency by letting your people experience that having that second dialogue leads to good outcomes.

How to teach agency

First, let me tell you how you would do it in an idyllic world.

1. Assign one of your subordinates the smallest task requiring agency you can think of. It has to be job-related and meaningful, but it doesn’t have to be big. In fact, the smaller, the better. For example, “Find two ways we can lower our costs and verify their feasibility.”
2. Make explicit that you expect them to use agency. For example, “I expect you to tackle any unexpected problems.”
3. Make a concrete example illustrating the previous point. “For example, if you do not know how to do any part of the task, I expect you to google that, and only if Google doesn’t have the answer, ask a colleague.”
4. Get them to work on the task.

When they complete the task, acknowledge their successful outcome, specifically pointing out your appreciation for their display of agency. This will teach them not only that they have the skills to be high-agency but also that it’s easier and worth it.

Bam, that’s it. Doing this a few times with each of your subordinates should be enough to transform 30%-80% of them into high-agency people.

The problem is that, in the real world, if you ask low-agency people to do something high-agency, they might still try to do it the low-agency way.

Hence, there are three things you should be paying attention to:

1. The task must be as simple and easy as possible. Of course, it should still be relevant to their job and require some agency, so don’t come up with a trivial task. But it should be something that ideally can be completed in no more than a couple of hours. The larger the task, the higher the chances they fall back into low-agency mode.
2. You should be extremely explicit and specific in your request for them to be in high-agency mode while completing the task. Give them a few concrete examples of what completing the task in low-agency mode would look like, and tell them it won’t be enough. For instance, if the task you assigned was to invite a client to a customer event you’re organizing, you can say something along the lines of, “Just inviting the client to our event is not enough; you must make sure they read and accept the invitation, and if they really cannot come, find ways to set up a later meeting with them. No excuses.”
3. Follow up with them frequently while at the same time avoiding micromanaging them. Ask them how it’s going. But if they face any obstacle, do not solve it for them; just encourage them and/or repeat your expectations that they will overcome it.

If you follow all three points above, the chances are that you will succeed. It won’t work all the time, not with all your employees, but it will work most of the time with most of them.

Keep in mind at all times the following:

Low agency is a learned reaction to a past experience that taught them that it’s not worth it to be high agency.

Your job is to make them undergo experiences that teach them the opposite.

More on this

I recently recorded a video on this topic.

Watch video on YouTube

Apart from the fact that, as Mark Baker noted, electric toasters are used even less.

The unspoken issue here is that if you ask a driver whether their car is inefficient, they won’t say “yes, because it’s parked 92% of the time.” They will say, “Of course it’s efficient, in fact, it’s the most time-efficient way to get to work, and it’s so efficient (and safe/comfortable) compared to alternatives that I’m willing to pay an outrageous amount of money on it on top of what public transport would cost me.”

This is not a defense of cars but rather an invitation to consider that the bottleneck to change is probably in understanding and addressing the reason people are so willing to use and even pay a premium for something so “inefficient.”

And, critically, forcing alternatives that people wouldn’t choose even if they look more efficient is probably a sign that these alternatives are in fact rather inefficient in at least a very significant way.

The objective should be to find a way to offer alternatives that don’t require subsidies or coercion to be chosen – that’s when we will truly have something more efficient.

Leaders who think organizational culture is a set of concepts attempt to change it using words and concepts – and inevitably fail, because organizational culture is not a set of concepts.
It’s a track record.
In particular, it’s the track record of which behaviors are a waste of time and which lead to good personal outcomes.
For example, what happens when someone raises a hand – do they get listened to, or do they learn that raising a hand is a wasted effort?
In other words, what’s the track record of what happens when someone raises a hand? That’s what determines whether raising hands is part of the team’s culture.

<Principle
text={[
"Culture is the track record. You change a culture not with words or concepts but by changing the track record.",
]}
/>

Defining Core Values and communicating them doesn’t change cultures.
It’s not a useless exercise but merely a first step. After Core Values are defined, track records must be changed.
This cannot be achieved through words, only actions.
Or, more precisely, words can initiate and facilitate the process, but only words backed by action count.

Engagement is also a track record

It is the track record of what happens when one cares.
What happens when someone works hard? When someone points out a problem? When someone comes up with an idea? Does it lead to good or bad outcomes?
What’s the track record of caring? Does it lead to good personal outcomes? Or does it lead to wasted effort?
If you want your people to be more engaged, change the track record of caring.
Make sure that the next time someone cares, good things happen to them. Or at least they aren’t taught the lesson that it would have been better to care less.

Teamwork is a track record

Similarly, and contrary to common belief, teamwork is not about liking or trusting your colleagues.
Instead, teamwork is the track record of what happens when colleagues interact.
What happens when someone asks a colleague for help? Does what follows teach them that it was a good idea to ask for help? Or that asking for help is a waste of time?
What happens when someone gives feedback to a colleague? Are they listened to and thanked? Or are they made wish that they hadn’t voiced their feedback?
Again, to improve teamwork, improve the track record of interactions.

Improving the track record

Let’s work on this last point. How do you improve the track record of interactions?
The trick is to not address all interactions at once – such a generic goal will produce a generic approach that won’t be effective. Instead, begin by picking one type of interaction and working on that.
For example, let’s work with the interaction of “asking and receiving feedback.”
People won’t ask for feedback unless, in your team, there is a track record that, when people ask for feedback, they receive helpful and actionable feedback that doesn’t feel personal. And people won’t give good feedback unless the track record in your team is that, when people give feedback, it is well received and taken seriously.
So, if you want your people to give more feedback to each other, you need to create these two track records.

Leading by example

Achieving this requires, first and foremost, that your personal actions contribute to the new track record. Whenever you give feedback, make sure it’s not just correct but also helpful, and that makes the receiver glad to have you as a manager rather than wishing you didn’t exist. And whenever you receive feedback, make sure you take it seriously. This doesn’t mean accepting all feedback as correct – some will be wrong – but always making your interlocutor feel listened to, and if you disagree, let them know why. Never take any feedback you receive personally, and never make any colleague giving you feedback feel like they wasted their time.
The more your actions show that in your team there is a good track record associated with giving feedback, the more people will give and request feedback.

Teach skills

However, leading by example is necessary but not sufficient. Not only must your people be open to giving and receiving feedback, but they must also have the skills to do it in a helpful way that makes their interlocutor want to have more such interactions in the future. This requires you to train and coach them on how to give and receive feedback.
Note that doing “politically correct” things, such as forcing people to say thank you even when they receive bad feedback, won’t work. Instead, what will work is to teach your people to give such helpful feedback that saying “thank you” is a natural reaction.

Conclusions

So, to summarize what we’ve seen so far.
Organizational culture – what your team does, what your team cares about, what your team doesn’t do – is not a bunch of words but a track record of actions and reactions.
So, changing your organizational culture means changing the track record.
Find out the behaviors you want your team to exhibit, and ensure that there’s a track record of good things happening to those who exhibit them.

Here is how I did it and the principles I followed.

My first 1,000 followers

Building a following from scratch is hard because no one sees the content you post.

Therefore, it’s critical to leverage the platform-specific features that get you seen when you don’t have followers.

For Twitter, it’s replies. You build your first 1,000 followers by writing value-adding replies to users with a wide following. For Instagram, it’s hashtags. For YouTube, search relevance. Each platform has its own feature to leverage, and some work better than others. But what’s critical is that writing great content isn’t sufficient when you don’t have followers – you must get it in front of eyeballs too, and simply posting to your feed is not enough.

In fact, a common mistake of novice creators is to focus on creating content for their existing following before they have enough followers for it to be a sufficient growth engine. Until then, your focus should be on acquiring new followers by posting not on your feed but where these potential followers are.

Twitter is a particularly good choice to build a network from scratch because users can easily retweet replies – whereas in other social media, users cannot share them or are unlikely to do so.

From 1,000 to 5,000

If replies were the dominant way I gained followers from 0 to 1k, retweets were how I got from 1,000 to 5,000. Post great content, and your followers will show it to theirs.

This is where Twitter really shines. Retweets are so frictionless and central to the user experience that going viral is easy. Other platforms have repost features too, but they are less frequently used.

How do you write great content? A great way is to answer the most difficult questions your audience has. Why the difficult ones? Because they are the ones that wow people into following and recommending you.

From 5,000 to 10,000

The growth from 5k to 10k followers happened in just a couple of weeks in February 2020, thanks to a few tweets I wrote about the pandemic as a risk management expert.

Writing about current events is a good way to gain followers, but beware of how you do it. Simply covering the facts like any news outlet would make you a commodity – you will gain followers, but for the wrong reason, and they won’t be relevant to you. They will grow your follower number but won’t retweet your tweets (unless on the specific topic you wrote about when they followed you) and won’t become your customers.

Instead, if you do write about current events, do it from your angle of expertise and only write about events to which your expertise is relevant. You will gain fewer followers, but they will be valuable ones, and you won’t alienate your current ones with irrelevant content.

From 10,000 to 20,000

After my first 10k followers, the dominant way I gained followers was through shows. An account with a large following would invite me to a conference or podcast and share the recording. Each time it happened, I would gain hundreds of followers overnight.

I am particularly proud of never having asked any host to get invited to their show. Instead, I published tons of expert content that demonstrated I was someone worth inviting. However, if there’s something I would have done differently, it would be to have been more proactive in contacting podcast hosts and conference organizers to get more invites.

That said, I wouldn’t have been invited on shows without a track record of publishing great content. For me, it was a mix of books and tweets. For you, it can also include videos and articles. But publish first and use that to get invites – the other way around won’t work unless you’re already a celebrity.

Beyond 20,000

As I keep growing my follower count beyond 20k, I try to observe the following principles:

• C users follow B users, and A users follow A users. Writing beginner tips, news, and lists (“The top 10…”) will appeal to a large audience but not to extraordinary people. To get followed by exceptional people, produce content that they would find valuable, such as advanced tips and expert commentary. Since extraordinary people are extraordinarily busy, conciseness is a must.

• Reward attention, don’t waste it. My followers’ attention is my most precious asset. I shouldn’t waste it by posting something low-quality, reposting old content too often, or sharing promotions too frequently.

• Do not follow a fixed schedule. Writing a daily post or weekly newsletter might force you to post sub-par content just to “fill the slot.” Don’t. Only post when you have something valuable to say.

• Build trust, don’t destroy it. Don’t exaggerate claims. Don’t follow fads. Don’t compromise your principles. Be the immovable rock people can trust when the sea around it is in turmoil.

• Do not imitate accounts that don’t follow the four points above. They might be faster to build a large following, but it’s going to be made of low-quality accounts. It won’t contain paying customers or large accounts that can put your content in front of the eyes of thousands.

• Write content for the top nodes of your network. A retweet from someone with 100k followers will get you more visibility than 100 likes from accounts with 100 followers. Ask yourself, “What kind of content would the top nodes in my network share with their followers?” Then, produce that.

• Write clearly but don’t dumb it down. People value great communicators, but – unless you’re the world’s #1 communicator, you don’t want to compete on simplicity but usefulness; otherwise, you’ll lose to someone else.

• Do not become a commodity. It’s easy to copy someone else’s style or content, but precisely because it’s easy, it puts you at risk of being copied. Even worse, it makes you a commodity, forcing you to compete on aspects you don’t want to compete in, such as who’s cheaper or who works the hardest. Instead, compete on expertise. Answer better questions. Answer more difficult questions. Provide more solid answers. Be more reliable. More trustworthy. More sincere. You will attract more valuable followers.

• Never measure yourself against people playing a different game. If you position yourself as the expert, do not measure yourself against people positioning themselves as the beginner’s help – if you do, you will stop writing expert content. Similarly, if you look for customers, do not measure yourself against people looking for likes – if you do, you will get more likes but fewer customers. And finally, if you’re here for the long term, do not measure yourself against people here for the short term – if you do, you will take actions that destroy long-term trust in search of a quick boost.

My mailing list

In addition to my Twitter network, I also have a mailing list.

I suggest you do the same, for two reasons. First, social media platforms and users come and go, whereas emails stay. Second, emails are personal and guaranteed to get on your readers’ reading list. (Whether they read it depends on whether your previous emails were worth reading.)

When writing to my subscribers, I follow the nine principles above. In particular, I always ask myself the following question when writing an email: “Is this email going to make my reader more or less likely to open my future emails?” For this reason, I rarely write promotional emails. If I have to tell my readers about a new product or promotion, I write it at the bottom of an email with value-adding content (not just commodity content).

I milk my current subscribers less but retain them more and – crucially – increase the chances that they recommend my newsletter to their friends and colleagues (no one recommends something too salesy).

Conclusions

To build a following from scratch, identify your network’s largest nodes, write content they would share, and get it in front of them. Differentiate yourself on reliability and expertise. Build trust more than you trade it in.

Note: you might also be interested in this interview where Wenlin Tan asks me about how I use Twitter and my advice for others looking to build an inspiring virtual network of interesting people.

Note #2: you might also be interested in my book Winning Long-Term Games, where I discuss how to grow long-term assets such as relationships and a social media following.

During the first years, skill and a decent work ethic are enough to get ahead. This lures many into believing they have an easy shot at winning.

However, as the race progresses, competition becomes fiercer. Skill and a decent work ethic aren’t enough anymore. Keeping up requires an unreasonable work ethic, and getting ahead demands reckless risk-taking.

Participants with a narrow vision for success let their eagerness to win set their boundaries. As a result, they often find themselves with miserable lives – either because they sacrificed too much or took too much risk that turned out poorly.

Conversely, participants with a broad vision for success are more eager to have a full life than to win any race to the bottom. As a result, they set ambitious objectives for all important parts of their life. Then, they use these objectives to set their boundaries – what they aren’t willing to risk and sacrifice. And finally, they use these boundaries to decide how to compete in races to the bottom and to what point.

These are the real winners – not in the sense that they get #1 (it happens rarely) but in the sense that they get out of the race more than they risk and sacrifice. They choose the conditions at which to compete and therefore end up with a good bargain.

People who achieve mastery do two things differently: they practice more, and they adjust their practice more frequently. During each session, not only do they work to improve their skills but also to improve their practice.

Metapractice – the ability to tweak one’s practice to maximize its effectiveness – is the most underrated skill of them all. After all, if one is bad at metapractice, he will have trouble learning any other skill.

Do not just practice your skill – practice your practice.

Examples include:

• Asking for feedback and then deflecting critiques.
• Asking to focus on quality but also speed and cost.
• Asking to prioritize a critical task but not following up.

In all examples above, employees receive mixed signals. Does my manager really want me to say what I think? Is quality really the priority? Is the task really critical?

"When you give your brain mixed messages, you’re going to get mixed results." – Tony Robbins

This principle surely applies to individuals. For example, those with mixed feelings about money have trouble taking decisive action to improve their income.

But this principle also applies to business. Managers who give their teams mixed messages get mixed results. When they ask for feedback, they should demonstrate that they really want to hear what their team has to say. When they assign a priority, they should explicitly address that everything else is less important. And when they assign a task saying it’s important, they should follow up as if it were.

Mixed signals are the #1 reason change initiatives fail

Whenever a manager introduces a new process, their team have a question at the back of their mind: "Is this going to stay? Or will it be abandoned after a few weeks?"

To answer this question, employees look at their manager's behavior. Is the manager following up on the new process and acting as if it were important? Or is the manager acting as if they didn't care?

Unless the manager acts as if the new process were important, the team will not act as if it were important.

Hence, it is critical that managers send clear signals that the new processes are important and there to stay. Otherwise, they migth as well not try and not waste anyone's time.

1. **The next time you delegate a task, ask yourself if you are giving mixed signals.** If you are, ask yourself how you would delegate that task if your life depended on it, and then do at least 80% of it.
2. **The next time you ask something out of your team, ask yourself if they might be receiving mixed signals** – from you, from other managers, from other colleagues, and from eventual beliefs of theirs. If it’s the case, consider discussing these mixed signals. After all, increasing clarity is one of the highest-leverage activities managers can spend their time on.

1. You didn’t demonstrate a track record of being helpful. Perhaps, your past feedback created more problems than it solved. Or perhaps, your team doesn’t have reasons to trust you know their job. Or maybe, you have a history of self-centeredness. Either way, unless you have a track record of being helpful, your people will be reluctant to listen to your feedback.

2. Your feedback isn’t helpful, or doesn’t feel like it’s helpful. Perhaps, it points out a problem your interlocutor already knew they had but didn’t know how to solve. Or perhaps, your feedback is too abstract and generic and doesn’t provide a clear step forward. Or maybe, you criticized your interlocutor instead than a specific behavior or part of their work. Either way, you’re not perceived as adding value.

If you want your feedback to be listened to, learn to give feedback that feels helpful, and get a track record of giving more helpful feedback than unhelpful one (as determined by its recipient).

I first learned about the Lindy Effect, also called Lindy’s Law, in Taleb’s book “Antifragile.”

Some examples of what is Lindy and what isn’t

Before discussing how managers can use it, let’s see a few examples of what is Lindy and what isn’t.

• The non-perishable (e.g., ideas, technologies, recipes) are Lindy. The longer a song has been on the radio, the longer we can expect it to remain on the radio.
• The perishable, such as food and people, aren’t Lindy: the older they are, the sooner they are expected to perish. After all, a 90-year-old is expected to die sooner than a 40-year-old despite a higher conditional life expectancy.
• Groups of people and animals, such as cults and species, do are Lindy. The longer a species has been around, the longer we expect it to still be around.
• Jobs are Lindy. The longer a job has existed, the longer we can expect it to still be around. (If you disagree bringing the counterexample of farmers, consider that farmers are still around.)
• Careers are partially Lindy. The longer someone has been in politics, the more we can expect them to be in politics until they retire.

The latter example gives us an insight into the two mechanics that explain the Lindy Effect.

The rationale for the Lindy Effect

There are two mechanics underlying life expectancy.

On the one hand, life expectancy is inversely proportional to hazard rate: the lower one’s likelihood of dying in any given year, the longer their life expectancy. We can turn this around to say that the longer something has been around, the lower its hazard rate must have been, and therefore the longer it is expected not to perish.

On the other hand, some entities (the living) have a bound to their life expectancy. People seldom live above 90 years old, and the closer they get to this bound, the more their hazard rate increases.

These two mechanics sum up into a general theory of life expectancy:

The longer something has been around, the longer it is expected to be around, and the closer it gets to its natural bound of life expectancy (if any), the earlier it is expected to perish.

How can managers use the Lindy Effect?

Here are a few principles we can derive from Lindy’s Law that can be useful to managers:

The longer a problem has been around, the longer it is expected to be around in the future. Address it now once and for all.

To estimate the life expectancy of one of your products (or one of your competitors’), consider how long it’s been around and how long the assumptions upon which it survives (habits, technologies) have been around.

The more areas someone has exhibited competency in, the higher the chances they will demonstrate competency in a new area.

What other examples of the Lindy Effect can you spot in your job?

This heuristic is called “Wittgenstein’s Ruler.” I like to formulate it more
precisely as follows:

The more free parameters, the less you know what is being measured.

Some examples of Wittgenstein’s Ruler

• When prizes (such as a Nobel) are awarded too often to a non-deserving candidate, awards tell us more about the awarding committee than about the winner.

• Feedback sometimes tells us more about the person giving it than about its object.

• When a ranking based on objective metrics is published, the choice of the metrics used sometimes tells us more about the committee choosing them than about what the ranking is supposed to evaluate.

How does Wittgenstein’s Ruler apply to businesses?

Here are a few examples:

• When you survey your customers, make sure that you choose the questions well so that the results will give you information about your customer’s preferences for your product and not about your own preference for survey questions.

• When you ask for feedback, use very specific questions and have a track record of responding well to feedback. Otherwise, the feedback you receive won’t be about what it’s supposed to describe but about your relationship with the feedback provider and your mutual expectations.

• When you choose which business metrics to measure, make sure you pick metrics that describe well what’s going on and don’t instead measure the amount of “gaming” your people do to achieve them or the measurements that you’re comfortably making.

Personally, I believe that in many cases, it’s impossible to avoid Wittgenstein’s Ruler effect entirely. Instead, it is possible to mitigate it by increasing direct qualitative observation. For example, if now and then you go to your teams’ workstations and observe how they work and how metrics are collected, you might get a better overview of what’s really going on in your business than any metric might tell you.

I’m not saying that metrics are bad. They’re good.

Instead, I’m saying that metrics cannot be relied upon and must always be coupled with direct qualitative observations.

Here, I introduce the concept of ergodicity as a non-binary property and suggest a few real-world applications.

Watch video on YouTube

The purpose of studying ergodicity

Ergodicity is one of the most important concepts in economics. If you are unfamiliar with the term, I suggest my book on the topic.

If, instead, you are familiar with the term, you might have wondered how it applies to everyday life. In particular, you might have wondered, which activities in life are ergodic and which are non-ergodic?

The answer is simple. Almost everything in real life is non-ergodic. The fully ergodic mostly lives only in theory and simulations.

What's the purpose of studying ergodicity, then, if nothing is ergodic?

The answer is that, while everything is non-ergodic, something is more non-ergodic than others - and questions such as "what alternative is less non-ergodic" or "how can we make this activity less non-ergodic" matter.

I recently published a paper on ergodicity as a non-binary property, where I examine these questions. You will learn how to interpret ergodicity as a spectrum and how to apply it to real-life conditions.

The impact of better email writing

If your team is excessively polite and formal in their internal emails, wasting twenty seconds to add a few unnecessary lines, and they send twenty emails a day, addressing this would save three workdays a year. (20 emails a day times 20 seconds equals 6.67 minutes a day, multiplied by 220 working days equals 24.45 hours, which is about three 8-hour working days).

If your team sends external emails, how much would a 10% higher closing rate mean to you?

If your team’s poor communication causes unnecessary back-and-forths, how much would cutting these by 10% mean to you?

Coaching your team to write better emails is a high-leverage activity and should be high on your to-do list.

Refute the pervasive assumption that people know how to write emails. Most people have never been trained and would benefit from some coaching.

Let’s see how you can do it, and let’s begin with what you shouldn’t do.

What not to do

• Don’t enroll your people in a course on writing better emails. Most of the advice contained there would be too generic for the specific emails your team sends.

• Don’t ask HR to train your people, for the same reason as above, with the exception of an HR person who knows extremely well the context your team works in (it’s rarer than commonly believed).

• Don’t hire an external coach, again, unless they specialize in your specific industry and have extensive knowledge of the kind of work your team does.

• Don’t run a one-way training, where you speak and your team listens. You might give your people the perfect checklist to follow (assuming it exists), yet they might not follow it or follow it sub-optimally.

Don’t make it formal. Depending on the context and personalities involved, announcing a formal session might produce feelings of inadequacy, skepticism, annoyance, anxiety, or other negative emotions.

Instead, here is what to do.

Coach your people

Here is how I used to coach my people to write better emails.

First, I would observe. I wouldn’t proactively take action but wait for an email with ample margins of improvement to enter my inbox.

Then, during my next one-on-one with one of the people on my team, I would mention the email, saying I noticed it could have been written, e.g., more clearly.

I would be very specific, pointing out what exactly was unclear. If more than one thing were unclear, I would focus on the more important one – mentioning more than one problem might feel overwhelming.

I would avoid being arrogant or confrontational. One great way to achieve this is to frame it as “I used to make the same mistake, then my former manager explained this to me, and now I write more clearly, and that helped my career.” Notice how it helps to explain not just why clearer emails are beneficial to the organization but also to them.

Once the problem is clear, it’s time to help them improve.

If this is the first time we’re having this conversation, I might simply ask them to “write more concisely” or whatever behavior I want them to correct. Then, I would keep an eye on their following emails to see whether they implemented the advice – and if they did, I would be quick to praise them to reinforce the behavior.

If, instead, this isn’t the first time we’re having this conversation, I would have to dig deeper.

First, I would explain what adverbs mean in practice. Everyone knows they should write more clearly (“clearly” is the adverb). Fewer know what it means to write clearly or how to do it. It’s your job to explain this.

Personally, I do one of the following three exercises.

1. If conciseness is the problem, I tell them that the email should have been half the length. Then, I put a printed copy of their email in front of them and ask them to strike out the unnecessary parts. Finally, I validate their efforts, telling them that what’s left now is clearer. This last step is critical, for lack of conciseness often derives from a belief that unnecessary details help.

2. If clarity is the problem, I tell them it’s unclear what the request or takeaway from the email is. Then, I ask them to tell me what the point of the email is. Once they tell me, I say they should have written exactly that either at the beginning or end of the email.

3. If beating around the bush is the problem (common in status updates that try to hide a problem between paragraphs of positives), I ask them to write down up to three bullet points with the most important things they want the reader to know. Then, I tell them their email could have been those three bullet points.

Of course, feel free to adapt these exercises to your needs and the specific problem you want to correct.

That said, here are a few principles you should follow:

• Be specific. Don’t just say what they should do. If they don’t know how to do it, also explain how to do it.

• Be concrete. Talk in terms of actions. Use specific examples. Show them a bad email and explain why it’s bad. Show them a good email and explain why it’s good. Notice how this very article is specific and concrete; otherwise, it would be useless.

• Never criticize the person. Never say, “You’re unclear.” Instead, say, “This paragraph is unclear.”

• Validate their improvements. People often communicate the way they do because they believe it’s the most advantageous way. For example, people who struggle to be concise often believe that details are necessary. In this case, just telling them to be more concise won’t work. You must get them to write something more concisely and then validate that what they write is clearer, thanks to the absence of details.

• Keep validating their improvements every now and then. You should catch them right and let them know you noticed relatively frequently, at least during the first few days or weeks. Failure to do so might cause them to believe that you don’t care or that their efforts are going to waste.

• Get them to commit to adopting the new behavior in the future. The best way to do this is to ask, “Do you feel ready to apply this to future emails,” or, even better, “Is there any reason why you wouldn’t apply this to future emails?”

Conclusion

Coaching your people to write better emails is a high-leverage activity: with 15 minutes of your time, you can save them workdays writing unnecessary words, decrease wasteful back-and-forths, and improve your teams’ persuasion if they deal with external clients.

The best way to improve your team’s email-writing skills is to coach them individually.

Focus on a single area of improvement, be very specific about why it’s a problem and how they could improve it, give them actionable next steps, and validate their improvements.

If you are clear enough to be understandable but not so clear that you cannot be misunderstood, your subordinates might misunderstand you. If it happens and the misunderstanding isn’t clarified immediately, it will lead to blame and resentment. Hence the need to be super-clear: not just enough so that you can be understood but clear enough so that you cannot be misunderstood.

Why aren’t managers superclear?

It is often a deliberate choice. For example, some managers believe being superclear would insult their interlocutor’s intelligence. While this might be true, it’s also true that any misunderstanding from not being superclear will damage their subordinates’ trust and respect – and the latter effect is stronger.

Other managers aren’t superclear because they believe they must leave space for their subordinates to be creative in coming up with a solution. But it is possible to be superclear about an objective and yet leave space for how to achieve it. Conversely, being unclear about what you want them to do might lead to paralysis or playing it excessively safe.

And finally, some managers aren’t clear because they do not know what they want, at least not concretely.

How to become superclear

The theory is easy: aim to be so clear that you cannot be misunderstood – and, to avoid micromanaging – focus on the outcome you need, not on how to achieve it.

The practice is harder. I have three actions that help achieve superclarity.

1. Be concrete and make examples. Don’t just mention abstract concepts, such as “be ethical.” Talk in terms of actions. Explain what it means to be ethical. What does an ethical person do? And an unethical one?
2. Ask yourself, “Let’s imagine that after I finish speaking, my interlocutor has a different understanding than me. What might they have missed or misunderstood?” Then, of course, proactively add information that will pre-empt the misunderstanding.
3. Ask your interlocutor to rephrase what you asked them. This will help catch omissions and misunderstandings. Asking to rephrase isn’t an insult to your interlocutor’s intelligence – after all, rephrasing and repetition are performed mainly by high-stakes and highly-professional specialists such as surgeons and airline pilots. That said, if you feel uncomfortable asking to rephrase, you can instead ask, “what do you plan to do?” and then notice if their answer is aligned with the outcome you want them to achieve.

Conclusion

As a manager, you are responsible not only for communicating values and objectives but also for your people understanding them and, crucially, for your people not misunderstanding them.

This requires embracing high levels of communication standards. Be clear and concrete. Don’t aim to be so clear that you can be understood. Instead, aim to be so clear that you cannot be misunderstood.

Be superclear.

The real issue is simpler: our minds naturally favor what I call "first-order thinking" – looking at things exactly as we experience them right now, without considering how they might change over time.

Think about your first day at the gym. Your muscles ache, you're exhausted, and you don't see any immediate results. First-order thinking tells you: "This is terrible. Why would I ever do this again?" But wiser, "second-order thinking" recognizes that these initial costs will decrease while the benefits will grow. Your body will adapt, exercises will become easier, and you'll start seeing real improvements.

This difference between first- and second-order thinking is crucial. First-order thinking assumes the future will be just like the present – that today's costs and benefits will stay the same forever. Second-order thinking understands that things change over time, often in ways that completely transform the original equation.

Why are we stuck in first-order thinking? It's actually built into our biology. Our brains evolved to be intuitive rather than analytical. While humans can think analytically better than any other species, it takes real effort. It's mentally taxing and requires sustained focus – something our brains naturally resist.

This creates a trap: First-order thinking tells us something isn't worth the effort. Because we believe this, we don't bother analyzing it more deeply. Without deeper analysis, we never discover the long-term benefits. And without experiencing these benefits, our first-order thinking never changes. It's a perfect circle that keeps us stuck.

This same pattern explains why we tend to focus on negative experiences. We use our immediate reactions as a proxy for future value, forgetting that this relationship often changes dramatically over time. Just as muscles need stress to grow stronger, many valuable things in life require pushing through initial discomfort to reach lasting benefits.

Understanding this pattern gives us a powerful tool: when you notice yourself dismissing something based on immediate results, pause and consider how the situation might evolve over time. Sometimes the best opportunities are hidden behind challenging beginnings. Of course, the doing the above won't be sufficient to help you change behavior; but it will help to know that our instincts are not reliable in contexts dominated by second-order effects and, therefore, we should consider acting even if our first-order emotions tell us otherwise.

A recent comment by Nassim Taleb made me reflect on extreme performers and what we can learn from them:

"Elon Musk illustrates my point: solid financial success is largely the result of skills, hard work, and wisdom. But wild success (in the far tail) is more likely to be the result of reckless betting, extreme luck, and the opposite of wisdom: folly." – Nassim Nicholas Taleb

First of all, let me clarify that I agree both with Taleb (most of Musk’s wealth is due to luck) and with Musk’s fans (Musk is very skilled).

In fact, the two are not at odds: Musk is probably both very skilled and very lucky. Skill is sufficient for becoming wealthy, but given that one is wealthy, how wealthy depends a lot on luck. It’s easy to imagine that in many parallel universes, Musk is also a very successful billionaire, but with how many billions? One, twenty, a hundred? It would still be less than half of his wealth in the current universe. The difference, which makes up for much of his present fortune, must be due to luck.

Similarly, skill is sufficient for becoming rich, but becoming the richest man on Earth also requires a lot of luck. Let me justify this statement with a thought experiment. Imagine taking a thousand entrepreneurs, all with the same starting conditions (cash, connections, etc.) and only differing in skill. Then, let’s observe how their wealth evolves in a few decades. As expected, we would notice that, in general, the more skilled a person, the wealthier they became. And yet, if you took the wealthiest one amongst them, the chances that he is also the most skilled one are slim. It’s more likely that the richest person is almost as skilled as the most skilled one but considerably luckier.

My point is not about whether Musk deserves his wealth – I couldn’t care less. Instead, my point is about reproducibility. We often wish to imitate the person with the highest score assuming they are also the most skilled, whereas the most skilled person is more likely to be found among those with a high-but-not-highest score.

Note that I wrote “more likely.” There may be someone so skilled that he ends up with the highest score. But he must be that much more skilled than everyone else. Otherwise, the chances are that one of the “great-but-not-best” participants will get enough luckier than the best one to overcome the difference in skill.

That said, my point is not “don’t imitate the best one” or “imitate the second-best one.” Instead, it’s “be critical about whose strategies you aim to imitate and why.”

Ask yourself, how reproducible is that strategy? In ten parallel universes, in how many do they end up as successful as in this one, and in how many do they end up bankrupt or in jail? Are you okay with not only the outcome in the current universe but also with the full range of outcomes across universes?

Moreover, consider another point Taleb made. “You get to the tail by increasing the variance (or the scale) rather than raising the expectation.” In other words, to get extreme outcomes, you must reduce average outcomes. Do you really want to be the one with the highest score? It will come at a cost. Not just effort and opportunity costs but also risk – risk that will increase the best outcome but decrease the average outcome.

Let me explain this last point with another thought experiment. Again, let’s take a thousand entrepreneurs, all with the same starting conditions (money, connections, etc.) and only differing in skill. Five hundred of them take extreme risks, whereas the other five hundred only take small risks. Let’s observe what would happen after a few years in ten parallel universes. We would notice that, in all universes, the wealthiest entrepreneur would come from the risk-taking group. However, and this is the key point, in each of the ten universes, it would be a different person! Each of these ten people would have extreme success when lucky and terrible outcomes when unlucky. In contrast, a skilled person who only takes moderate risks would have great-though-not-extreme outcomes in almost all parallel universes.

If you don’t take extreme risks, even if you’re the most skilled person, you will be outperformed by someone who did. And if you take extreme risks, you will have worse average outcomes than if you didn’t (competing for the first place often means using strategies that reduce your average outcome).

Let me clarify a couple of things. First, this doesn’t mean that you shouldn’t take risks – here, we’re talking about extreme risks, bets that damage you irreparably when they go wrong. In general, taking small risks is a good strategy.

Similarly, this doesn’t mean that you shouldn’t take extreme risks. Instead, it means acknowledging that competing for the first place often means using strategies that reduce your average outcome. Then, the choice of whether to aim for the first place is yours.

And if you really want to become the best, I suggest restricting the scope of “the best at what.” For example, aiming to become the best singer in your town rather than the best artist in your country. Not only does a smaller number of competitors make it easier to win, but it also increases the chances that the winner is the most skilled rather than the luckiest one – in other words, it increases the possibility that a reproducible strategy can lead to victory (because there are fewer chances that someone gets so lucky to overcome the difference in skill with the most skilled person). This is advantageous because it means you can have a strategy that lets you win and has relatively high outcomes even if you’re unlucky.

An addition, as of November 2022: the FTX crash and it’s CEO’s Sam Bankman-Fried (SBF) quick rise-and-crash from little to billions to nothing is another example of the principles described in this article. If you take extreme risks, you will have worse average outcomes than if you didn’t. As Nassim Taleb noted, “SBF got temporarily rich because he is both aggressive and clueless about finance.”

And the fact that SBF overshadowed other more honest and conservative crypto exchange owners is another example of the principle, “if you don’t take extreme risks, even if you’re the most skilled person, you will be outperformed by someone who did.”

Nowadays, after having worked with many managers that repeatedly fought inertia and achieved long-lasting results, I changed my mind.

Fighting inertia mostly consists in overcoming three key obstacles:

1. The doubt that efforts will go to waste. Most employees have witnessed change initiatives that created much disruption but didn’t achieve any concrete improvement. They must be convinced that this time it’s different, and words won’t cut it.
2. The lack of closeness. People won’t change their ways just because their CEO asked them in a corporate-wide email. They need to see that their direct supervisor is actively committed too.
3. Contradictions. People won’t change their ways if they see others still being allowed to behave the old way. This includes the manager being inconsistent with his actions and standards.
   Here, I give you three catalyzers for change that overcome these obstacles and allow managers to create long-lasting change within their organizations.

The first catalyzer

Have you ever wondered why most toothpaste brands have a strong mint flavor?

Rory Sutherland pointed out in his book "Alchemy" that the mint flavor does nothing towards killing bacteria but does everything towards keeping you hooked on brushing teeth. Imagine if there weren’t any mint flavor. You would brush your teeth once, feel no particular change, think that your efforts went to waste, and quit the idea of brushing teeth after every meal. It’s not worth it. Conversely, if you brush your teeth once and your mouth feels fresher thanks to the mint flavor, you’re more likely to trust that brushing teeth is an effective and beneficial habit. You’d keep brushing your teeth because every day, you get immediate feedback that your efforts are not going to waste.

The same applies to organizations. People require early feedback that their efforts aren’t going to waste. As long as they get it, they stay motivated. And as soon as they don’t get it anymore, they lose motivation and disengage.

For example, if you ask your people to follow a new procedure at work, and they do it, but feel no difference, no better outcome, they will learn the lesson that their efforts are going to waste. The rational decision is to disengage and abandon doing the new thing.

Conversely, if the procedure has some kind of early feedback (like the “mint” in the toothpaste) showing that efforts are not going to waste, then people will be more willing and motivated to use the procedure and will be more engaged in general. This is the first of three catalyzers for change: give early feedback that efforts are not going to waste.

One way to implement the first catalyzer

There are three common ways to give early feedback that efforts are not going to waste. The first one is to catch your people doing something good and thank them for it. For example, if you ask your people to follow a new procedure, then spend some time at their workplace, and when you see them do the new procedure, thank them for it. It will give them a clue that their efforts are noticed and matter.

"Management hack: thank people for doing things that are a normal part of their job." – Mark Brooks

A common mistake

When I advise my clients to do the above, a common mistake is waiting too long. If you ask your people to follow a new procedure on Monday, you should already catch them doing something good on Monday. If you are waiting for Friday, by Tuesday, they will have learned the lesson that their efforts do not matter. Feedback must be early; ideally, immediate.

A second way to implement the first catalyzer

The second common way to give clues that efforts aren’t going to waste is to get positive customer feedback in front of those whose work caused it. If your product changed the life of a customer, everyone needs to know about it, from the janitor to the accountant – not just the product design team. Go get customer feedback, interview your best customers, and show the relevant bits to your employees who need to see it. And do it fast – before the doubt that efforts are going to waste creeps in.

A second common mistake

When I advise my clients to do the above, a common mistake is only getting feedback from customers. However, in a company, every employee is another employee’s customer. Everyone benefits from the janitor’s work, for example. And yet, how many give the janitor clues that his work is improving their lives? Get feedback from all departments, and show it to the workers who worked hard for them.

A third common mistake

Another common mistake is to make the above too mechanistically. For example, if you ask all your employees to make a video thanking someone else in the company, people might doubt these videos are sincere. Instead, hire a freelancer for a couple of days, give him a list of roles in your company, and ask him to find someone who benefits from each and record a 30-seconds video interviewing them. Then, distribute the videos as appropriate. Similarly, such videos shouldn’t be too sweet: just explaining why people’s work matters is sufficient. People don’t need to feel loved at their workplace, but they need to feel like their efforts aren’t going to waste. Aiming for the former will lead to a lot of insincerity and other counterproductive outcomes. Aiming for the latter is easier and more effective.

Of course, the above won’t work for all companies. But for many, it could be a turning point in the engagement of their workers.

A fourth common mistake

Some managers understand the need to give people early feedback that their efforts are not going to waste. However, they immediately start thinking about ways to provide it in a scalable way – for example, a dashboard or a monthly report. Don’t. People need personal and early feedback, whereas scalable feedback tends to be impersonal (the dashboard) or late (the monthly report).

Or, better said: you can also use dashboards and reports, but they should always be complements to personal and early feedback, not substitutes.

Summarizing the first catalyzer to change

Just like toothpaste uses the mint flavor to provide early feedback that our efforts to brush teeth aren’t going to waste, workers need early feedback that their efforts are not going to waste; otherwise, they will disengage.

Managers should constantly ask themselves, “am I providing the mint flavor?” – or, more precisely, “are my people getting early feedback that their efforts aren’t going to waste?”

It is the manager’s job to constantly provide early feedback and, where appropriate, collect personal and meaningful feedback from customers or other departments and show it to their people early enough.

Common mistakes include waiting for too long, only collecting external feedback, and making the feedback collection process too mechanical. Instead, strive for early, personal, and meaningful.

The second catalyzer

Have you ever wondered why our arteries divide into capillaries?

That’s because our blood cells can only exchange oxygen with tissue cells that are close by.

The same happens in organizations: people don’t change when asked by someone from afar. CEOs are the pumping heart of companies, but they require a capillary structure that can drive change from close by: middle management.

Yes, I know middle management gets a bad rep as an unproductive layer of the company. But that only applies to bad middle managers. Good ones are invaluable and indispensable to drive change.

Put yourself in the shoes of a line worker. You receive a corporate-wide email from the CEO saying that there is a new way of doing things. You don’t know the CEO, so you might not trust him: does he know what he’s doing? Does he have your best interests at heart? Or perhaps you trust him but do not trust that he knows how to do your job. Or you do not trust the full repercussions of the change he proposed. Long story short, workers are rationally suspicious of any change coming from someone they do not have a close working relationship with.

Instead, a direct supervisor is uniquely positioned to explain the change to his team, listen to their questions, and answer them personally. And he can do so in a way that is impossible to reproduce at scale. Moreover, as we saw with the first catalyzer, change requires early feedback that efforts are not going to waste, and that can only be given by someone close enough and trusted – reports take too long, and dashboards are too impersonal.

Change requires trust, and trust doesn’t scale, hence the need to drive change through a capillary structure made of middle and lower management.

This doesn’t mean that communication from the top is useless; contrary, it is fundamental. It just means that it is not sufficient.

How to implement the second catalyzer

There are four steps to implement the principle of driving change through a capillary structure.

First, involve middle and lower management. Cascade down the goal of driving change through supervisors, explain the rationale and clarify that supervisors need their own supervisors to drive change. Hence the need for a capillary structure (CEO → middle management → supervisors → workers) rather than a flat one (CEO → supervisors → workers).

Second, train middle and lower management. You can’t expect that your managers know how to communicate change. Train them on what to communicate and how to communicate it. Train them to listen for questions and to answer them without dismissing them. Train them on giving early feedback that efforts aren’t going to waste.

Third, explicitly demand middle and lower management to be agents of change. Be clear, and use visual examples. Describe three managers: one doing its job of driving change, one doing too little, and one doing too much – this will clarify expectations better than anything else. Set high standards: communication doesn’t happen when you can be understood but when you cannot be misunderstood, and change happens not when it is communicated but when it is followed up with consistent action.

Fourth, sustain the change initiative. Constantly demonstrate the behaviors you’re demanding in others, and keep them accountable to the high standards you asked of them. The moment you stop is the moment doubt will arise that the change you requested yesterday isn’t relevant anymore (and therefore, any further effort would go to waste).

To summarize

Change requires trust, and trust doesn’t scale – hence, the need to drive change through a capillary structure made of middle and lower management. To achieve it, involve middle and lower management, train them, and explicitly expect them to be agents of change; then, constantly sustain the change initiative by taking action demonstrating that it is still a priority. Never allow fertile ground for doubts that efforts are going to waste.

The third catalyzer

Years ago, I consulted an operations manager with a warehouse problem. At all times, employees would leave mechanical parts and components scattered on the floor – a safety hazard and an efficiency drain. And yet, no matter how many times he repeated to always store the components properly on the shelves, his workers never did.

The root problem was that the manager was too busy and the warehouse too big for him to consistently enforce the standards he asked his employees to follow.

Therefore, we decided to restrict the area of change to a single point of the warehouse, small enough so that he could consistently provide feedback on it. He chose the area next to a safety exit. He held a stand-up meeting with the warehouse employees and told them that the area next to the exit had to be clear of components at all times. He asked them to clear it immediately, and he didn’t leave the warehouse until that was done.

Then, the hard part began. For the next month, he had to visit the warehouse multiple times a day and, first thing there, look at the floor next to that safety exit to see whether it was clear. If not, he should immediately stop whatever he was doing, walk to the nearest employee, remind him that the area had to be clear, and stay there until it was.

Here is what happened.

After a week, the warehouse employees learned that the safety exit area was to be left clear.

After two weeks, the employees began noticing that the area next to the machine was easier to walk in, and parts there were easier to find.

After three weeks, the magic happened. The employees began to clear the other areas of the floor of their own account.

You see, habits require consistency, but once they’re learned, they can easily be expanded to other areas. The bottleneck was the achievement of a critical mass of consistent repetitions of the desired habit within a few weeks. However, that requires time and effort from workers and their managers alike. They’re both busy and with limited bandwidth. The solution was to shrink the area of change from the whole warehouse to the few square meters next to the safety exit, an area small enough so that busy people could focus on it frequently enough for habits to engrain.

This is the third catalyzer for change: to avoid compromising consistency, compromise in the scope of change. Don’t attempt to change too many habits and too many people at once. Instead, focus on a single habit at a time, in a single team, in a single area of their work – and then obsess over it for the next three to four weeks.

By focusing change over a small area, obsessing over it, and letting others see the benefit of the change, you will achieve what you couldn’t before. This is the magic of obsessive consistency. Once the workers understand that they can change faster than their manager, they will. Once they understand that if they change, good things happen, they will. Good managers embrace the effectiveness of obsessive consistency, and so should you.

To summarize

Change requires consistency; to achieve consistency, reduce the scope of change so that you can obsess over it for a few weeks.

I get this question. Too much micromanagement is bad. However, not doing enough management for fear of micromanaging is also bad.

It is important to distinguish between the two. Here are three rules of thumb:

1. Feedback on methods (how you would have done the task) might be micromanagement.

2. Feedback on outcomes (“That’s below standard” or “You crossed this boundary”) is never micromanagement.

3. Clarifying what matters is never micromanagement.

Let’s go through each of these rules of thumb.

Feedback on methods

Comments on how you would have done the task might or might not be micromanagement, depending on whether your comments are helpful.

Here are some examples:

• If you comment just to say something, you’re not being helpful.

• If your comment adds work that doesn’t meaningfully improve the outcome, you’re not being helpful.

• If your comment takes a few minutes but could have been said in a few seconds, you’re not being helpful.

• Any comment such as “I would have done it this way, but it is okay if you do it that way” is a waste of time.

• If you highlight that they did something wrong instead of focusing on how to improve the outcome, you’re not being helpful.

• If your comment helps them see something they didn’t consider, you’re being helpful (but only if that something is important).

Feedback on outcomes

Feedback on outcomes is never micromanagement.

People need to know if they are doing something well or badly, and they need to know it very frequently.

There’s a reason many people hate their jobs but love playing video games: video games give them feedback on their performance very frequently, and their bosses don’t.

Feedback on what matters

Clarifying what matters is never micromanagement.

In fact, it is management. It’s a core part of what your job is about, and if you do not do it, you are not doing your job.

Summary

Do not let your fear of micromanaging keep you from adequately giving your subordinates the information, direction, and feedback they need to perform at their best.

Disclaimer: nothing here is professional advice or advice of any kind – take everything with a grain of salt and do what works for you in your situation, according to your values and objectives. This is just a map – you decide whether it fits where you are, where you want to go, and how fast.

Doing more of what got you here won’t get you there

A common scenario I’ve observed countless times. A young graduate, let’s call him Mark, gets an internship. Mark is good at Microsoft Excel. At the end of the internship, his boss hires him, specifically mentioning his Excel skills. Mark spends the next three years focusing on getting better and better at Excel. He makes the best spreadsheets in the company. And yet, no promotion comes.

The #1 reason people get stuck in life is that they keep doing what worked for them in the past, even if it’s not what’s required for their future.

Yes, being good with Excel might have been what got you the job, but it won’t be what will get you promoted.

To get a promotion, you must display that you have what it takes to do your next job well – not just your current one.

Similarly, there is this common misconception that once you get promoted, you can become more proactive. No. It’s being proactive that will make you promoted.

Don’t do chronic overtime

Occasional overtime is okay; needed, perhaps. Every now and then, there will be important milestones such as a product launch. You are expected to do what it takes to ensure that they are completed on time.

However, doing overtime every week is a signal that you can’t manage your current job. In other words, that you are not ready for the next one. Your boss might be afraid that if he promotes you and gives you more responsibilities, your reaction would be to work even longer – eventually dropping some balls or burning out. No thanks, better give the promotion to someone else.

Wait – what? Isn’t working overtime something that companies reward? No, not really. They’re glad if you work a lot, of course. But they won’t promote you just because of that.

Here is what I would do instead. If your office hours end at 5 pm, stop working on your current tasks at 5 pm. Then, if you want, keep staying at the office – but work on something that would make you better at the job above yours. For example, learn a relevant skill, spend time getting to know senior colleagues, or think about new business opportunities for your company. But don’t do more of what you’re already doing. It won’t bring you forward much.

Even better: if your office hours end at 5 pm, strive to finish your current tasks by 4 pm. Then, reserve the last hour for growth activities. This is hard to pull off at the beginning. However, this constraint will force you to delegate more and to drop the least important tasks, ultimately making you more effective. You’ll also be more likely to leave your workplace on time and have more time for yourself and your loved ones.

Your to-do list

On your first day, your boss probably took some time to walk you through a list of tasks you have been assigned. Never make the mistake of believing that these are all you should do.

If all you do is completing these tasks, career progression will be slow, if any. More importantly, getting better at them or working overtime on them is unlikely to bring you any tangible benefit.

Instead, you should consider the list of tasks assigned by your boss to you as a starting point. Over time, you should discover which of these tasks should be done well because they matter, which should be done at the bare minimum level just to “check them off” your to-do list, and most importantly, which important tasks are not on your to-do list but should be.

A good place to start is by asking yourself, what do your boss and your boss’ boss do that is not an exclusive prerogative of their role? For example, telling others what to do is a prerogative of their role, and you probably shouldn’t do that. But finding business opportunities and making processes more efficient are two tasks you might consider taking on.

Of course, do not break any boundaries. For example, come up with ideas of potential clients to contact, but do not contact them unless you have your boss’s approval. But the point is: you get to the next job by showing that you would be good at your next job, not just the current one.

Why you must discover by yourself what’s to be done

Let me clarify a common doubt. If there is anything you should do, your boss would have told you, right? Wrong. There might have been many reasons for which your boss might not have mentioned that. For example, he didn’t know about it, or he put it on his to-do list to let you know but always forgets, or he hinted at it but not explicitly enough for you to notice.

Alternatively, he might think that the task is someone else’s job. For example, he might think that finding new business opportunities is the salespeople’s job. Yes, it is, but that doesn’t matter that if you work in the back-office you cannot come up with good ideas for new opportunities. Nor it means that being able to recognize business opportunities isn’t a prerequisite for a promotion – especially if the next role is expected to be able to do so. I got myself into consulting from a back-office job by making suggestions no one asked me to make.

Two more reasons your boss might not tell you what’s important that you do is that he’s afraid that you might take his job or that he doesn’t think that you’d be up for the challenge. Neither is a reason good enough for you not to try.

Finally, there’s one last reason might not tell you everything that you need to do to get promoted. He knows that the role to which you aim to get promoted requires proactivity – and the best test to know whether you’d be a good fit is to see if you’re proactive enough to find out what you should do to get there.

It’s by being who you want to become that you get there.

Some good questions

Consider asking the following questions to your boss:

1. What, of what I’m doing, is not adding value (and I could stop doing)?

2. What am I doing wrong?

3. What are you expecting me to do that I’m not doing yet?

4. Anything I can do to help you?

Better to know the answers sooner than later.

Don’t worry about the risk of being given more stuff to do. First of all, questions #1 and #2 are likely to decrease your workload instead of increasing it. Second, if your boss gives you additional tasks, you can always say, “there would be too much on my plate, what other tasks of mine should I give up?”

Here are some more good questions to ask, this time to people in the position you aspire to reach over the next 2-5 years:

1. What are the requirements, explicit and implicit, to get where you are?

2. What did you do that helped you get here?

3. What did you do that, in hindsight, turned out to be a waste of time?

The people to whom you ask these last three questions do not have to work at your company – look for answers inside and outside (but careful with contacting competitors, though, if policies or ethics forbid it; consider asking to people covering the position you seek in another industry or reading information from public sources, taking everything with a grain of salt).

Asking for support

It is your boss’s job to help you be effective. Whenever you face an obstacle that you cannot solve by yourself, or that would be addressed much faster if your boss intervened, ask him for support.

Some examples of support you can request:

– “I’ve never done X. I would need some training.”

– “To complete my task, I need input from Legal, but they’re not replying to my emails. Can you give them a call so that they do not delay my project?”

– “This task is way below my paygrade. Can we outsource it?”

Of course, you should not ask for help on anything you can solve within 15 minutes with the help of a Google search or by asking your colleague next door.

Lazy vs. Effective

It will happen that one day, your boss gives you one task too much. It is your responsibility to tell him or her that you have too much on your plate.

Many prefer not to ask because of the risk of appearing lazy. They try to handle everything – either burning themselves out or making some mistake. This is not good, neither for you nor for your company.

Instead, you can ask in the following way, which will make your boss think not that you’re lazy but that you’re effective: “Boss, I have too much on my plate and cannot possibly do everything well enough and on schedule. Which of my tasks should I postpone or outsource?”

It’s not lazy to ask for support. It’s lazy not to ask.

Efficacy vs. efficiency

Here’s a mistake that too many young employees make. At university, money was the constraint. Students do what they can with what they have. Later, they use the same approach at work. If they are given a task and a budget, they would rather achieve 80% of the target with 50% of the budget rather than going over budget.

Sometimes, this is appropriate. Other times, it’s a mistake. In many companies, the constraint is not money but results. Your boss might be glad to increase your budget by 20% if that means you will reach your target but might be furious if you fail to achieve it – even if that meant money saved.

Never compromise on results. If you are given a target and feel like you might not achieve it, raise your hand as soon as possible and ask for what you need. When you do so, make sure that you ask for support first, and only ask for a target relief if you’re denied the support. Asking for a target relief first does make you seem lazy.

Asking for raises and opportunities
The first rule of raises and opportunities is: don’t ask, don’t get.

Sure, you might have seen someone getting a raise because it would be impolite not to do so after five years of loyal service. But the point is, how much more would she be paid now if she had asked for a raise the right way every 12-18 months?

You must ask for raises and growth opportunities.

A test for proactivity

Many companies do not tell their employees about opportunities for professional growth, such as internal job openings or career programs. Their reasoning is that career opportunities and cash are limited resources. They should be given not just to those who deserve them but to those who have enough ambition to do more for the company. And what’s a better test for ambition than seeing what comes asking for more?

Don’t ask, don’t get.

I know; I also wish that I hadn’t had to ask for what I deserved. Sadly, that’s how things work in some companies. And if that’s representative of your workplace, there is little you can do other than acknowledge the situation and either ask for more, get yourself another job, or accept that nothing will change much anytime soon.

The 3 ingredients to a raise

There are three components of getting raises.

1. Know what is possible. In many industries, a raise every 12-18 months is realistic.

2. Do the work. You must show that you delivered value to the company beyond what’s expected from your current paygrade. Not that you worked harder, but that you delivered more value.

3. Ask for it. Make a well-thought case of why you deserve more.

Let’s see each point one-by-one.

Know what is possible

You must know what reasonably talented people in your role and industry can expect as a career progression. It will make the next two points easier: you will be more motivated to put in the work, you will be more likely to ask for a raise, and you will have a better argument when asking for it.

Common sources to know what a good career progression looks like in your industry is to consult dedicated websites such as glassdoor dot com, online communities, and hanging out with people who’ve been where you’re at.

Yes, I know, if you ask an ethical professional how much he makes, he might not answer the question (because of confidentiality). But it’s fair to ask how frequently he asked for a raise and what it took for him to get it.

Do the work

Of course, you should do the work to ensure that you provide enough value so that when you ask for a raise, it’s justified. Also, unless you genuinely believe that you did the work to deserve a raise, you won’t feel confident enough while asking for it.

“Do the work” means “do what it takes so that your boss is willing to ask his own boss to give you a raise and that he has a great argument for it.” (Yes, I know, your boss might have the authority to give you a raise without asking – but it doesn’t mean that he won’t have to justify it to his own boss.)

Ask for it

The best time to ask for a raise is perhaps during your yearly performance review, but you don’t have to wait for it necessarily, especially if it’s months away.

Before meeting your boss, make sure you’re well prepared. List down the following:

– The tangible value you brought to your boss or to the company, preferably with the financial value of your contribution (e.g., I closed the Nike project for $X, the process I improved saved $X, and so on).

– How much you’re asking for a raise.

– Why this is not much (because you can make their money back, because other companies offer similar progressions, etc.)

Show you did the work.

Handling objections

The most common objection your boss might give you is, “we don’t have the budget.” This might or might not be true. Regardless, you should ask for clarifications on whether it is a temporary thing that will resolve soon. Unless you’re given a clear answer that explains step-by-step when funds will become available and from where, you should assume funds will always be an issue. Too many people waited for “just a few more months” for a raise that never materialized.

At this point, you have three options.

1. Ask for a raise but not in cash. More vacation days, for example, but also growth opportunities (such as trainings, mentorships, etc.) or more interesting projects to work on. Alternatively, you can ask to be relieved from some of the tasks that are draining your energy – such as having to file travel expense reimbursements yourself or other menial tasks that can be outsourced to someone else.

2. Look for another job. If you are not satisfied with the career paths that your company is offering, feel free to look for another job – at another company, or at your current company but in a better-funded department, if any.

3. Work with your boss on a solution that would give the company enough funds to give you a raise. This doesn’t apply to all companies, but you can always propose to your boss something along the lines of: “let me pursue this new project / client / opportunity, and if it succeeds, I get a raise.”

If you go for the last solution, make sure that you define what “if it succeeds” means in objective terms. Example: “if I bring a new client worth at least $200k” or “if I manage to increase production to X units an hour.”

(We’re about halfway through this post… If you think that it has been useful, please share it with your network!)

Asking for a career opportunity

This is not so different from asking for a raise. The points listed above apply here too. In addition, you should also list:

– The times you demonstrated the skills that are needed for the career opportunity you’re about to ask.

– The tangible benefits that your boss and company are likely to receive if you are given the opportunity. Be realistic but not conservative.

When to ask for a raise or a career opportunity

The number one rule is: inform yourself to what a reasonably fast-paced career progression looks like in your industry, then try to match this pace. You do not want to look for geniuses for whom work is the sole focus of your lives, but you do not want to look for average employees either. Look for reasonably ambitious people whose life you would be willing to exchange places with (both the good and the bad).

Once you know how fast a good career progresses, try to replicate it. If, for example, this means a raise every 18 months, then ask for a raise at least every 18 months.

Do not let too much time pass by

It’s important that you do not let too much time pass for two reasons: compounding and precedents.

Compounding. In most cases, raises depend on your previous salary. This means that failing to increase your salary once means that all future salaries of yours will be lower than they could have been. For example, let’s s say that Adam and Bob both got hired at the same time, for a salary of $2000 a month. After one year, Adam gets a raise up to $2200. Bob doesn’t. At the end of their second year, they both ask and receive a raise. Adam now earns $2400 whereas Bob earns $2200. This is true even if Adam’s and Bob’s output is the same! And what’s worse, it’s that this difference will keep compounding over the rest of their careers.

This applies to promotions too. A fast early career might make your later career faster. Similarly, you might want to consider that grabbing job opportunities is easier when you’re in your twenties and flexible than when you’re thirty and perhaps with children.

Setting a precedent. The more times you let pass without asking for a raise, the more you set a precedent that you’re okay with not receiving raises. This is bad for two reasons. First, your boss will be more likely to think that he can refuse or postpones eventual future requests of yours, for you’ll keep being a good employee anyway. Second, you will be less likely to ask for raises in the future or to do so confidently.

If you want to go fast, you must keep the momentum up.

Of course, the fact that a fast progression is possible doesn’t mean that you should go for it. Look inside you, what you want, and what your values are. Consider the negative impact that a promotion that requires a move might have on your social circle and family. Again, this essay is a map, and as with any map, it should only be used if it contains the path you want to take.

Never accept an increase in responsibility without getting something in return

For the same two reasons listed above, whenever it happens that your boss increases your responsibilities, always ask for something in return.

It doesn’t have to be a raise or a promotion, especially if you received one not long ago. You can ask for more holidays, flexible working hours, better tools to do your job more efficiently, more internal support, trainings, certifications, and so on. You can ask to work on better projects or to be relieved from bad clients. (“Better” depends on what you look for: less stress? Bigger challenges? It’s up to you. But don’t let chances to make your time at work better.)

Weekly updates

Send your boss weekly email updates – especially if he didn’t ask for it.

Keep them short. Do not waste his time.

Don’t write what you did last week (do so only if you did something remarkable; you do not want to pass as needy). Instead, write about what you’ll do this upcoming week. Mention the bottlenecks you’re facing. Your boss might help and will anyway be more considerate of the obstacle you face. He might even improve your processes or give you support.

Here’s a template.

Boss Name,

Last week, Mark and I closed the Williams contract, worth $300k.

This week, I will work on the Chicago project. I am still waiting for the contract review from Legal – could you please give them a call to ensure they send it by tomorrow? This would help ensure that the project continues smoothly.

Thank you,

Your name

Short, to the point, actionable, not wasting your boss’ time.

Mentorship

Some people find mentors to be of great help. I do agree, though I do not believe that you need a formal one. The alternative would be, at each stage of your career, to find a person whose advice can help you. Then, reach out to him and ask for help or advice.

This will help you get where you want to be much faster than otherwise.

Asking for help and advice

The first rule of asking for help is to avoid wasting your mentor’s time.

This means, when you first reach out to him or her, always ask for what you need directly. Do not ask for a call or a meeting. Ask for what you need. Meetings should be an option at his or her discretion, not the object of your request. This is because many people are willing to help you but have little time available. The less time you request for them, and the easier you make it for them to help you, the more chances you have they will do it.

The second rule of asking for help is to explain what you will do with it. The more your mentor sees that what you want to do is impactful, the more he will be willing to help you. Of course, if there’s something in it for him, highlight it. But it’s okay to ask for something he or she will gain nothing out of it, as long as it’s impactful.

The third rule of asking for help is to write personal emails. Cold emails (the technical name for an email sent to someone you never met) don’t have to be “cold” as in “impersonal.” The opposite: you should tailor them to their recipient, explaining why you are reaching out to him or her specifically and why they are uniquely positioned to help you. As a rule of thumb, if your cold email could have been sent to any other recipient just by changing the name, it’s spam.

To summarize: make it easy and worthwhile for others to help you. If you do, you will be surprised by how many people will be willing to help you. If you don’t, you might end up believing that you’re alone and the world is a selfish place.

Understanding metrics

You must know and understand three sets of metrics: the ones that measure your performance, the ones that measure your boss’s performance, and the ones that measure your company or department’s performance.

Unless you do, you will not be able to know what tasks are for. You will risk doing something useless and not knowing it. Also, you will miss a lot of opportunities to be effective.

The three sets of metrics listed above can and should become one of the compasses you can use at work to decide what to do, what to prioritize, and what to explore (the other compass should be your values).

Finally, there’s one more set of metrics you should familiarize yourself with: the metrics that measure performance at the next job in your career progression. You do not need to work on them right now, but you must work on the skills that will be needed – and eventually find ways to showcase them. After all, that’s one way to demonstrate you’re ready for your next job.

The three factors that influence your career

Three factors will have a disproportionate influence on your career.

1. How good you are at your job. Obviously.

2. How fast is your department / company / region / industry growing. The faster it grows, the more budget and opportunities will be available.

3. How good is your manager, and how aligned your values are. A bad manager might become your worst nightmare and significantly affect your income and stress levels, and thus your life outside of work.

Too many people focus on the first one and leave the other two to chance. Don’t. The impact work has on your life is too important.

Of course, this doesn’t mean “forget about your childhood friends and dreams and go to work in tech in San Francisco.” It means to know that where you work opens some doors and closes others, and that good opportunities can be found in the unsexy city if you look for them in the right industry. Make an intentional choice based on your dreams and values, and do not let it up to chance.

Similarly, your boss might be the best or worse thing that happened in your career. While interviewing for a job, make a point of meeting your new boss or ask your potential future colleagues about him or her. If you find yourself with a terrible boss, find a way to get a new one (for example, by transferring to another team or company). Otherwise, he or she might wreck your career, health, and personal life.

A recap of the most important points

• Doing more of what got you here won’t get you there.

• Don’t work more hours than necessary; if you want, use the extra time to do what will get you your next job, not more of the work you’re already doing.

• Ask for what would make you more effective – it’s in everyone’s benefit.

• Know when you should ask for raises. Prepare yourself by showing the value you delivered in $$ terms. Handle objections.

• When asking for help, don’t waste your recipient’s time and make it easy for them to help you.

• Know the metrics that matter to your job, your boss’, and your company.

• Don’t leave to chance who you work for and who’s your boss.

Conclusions

These were a few of the things I learned too late about career in a corporate environment. Hopefully, they will be of help to you.

I wrote a book from a similar point of view, called 100 Truths You Will Learn Too Late. It got great reviews and helped hundreds of people. You can download a copy here.

If you know anyone who could benefit from this blog post, please share it with them! Also, you might want to subscribe to my newsletter to receive future ones.

The Lindy Effect, from Taleb’s book “Antifragile,” can help you.

The Lindy Effect: what is it?

The Lindy effect, sometimes also called “Lindy’s Law,” relates age to life expectancy.

For people, every year of life DECREASES its remaining life expectancy. A 70-year-old is expected to live 14.4 more years, and a 71-year-old is only expected to live 13.7 more years. One year of life reduced life expectancy by 0.7 years.

Conversely, for ideas and technology, every year of life INCREASES their life expectancy. For example, books on the NYT bestseller list only remain there for an average of 5 weeks. However, a book that makes it to the 5-week threshold is expected to stay there for more than 5 weeks. The longer a book is on the NYT bestseller list, the longer it’s expected to stay.

In Antifragile, building on Mandelbrot, Taleb describes the Lindy Effect as the following:

"For the perishable, every additional day in its life translates into a shorter additional life expectancy. For the non-perishable, every additional day may imply a longer life expectancy." – Nassim Nicholas Taleb

What justifies the Lindy Effect?

The older something is,

• the more conditions it must have been fit for,

• thus, the broader range of possible futures it is fit for,

• thus, the longer it is likely to survive,

(in the absence of bounds such as senescence).

Taleb also presented a statistical justification for the Lindy Effect in his books. I won’t cover it here, as I try to keep the understanding of the Lindy Effect intuitive.

Perishables and non-perishables

The reasoning above doesn’t apply to people, for senility poses a natural bound to the maximum age they can reach. An 80-year-old person cannot survive another 80 years.

The Lindy Effect mostly applies to entities with no natural boundaries to life expectancy: technologies and ideas. For example, it applies to books, movies, and technologies such as bicycles (but not necessarily to objects subject to decay, such as bicycles).

However, the applicability of Lindy based on the criterion perishable / non-perishable is not as black and white as it seems. For example, Lindy doesn’t apply to adults but does apply to babies. A baby that survives his first week has a considerably longer life expectancy than a newborn. Therefore, we can say that the Lindy Effect applies to perishables, but only when distant from natural bounds such as senility. As an entity approaches its natural bounds, decay dominates Lindy (more on this later on).

The Hazard Rate

For non-perishables, such as objects and ideas, the main determinant of life expectancy is the hazard rate (the chances of dying/disappearing at age X).

When we observe an object’s life, we can use Lindy to estimate its life expectancy or hazard rate. For example, we can estimate a book’s life expectancy on the bestsellers’ list (its life expectancy) or its chances of dropping off next week (its hazard rate). Of course, the two are negatively correlated.

That said, we can reason the following.

The older something is,

• the more conditions it must have been fit for,

• and thus the broader range of possible futures it is fit for,

• and thus the lower its hazard rate.

Our estimate of an entity’s hazard rate decreases as time passes without it breaking/disappearing.

The first keyword is “an entity’s.” A book staying months on the NYT bestsellers’ list doesn’t mean that all books on it are less likely to drop off next week. It just means that that specific book is less likely to disappear.

The second keyword is “our estimate.” The book’s hazard rate doesn’t decrease over time. Its hazard rate is probably constant. Instead, it’s our estimate that decreases. The longer the book survives, the more reasons we have to lower our hazard rate estimates.

The hazard rate for perishables

We previously saw that Lindy applies to perishables, but only when they are distant from natural bounds, such as senility. Now that we know about the hazard rate, let’s clarify this sentence.

We can decouple the effects of Lindy and of decay into multiple hazard rates that we can aggregate together to obtain an entity’s total hazard rate. For example, a person’s total hazard rate is made of:

• The hazard rate from accidents (subject to Lindy; the more a person survives, the more we can suppose them to be cautious, and thus, the lower our estimate of his hazard rate from accidents).

• The hazard rate from illnesses and internal conditions (e.g., stroke) is a component not influenced by genetic causes (this increases linearly or exponentially with age).

• The hazard rate from illnesses and internal conditions is a component influenced by genetic causes (subject to Lindy – the more a person survives, the less likely he is to have genetic conditions).

• The total hazard rate of a person is the sum of the three points above. The second one becomes dominant as one person approaches the natural bounds of human longevity. Hence, it’s not that Lindy does not influence the life expectancy of perishables – it does, but it loses relevance over time.

The Lindy Effect, generalized

Lindy is not just about time but also applies to other dimensions: space, cultures, uses, conditions, etc. Here are a few examples of practical applications.

Continuing the NYT bestseller example, a book sold in one country only might be successful because it’s a great book or because it talks about something very relevant to that country.

Once it’s translated & does well in another country, the odds it’s a great book increase.

In general, the more geographically widespread something is,

• the more conditions it must have been fit for,

• thus the broader range of conditions it is fit for,

• thus the lower the estimate of its hazard rate upon entering a new geography.

I suppose the same works across cultures, use conditions, and most dimensions. (Remember the limitation of “estimates made by the Lindy Effect are subordinate to intrinsic limits.” For example, a book read in 150 countries is not likely to be read in 150 more countries, if there are only 200 of them on Earth.)

For example, bicycles are Lindier than cars.

• not only are they expected to be around for longer,

• but they can also be used in a wider range of conditions (off-road, in the absence of fuel) and can be built/repaired by more people with less specialized tooling.

Therefore, we can often use the Lindy Effect to estimate not only life expectancy but also usefulness / relevance / maintainability across a wider range of conditions / use cases / skills, etc. (again, a reminder: it is probabilistic, not deterministic)

Before closing this essay, I have two more remarks.

What the Lindy effect is not

The Lindy Effect estimates an entity’s hazard rate, not whether it is good or bad. You can’t say, “It’s Lindy, therefore it’s good.” Mosquitoes are Lindy.

Second, being Lindy doesn’t mean that something cannot disappear tomorrow. It just says we have reasons to believe it’s less likely than it would be if it hadn’t been around for so long.

The Lindy Effect doesn’t tell you how long something will survive. It helps you estimate its hazard rate or life expectancy – both of which are probabilistic.

Lindyness, what is it?

Lindiness is the property of being Lindy, in other words, of having been around for a long time and, therefore, being expected to be around for a long time from now.

It only applies to the non-perishable (e.g., ideas, book contents, technologies, songs, etc.) and carries no moral valence.

Its use is to estimate whether an assumption will still be relevant over long time horizons.

What are some examples of Lindy?

Some examples of things that are Lindy:

• Books
• Songs
• Ideas
• Technologies
• Recipes

Some examples of things that are not Lindy:

• Food
• People
• In general, anything with a bounded life expectancy

Further readings

I first read about the Lindy Effect in Nassim Nicholas Taleb’s Antifragile (whose reading I strongly recommend). Here, I wrote some thoughts on the process behind it and how we can apply it to more use cases.

Also, just like this essay, my book on Ergodicity takes a complex concept related to survival and makes it simple and practical.

Conclusions

• The Lindy Effect: for ideas and technology, every year of life INCREASES their life expectancy.

• The Lindy Effect also applies to perishables, but only when distant from their natural bounds.

• The Lindy Effect is not deterministic but probabilistic. It doesn’t tell you how long something will survive. It helps you estimate its hazard rate or life expectancy.

• The Lindy Effect doesn’t tell us whether something is good or bad.

• We can often use the Lindy Effect to estimate not only life expectancy but also usefulness / relevance / maintainability across a wider range of conditions / use cases / skills, etc.

1. Warehouses are expensive. They occupy precious land, are expensive to build and maintain, locks capital into inventory, and require personnel.

2. Warehouses hide problems. If the suppliers have a late delivery but the warehouse still has stock, no one will notice. Therefore, suppliers are allowed to operate sloppily.

To avoid these two problems, some companies adopted a Just In Time philosophy. They request suppliers to deliver the components at the exact moment they are needed. This has two beneficial effects.

1. It reduces storage costs. The warehouse can be smaller, costing less to build and maintain. Less capital is locked in inventory. Less personnel is required to handle the components and maintain the warehouse.

2. It surfaces problems. If there is little or no stock on the factory grounds, production must stop if a supplier is late. This surfaces logistical problems and makes it urgent to solve them. As a result, the operations of the company and its suppliers become more reliable.

However, Just In Time has one flaw. It makes the company fragile to supply chain disruption. For example, the recent pandemic that hit global logistics crippled companies relying on Just In Time suppliers.

The solution is to keep some stock, but make it hard to access. For example, a signature from the Operations Manager might be required to pull stock from the warehouse. This way, you have some protection against logistics disruption, and you partially cut storage costs and surface problems.

Examples of Wittgenstein’s Ruler

The Nobel Prize for Economics being awarded to someone can mean two things: either that the receiver is very smart or that the judges are very dumb.

At the moment of the award, we probably didn’t know which of the two possibilities was correct. Sure, the receiver of the price must have sounded smart, but we did not know whether he was actually smart or if the judges were dumb and gullible. There is more than one free parameter (the quality of the receiver and the quality of the judges), so we do not know which one is being measured by the award assignment.

A similar phenomenon can be observed during the COVID-19 pandemic. In April 2020, a few studies were published on the prevalence of antibodies in some populations. However, we do not know if the studies are measuring the prevalence of the virus or the reliability of the tests.

Wittgenstein’s Ruler: a definition

Wittgenstein’s ruler can be formalized as follows:

Extending Wittgenstein’s Ruler

Interestingly, Wittgenstein’s Ruler is not just about the precision of the ruler but also about its choice. For example, centralization tends to result in the choice of metrics that, regardless of their precision, only measure some of the results that matter to the general population, resulting in effects such as “centralization is only efficient to the central observer.”

This is because the central observer is the one that chooses the ruler, i.e., the metrics to measure.

I used to understand the term “ruler’s reliability” as simply a matter of precision/variance; instead, it’s also a matter of choice of the ruler and metrics used to conduct the measurement. Do they reliably help estimate properties of the object of the measurement, or do they estimate something else?

Hence, we can use Wittgenstein’s ruler even before the measurement is conducted, using the choice of the ruler to deduce the properties of the measurer.

Mechanical parts and components were scattered on the warehouse floor at all times. Employees even had trouble walking without stepping on something. For months, he repeatedly told his employees never to leave parts on the floor and always store them properly.

They never did.

The problem was that the warehouse was too big, and the manager was too busy to consistently enforce the standards they asked his employees to follow.

So, he decided to restrict the scope of change to a single point in the warehouse and to obsess over it. He chose the area next to a machine. He held a stand-up meeting with the warehouse employees and told them that the area next to the machine always had to be clear of all parts. He told them to clear it immediately and didn’t leave the warehouse until that area had been cleared.

For the next month, he made a point of visiting the warehouse multiple times a day and, first thing there, look at the floor next to that machine to see whether it was clear. If not, he would immediately stop whatever he was doing, walk to the nearest employee, remind him that the area had to be clear, and stay there until it was.

He obsessed over it.

After a week, the warehouse employees learned that the machine area was to be left clear.

After two weeks, the employees began noticing that the area next to the machine was easier to walk in and parts were easier to find there.

After three weeks, the magic happened. The employees began to clear the other areas of the floor of their own account.

The manager achieved what he couldn’t before by focusing change over a small area, obsessing over it, and letting others see the benefit of the change.

This is the magic of obsessive consistency. Once the workers understand that they can change faster than their manager, they will. Once they understand that if they change, good things happen, they will.

Good managers know the effectiveness of obsessive consistency.

To create change, restrict the scope of the change so that you can afford the bandwidth necessary to enforce it.

Good managers aim to reach critical mass

They know that habits need a critical mass to form.

Some experts say an action becomes a habit once it is repeated for 21 straight days. Others say it becomes a habit once everyone in a room performs it at once.

Both groups of experts recognize the importance of reaching a critical mass of action, both on the temporal and social levels.

Consistency is essential for two reasons. First, it helps to achieve the critical mass that leads to action being converted to habits in our brains. Second, lack of consistency kills habits. The first time that you allow an employee to perform below standard without consequence, you open the door to him doing it a second time or to others doing it for the first time. They and their peers will interpret it as a signal that no one cares if someone performs below standard.
It doesn’t matter whether it is true. What matters is the perception that is created.

Because good managers know the importance of reaching critical mass, they restrict the scope of the change to be achieved at a time. Instead of asking their subordinates to adopt five new habits this month, they ask them to adopt only one. Otherwise, they would have to divide their limited time between noticing and praising or reprimanding five habits or lack thereof. By focusing on noticing a single habit, good managers decrease the likelihood of missing an instance where a subordinate failed to express the required habit.

Because they know the importance of reaching critical mass, good managers restrict the number of people who must adopt a new habit at a given time. Instead of requiring their whole building to adopt a new habit, they focus on one or two teams at a time. This way, they won’t have to spread their attention too thin. They ensure that no bad habit will go unnoticed and no good one unreinforced. They know that employees watch how their colleagues are treated. If they see a colleague failing to adopt a new habit and nothing is happening, they will learn that they can do the same. By obsessing over a single new habit of a small group of people at a time, good managers ensure that no such occurrence occurs.

The top-down gets selected because it makes sense, not because it works.

The top-down fails because it is applied to scale before having been tested in the conditions it will be applied to and in the conditions it will find itself after the environment reacts to its introduction.

The bottom-up is the voluntary adoption of a pattern because it works, by those who find themselves in a similar environment to where it has been proved to work.

The bottom-up works because it is adopted only after it has been proved to work.

The top-down works in theory, the bottom-up works in practice.

It doesn’t mean that if something is bottom-up it will work, but it means that: if something works it is bottom-up and that if something

• If something works it is likely bottom-up

• If something is bottom-up and reaches wide adoption then it works.

The top-down is bad because when it fails, it fails for all (because it gets introduced to scale before extensive testing in local conditions). Potentially threatening the whole.

And yet, we keep desiring top-down solutions for our problems, as if every instance of a given problem has the same cause.

The top-down inherently brings fragility, because:

• The top is centralized, thus local harm might be fatal
• Mistakes made by the top propagate to the bottom

Both the above increase risk of systemic damage.

When the top-down works, it is because it skewed the risk curve towards the tail: creating a false sense of security until it fails spectacularly.
Conversely, the bottom-up front-loads the risk: what survives and gets adopted the bottom-up way is usually safer.

Long-lasting progress is always bottom-up, because the bottom-up becomes adopted after having being proven to work. The top-down is fragile because untested.

• The flow of life is bottom-up.
• The arrow of causality is bottom-up.

History repeats itself because history is made by the bottom-up, not by the top-down, and the bottom-up is relative, and the relative takes place over and over again, just like we all aspire for a better life for ourselves, no matter how good our life is.

Top-down practitioners consider their peers to be the ultimate judges of an idea; bottom-up practitioners consider reality to be the ultimate judge of an idea.
Top-down that works is impossible. It necessitates full knowledge of the territory, and no single sensor could be tuned perfectly to make every detail of the territory legible (it would have to be calibrated to a single part of the territory).

We are under the illusion that there is something top-down which can influence the world in a lasting way. Either it won’t last or it’s something which emerged the bottom-up way and we confabulated it as top-down. Examples: inventions, policies, thoughts, careers, successes.

Less time should be spent on discussing top-down solutions and more on creating the conditions for bottom-up ones.

Below, you will find the text of the old essay, for reference purposes.

The basics of antifragility

Antifragility is a concept first proposed by Nassim Nicholas Taleb in his book Antifragile. Oversimplifying, humans and other living beings are antifragile: they benefit from stressors. Does it sound weird? Think about the last time you went to the gym: applying a physical stressor (the weights you lifted) made your muscles grow.

Moreover, antifragile entities benefit from stressors in a nonlinear way. If you walk 2 kilometers per day, your athletic condition will not improve that much. However, if you run one kilometer per day at approximately twice your walking speed, your athletic condition will improve noticeably.

The intensity of the stressor matters more than how many times it is applied.

Other entities, such as ceramic vases, are fragile: they are harmed by stressors, in a nonlinear way. If you let a ceramic vase fall one hundred times from one inch, it will not break. However, if you let it fall once from one hundred inches, it will break.

The antifragile is also fragile

We have seen how the antifragile benefits from stressors. If we lift weights, we become stronger.

And yet, despite our antifragile nature, we can break – such as my ankle that time that I jumped from a wall a bit too high.

Antifragile beings are antifragile only in a given range of stressors.

Moreover, antifragile beings can became weaker, such as my grandma aging.

Antifragile things can appear to become fragile. They never actually lose antifragility (the capacity to benefit from some stressors); rather, the range of stressors which are beneficial for them can shrink. Though antifragile entities never become fragile, they might change their likelihood to react to stressors like a fragile entity.

The difference between antifragile and fragile entities is not that the former do not break under stressors; rather, antifragile entities become stronger if they receive stressors inside a given range, and that they become weaker if they lack such stressors; in other word, antifragile entities are adaptive and fragile ones are not.

In the rest of this essay, I will describe how the adaptation process of antifragile entities to their environment works.

Before continuing, let me clarify one key concept: antifragile entities cannot become fragile (i.e., they do not lose the property to positively react to stressors in a given range). However, they can have such range reduced. I call fragilization such reduction of the range of stressors that benefits them, and antifragilization its increase.

The conditions for antifragility

Antifragile entities have a common property: they comprise a population of sub-entities at a lower layer.

Some examples:

• Animals and plants are composed by cells.

• Species are composed by a population of animals or plants.

However, also ceramic vases are composed by a population of ceramic molecules, and yet they are fragile. Something is missing in the previous definition. Let’s try again:

Antifragile entities have a common property: they comprise, at a lower level, a population of sub-entities which are subject to natural selection.

Some examples:

• Animals and plants are composed by cells; if subject to a stressor, the weakest cells die.
• Species are composed by a population of animals or plants; if subject to a stressor, the weakest members die.

Natural selection is what provides antifragility. Natural selection necessitates stressors (to kill the weak).

However, some might say: “hey, also the molecules of a ceramic vase undergo natural selection: if you make a vase fall, some of the molecules that form it (or rather, some of the bonds between them) will break; moreover, it’s not random ones that break: it’s the weakest ones.” Something is missing, again.

Antifragile entities only exhibit antifragile behavior when their underlying population dies in a distributed way.

Some examples and counterexamples:

• Animals are composed by cells; if subject to a stressor, the weakest cells die. If the weakest cells die in a distributed, non-local way, the exhibited behavior is antifragile (lifting weights at the gym breaks only a few muscle cells here and there, and the muscles regrows them in excess, becoming stronger). If the weakest cells die in local way, the exhibited behavior is fragile (if I lift a very heavy high, my muscle might strain and I lose the ability to use it properly for a few days; if I jump from the third floor, all the cells in a given area of my leg bone break and the bone breaks).

• Species are composed by a population of animals or plants; if subject to a stressor (such as a famine), the weakest members die. If the members die in a distributed way (some members of this tribe, some children of this family), then the tribe or family grows stronger (thanks to natural selection and learning): an antifragile behavior. However, if all the members of a local population die, then, simply, that tribe is exterminated, without opportunity to adaptation (through natural selection and/or learning): a fragile behavior.

The disappearance of antifragile responses

In the previous part, I described how an entity needs four conditions to be able to express an antifragile behavior:

• to be composed of a population at a lower layer,

• to allow for natural selection to act,

• to ensure that natural selection kills its lower layer in a distributed way,

• to be able to grow their lower-layer population up to a point of redundancy.

In the rest of this essay, I will describe what happens if natural selection is prevented (through the removal of skin in the game or through the introduction of “fences”) and what happens if conditions are present which might cause its population to die in a non-distributed way. In both cases, we will see, the consequence is fragility.

First, let’s see how a fragile entity reacts to stressors.

Note: the above is called a "Dellanna Diagram".

If the intensity of the stressor is lower than the fragility threshold, no change happens (if I let a ceramic vase fall from 1 inch, it doesn’t break).

If the intensity of the stressor is higher than the fragility threshold, the fragile entity breaks because its lower-layer population incurs a localized death (if I let a ceramic vase fall from 3 feet, the molecule bonds along a weak crystal boundary break and a crack appears).

(For the time being, I am applying a simplification: considering single stressors only. As engineers know, some entities exhibit a behavior called “fatigue failure”, where the effects of smaller stressors accrues over time. For the purpose of explaining the current concepts, I am only considering single stressors. Later in the essay, I will clarify the effects of distributions of stressors.)

Now, let’s see how an antifragile entity reacts to stressors.

If the intensity of the stressor is higher than the fragility threshold, the antifragile entity breaks because some of its lower-layer population breaks in a localized pattern (for example, if I jump from the second floor, I might break a bone).

If the intensity of the stressor is between the fragility threshold and the antifragility threshold (the green area above), then antifragilization happens. For example, if I jump fifty times over a 3-feet tall obstacle, I will grow some leg muscles. Antifragilization happens because the lower-layer population dies in a distributed way (for example, I break some muscle fibers here and there: this triggers muscle regrowth. If I exercised too hard, I would broke the muscle fibers in a localized way and I would have a muscle strain: an injury, a fragile behavior). I call this behavior antifragilization because it modifies the future response of the antifragile entity to future stressors. Following the effect of the stressor in the antifragilization area, the fragility threshold moves to the right, as the entity grows stronger and able to withstand more intense stressors without breaking (the more I go to the gym, the more I can lift without straining myself). As a result, there is a bigger proportion of stressors which induce an antifragile response in my entity: it became more antifragile. Hence, antifragilization. I will describe this behavior better later on.

If the intensity of the stressor is, instead, lower than the antifragility threshold (the orange area in the image above), no member of the lower-layer population dies. For example, if I lift a matchbox, the weight is too low to break any of my muscle fibers and to induce any muscle growth. If, over time, no stressor happens to be higher than the antifragility threshold, then fragilization happens. If I do not exercise for a few of months, my muscles mass will decrease, and I will lose the ability to lift heavy weights. In such case, both the antifragility threshold and the fragility one decrease (moving to the left in the image above). Because the fragility threshold lowered, the antifragile entity is more likely to express a fragile behavior (because, given a stable distribution of stressors, now a bigger proportion of them falls above such threshold). Therefore, fragilization, I will describe this behavior over the next paragraphs, just after antifragilization.

Antifragilization

As displayed in the image above, antifragilization (the process that happens when an antifragile entity is exposed to stressors whose intensity falls between the fragility and antifragility thresholds), consists in a distributed death, followed by an adaptation and therefore an increase in both the antifragility and the fragility threshold. The increase in the fragility threshold is bigger than the increase in the antifragility threshold, so that the range of stressors inducing an antifragile reaction is bigger, and therefore the antifragile entity becomes more likely to exhibit an antifragile reaction.

Why does antifragilization happen?

Antifragilization is the result of adaptation following natural selection.

Step by step:

1. A stressor hits the antifragile entity. For example, I lift some weights.

2. The stressor is strong enough to induce natural selection: it kills the weakest members of the lower-level population. Continuing the example, lifting the weights causes some of my muscle fibers to break.

3. In antifragile entities, those weakest members are usually normally distributed; therefore, a distributed death occurs. The distributed death is well-absorbed by the entity and therefore does not cause it to permanently lose any functionality. (I will describe later what happens if, due to some external intervention, the weakest members are not distributed and therefore a localized death takes place.) Continuing the example, the muscle fibers which break are not grouped in a single location (as it would happen in case of a strain) but are distributed along all the muscle.

4. A first effect, is that since the weakest members of the population died, the average survivor is stronger. Only the strongest will reproduce, generating a second-generation population which is stronger than the first one on average. Continuing the example, it is the weaker muscle fibers that die; only the strongest fibers will be left to reproduce, so that the muscle fibers that are born will be strong, on average. A variation of this effect, applicable to populations of humans, is that of learning. Following the negative event, the members of the population that were practicing the weakest beliefs die, leaving only the members with the strongest beliefs alive and able to reproduce. If a source of water in the village is contaminated, only those members of the population who thought that boiling/alcohol are not necessary to purify the water will die, leaving those who thought that boiling/alcohol are necessary alive and able to pass their advantageous beliefs to the new generation of the population.

5. As a second effect, the intense stressor creates an expectation of more intense stressors to come, so that the need for redundancy is established, and overgrowth is triggered. Continuing the example, lifting weights creates the expectation, in my body, that it will have to lift more weights in the future; it better prepare itself for the task by growing muscles which are not only strong enough to lift the weight I just lifter, but even stronger to lift even heavier weights. This is the process behind muscle mass growth at the gym. [In what resembles a bayesian interpretation of the world, after being exposed to an intense stressor, our body intuitively modifies the distribution of future expected stressors, so that even stronger stressors, never experienced before, are deemed possible.]

6. The consequence of the two effects described before is an increased tolerance to stressors, which causes both the antifragility and the fragility thresholds to increase.

Fragilization

Fragilization is the result of the lack of stressors and, thus, of natural selection (which needs stressors to kill the weak).

Step by step:

1. For a certain time (weeks, usually), an antifragile entity lacks exposure to stressors above the antifragility threshold. For example, for three months I do not make any physical exercise.

2. In that period of time, natural selection does not take place in the population at the lower layer (at least along the dimension of the lacking stressors). Continuing the example, in those three months no muscle fiber breaks because of an applied physical stressor.

3. A first effect takes place: because of the lack of natural selection, the weakest members of the lower-layer population do not die and are therefore allowed to reproduce. The second generation population has thus a lot of weak members, which means that both the antifragility threshold and the fragility ones become lower. Continuing the example, the weaker muscle cells are allowed to reproduce, and therefore the muscles contain an increasing proportion of weak cells.

4. A second effect takes place: because of the lack of stressors, there is no (apparent) need for redundancy anymore. Redundancy is useful only in bad times; in good ones, it seems unnecessary. Therefore, the antifragile entity adapts in such a way to reduce redundancy. This makes sense, because optimization is an adaptation to stability (for it assumes certain conditions, to which the entity optimizes for, to be present also in the future), whereas redundancy is an adaptation to volatility (for, if no condition is assumed stable, there is no stable condition to optimize for). The lack of redundancy makes the antifragile entity more vulnerable to failure, and therefore more fragile (the fragility threshold becomes lower). Continuing the example, because I didn’t lifted any weight for months, my body assumes I will not have to lift any weight in the future either. It then appears advantageous to reduce the number of muscle cells (to save energy, between other reasons). This makes me more likely to strain my muscles in case in the future I will suddenly have to lift an heavy weight.

5. The consequence of the two effects described before is a decreased tolerance to stressors, which causes both the antifragility and the fragility thresholds to increase.

Antifragile entities are adaptive

As described with the two processes of fragilization and antifragilization, the range of stressors which induce an antifragile reaction in an antifragile entity is not fixed. Antifragile entities are adaptive: this confers them an advantage in a changing environment. However, precisely because they are adaptive, they can also adapt to a stable environment. Adapting to an unstable environment makes an entity “more antifragile” (i.e., more likely to exhibit an antifragile reaction and to adapt to its environment), and adapting to a stable environment makes an entity “less antifragile” (i.e., less likely to exhibit a fragile reaction and to instead not adapt to its environment). Again, I must clarify: antifragile entities never lose their capacity to being adaptive (i.e., to benefit from stressors in a given range); however, they might shrink the range of stressors towards which they react in an adaptive way. Therefore, though antifragile entities never become fragile, they might change their likelihood to react to stressors like a fragile entity.

The importance of natural selection

As described above, lack of natural selection causes fragilization.

There are mainly two processes which prevent natural selection: the removal of skin in the game and the introduction of exogenous barriers (aka “fences”). The next part of this essay will describe them.

(Side note: hacks and quick fixes, which which offer apparently safer shortcuts but tend to bypass or alter natural selection, bring fragility.)

Introduction of skin in the game

First, let’s see what happens if skin in the game is increased in the population forming the lower layer of the antifragile entity. For example, if a human nation (an antifragile entity) passes a law to enforce skin in the game for its citizens (the population at the lower layer).

1. First, the introduction of skin in the game introduces direct accountability: one is more likely to suffer for his mistakes. Since mistakes usually become evident not when things go well, but the moment they turn awry, it is usually following the application of an external stressor (such as a financial crisis) that an individual with skin in the game exits the population (for example, it goes broke or gets fired from his investment firm). The more skin in the game, the more, as a first-order effect, weak individuals are likely to fail in case of stressors; such failure is likely to be distributed (thanks to skin in the game, only the weak individuals fail, without bringing anyone down with them), therefore, it is the antifragility threshold which gets lowered.

2. Because the antifragility threshold became lower, the antifragililization range (the green area) become bigger.

3. A random stressor is now more likely to induce antifragilization (a stressor which would have hit the right side of the orange area would now hit the left side of the green area). Therefore, antifragilization is more likely to happen.

4. As a result of antifragilization, the fragility threshold increases. As a consequence, a random stressor is now more likely to hit the antifragilization area (a stressor which would have hit the red area in its left side would now hit the green area in its right side), and the entity is now more likely to exhibit an antifragility response.

5. Because of the antifragile response being solicited more often, antifragilization happens more often, and the fragility threshold now increases moving to the right and offsetting the movement it did to the left during the first step.

As a result, thanks to skin in the game, all members of the population are now safer (less likely to die because of a random stressor).

It is worth noting that the dominant effect, and the only one significant over the long term, is the one described in the fifth point above, a second-order effect. However, because policy makers usually only think terms of first-order effect, they might take wrong decisions, some that only appear to work in the short term.

Now, let’s see what happens in the opposite case, the removal of skin in the game.

Introduction of exogenous barriers (aka, “fences”) and the removal of skin in the game

Humans do not like risky environments, and often introduce barriers to make them safer. However, often such barriers only increase the sense of safety. As Pasquale Cirillo describes in “The Fence Paradox”, because the barriers reduce the smaller stressors, humans feel safe, they take more risks, increasing the risk of an important negative event once a stronger stressor appears.

In The Fence Paradox, Dr. Cirillo tells a story of tourists taking pictures from the edge of a canyon. Since it is a risky endeavor, only a few tourists venture to the edge, and only do so with great care. One day, one of them goes a bit too far on the edge and falls down, dying. In response to this unlucky event, a fence is build on the edge of the canyon. It now looks safe to take pics from the edge, and tourists flock in. They lean on the fence to take pictures, and push each other in an attempt to take better shots. One day, a big group of tourists relays too much on the fence and they apply too much of their weight to it: the fence collapses, causing the whole group leaning on it to fall and die. After all, the fence didn’t make the canyon safer; it only made it safer to the population exposed to (or exposing itself to) smaller stressors, whereas it made it less safe in case of exposure to bigger stressors (or making the population more likely to expose themselves to bigger stressors).

The image below describes the fragilization which follows the introduction of exogenous barriers (which, by causing the population to reduce their exposure to the consequence of some of their actions, is not so different from the removal of skin in the game).

1. First, the introduction of exogenous barriers reduces direct accountability: one is less likely to suffer for his mistakes. As a first order effect, weak individuals are less likely to fail in case of (small) stressors; therefore, the fragility threshold increases.

2. Because the antifragility threshold became higher, the antifragililization range (the green area) becomes smaller.

3. A random stressor is now less likely to induce antifragilization (a stressor which would have hit the left side of the green area would now hit the right side of the orange area). Therefore, antifragilization is less likely to happen and fragilization is now more likely to take place.

4. As a result of fragilization, the fragility threshold decreases. As a consequence, a random stressor is now more likely to cause death (a stressor which would have hit the green area in its right side would now hit the red area in its left side), and the entity is now more likely to exhibit a fragile response.

As a result, thanks to the introduction of exogenous barriers, all members of the population are now less safe (more likely to die in a localized way in case of exposure to a strong stressor).

The importance of redundancy

In a first-order analysis, redundancy might seem to reduce the likelihood of antifragilization, for there is a higher probability that an exterior stressor is not perceived interiorly. For example, if I am strong (i.e., I have redundant muscles for most daily activities), I will not grow muscles by lifting my not-too-heavy grocery bags, whereas if I am weak and start lifting heavy grocery bags every day, I might actually grow some muscles.

However, a second-order analysis shows the opposite consequence: redundancy increases one’s willingness to expose himself to stressors, and/or his opportunities to do so. A strong person is more likely to go to the gym [footnote] and a person going to the gym is more likely to be strong; the two affirmations are not at odds[/footnote], whereas a weak person is less likely to expose itself to stressors (for example, to offer to help to move furnitures).

Moreover, a stronger person (i.e., a person with redundant muscles) is more likely to survive a stronger-than-usual stressor, meaning that it is more likely to survive to benefit from the stressors. A weak person (one with no redundancy) is more likely to injure itself or to die in case of extreme physical stress, and therefore less likely to continue its exposure to the smaller, more beneficial stressors that will take place in the future.

Therefore, a certain degree of redundancy is beneficial to antifragility.

How to become antifragile?

To conclude, there are four necessary conditions for antifragility, and four actions which can increase it.

The 4 necessary conditions for an entity to be antifragile:

1. It has be composed of a population at a lower layer, and

2. Natural selection has to be allowed at that lower layer, and

3. Killings from natural selection have to happen in a distributed fashion, and

4. The surviving members of the population have to be able to reproduce.

The 4 actions which can increase the likelihood of an antifragile response to a random stressor:

1. Ensuring skin in the game.

2. Removing exogenous barriers (aka, fences).

3. Encouraging redundancy.

4. Reducing sistemicity.

It is worth noting that the 4 action points above only work as second-order effects, and that understanding them requires a dynamic representation of the world. People using static representations of the world (IYIs), and therefore unable to understand second-order effects, are likely to dismiss them as useless.

Note: this was an excerpt from my book, "The Power of Adaptation".

Given that 80% of the rewards are contained in 20% of the activities, if you divide your time and resources equally between activities, you’re doing it wrong. You are negating the existence of Pareto’s law.

Some examples:

• If you’re reading the same percentage of pages for each book, you’re doing it wrong. (given that time is a finite resource). Some books are worth skipping after having read a few pages, whereas other books are worth reading many times.
• If you are attending all classes or all meetings, you’re doing it wrong. Some are worth not attending, and some are worth preparing for before and reflecting upon later.
• If you are spending the same amount of attention on each customer of yours, you’re doing it wrong. Some customers are worth following with double the attention, some are worth the minimum, and some are worth firing (you might discover that 20% of your customers generate 80% of your customer service costs).
• If you are spending the same amount on Twitter each day, you’re doing it wrong. Some days, you’ll be inspired, or great conversations will be going on, and other days, you’ll be just passively scrolling.
• If you are spending the same amount of hours at work every day, you’re doing it wrong. Unless you are the lowest employee at your level in a super-optimized operation, chances are that some days there will be opportunities worth spending more time on, and other days could be finished much earlier.

And so on…

Ruthlessly Pareto your activities.

• Unfulfillment arises from using metrics chosen by others as proxies for personal success (e.g. a new car as a proxy for happiness).

• Sustainability problems arise from using short-term success as a proxy for long-term one (e.g. boosting sales this quarter by delivering false promises to customers).

• Failed relationships arise from choosing a person using widely-desirable traits as a proxy for personally-desirable ones.

In general,

Regretful choices arise from using a widely-accepted metric for success instead of a personally defined one.

Proxy optimization

I once wrote:

“Humans are extremely good at succeeding at their priorities, and extremely dishonest about them”.

With that, I meant that we are great at acting in such a way to succeed at the metric we chose, but often choose the wrong one or do not realize we subconsciously chose another one. I call this phenomenon commitment to failure.

Every time we fail at something we had the resources to succeed at, it is due to the fact that we considered an internal success to fail at it (because we were uncomfortable with the consequences of succeeding at it). In other words, we acted optimizing an internal metric (Expected Emotional Outcome) instead of an external one (success at whatever activity we were doing).[^1]

Even when we choose a proxy that is initially correlated with the ultimate outcome we desire, we often fail at misunderstanding a key concept:[^2]

Optimizing for a proxy reduces the correlation with the ultimate metric.

As an example, imagine an author in the business of selling books online. He discovers that about 2% of his Twitter followers bought his book. He decides to run an advertisement to get more followers (the number of followers becomes a proxy for book sales). Such ad selects followers based on their sensitivity to advertisements, not on their propensity to buy. In other words, it tends to select people who are interested in following the author on Twitter, regardless of whether they are interested in buying his books. As a result, if before the advertisement 2% of followers would end up as customers, after the ad it it is likely on 1% will. The proxy optimization (running an ad optimized to get new followers) diluted the correlation between the proxy and the ultimate metric (the % of followers buying the book).

A useful heuristic: if there is a way you could maximize the proxy without contributing to your ultimate goal, it will happen. Proxies are not chosen because they are more impactful; they are chosen because they are easier to measure or to influence. And the reason they are easier to influence, is generally because there is a population of low-hanging fruits which contribute to the proxy but not to the ultimate metric. Collecting these is a waste: they do not do anything to improve your standing towards your ultimate goal. Optimizing for a proxy often brings a dilution in quality.

Proxies promote unwanted behavior by introducing unwanted rewards towards wasteful actions. It is the same thing that happens when you are not specific in rewarding someone. Let’s say that you told your son “Congratulations for having gotten an A on the test!”, without knowing that he cheated. By rewarding a proxy (the mark) instead of the real thing (the study), you would have reinforced an unwanted behavior (the cheating).

Define success without using proxies

Naval Ravikant said: “A cockroach is just as evolved as we are, just across different fitness functions.” What metric you choose to define success, i.e. your fitness function, matters. It will apply evolutionary pressure on your behaviors and personality traits and shape you, by reinforcing those traits that led to a progress on your chosen metric and by weakening those who did not. Choose your proxies wisely, don’t become a cockroach.

Another reason why proxies should not be used, is because circumstances change over time. It might sound useful to choose a proxy to focus on what appears to be the most beneficial sub-objective now, but this might lead to tunnel vision or to a lack of periodic reevaluation to determine whether the current proxy is still beneficial to follow. What got you here won’t get you there[^3]. Memorizing concepts might be a useful skill to get your degree, but it is a terrible one for a successful career (other than in acting). Money is great to increase your life quality when you’re poor, but it doesn’t do much once you’re rich. What looks a great proxy now will almost invariably be a bad proxy then.

A last reason not to use proxies: they bring noise (because they are partially decoupled from the ultimate metric which we do want to measure) and they bring cognitive dissonance (for the same reason; if we ever take an action which is good from the point of view of the proxy but not of the ultimate metric, we’ll end up asking ourselves “Why did I did it?”.

Following proxies instead of the real thing is similar to drug addiction. Addicts become reactive to the cues (the proxy). Living a diverse life increases happiness because it avoids addiction and tolerance due to repetitively associating rewards to the same cues[^4].

(I am inclined to believe that humans are fundamentally good and happy; evil and unhappiness emerge when they follow unnatural proxies or when they encounter constructs or products engineered to hack metrics, such as advertisements and drugs, and become addicted to them).

Eliminating proxies

Prioritization is the art of spotting proxies and exclude them from our to do list. Proxies are fought with not-to-do lists. A good example is Warren Buffet’s 25–5 rule. Write down the 25 most important things you should do. Circle the 5 most important. Move these 5 to your to-do list, and the other 20 to your not-to-do list (these 20 tasks would be busywork, which, by the way, is a proxy for real work).

Intelligence is the skill of optimizing a given metric; wisdom, the skill of choosing the right one to optimize for.

Some heuristics on how to spot proxies and get rid of them:

• Everything which causes addiction is a proxy.

• Any metric which is not weighted by the impact it generates is a proxy. (And any metric whose correlation/impact to your ultimate goal is approximated to be static in time, is a proxy.)

• If a proxy is chosen because it is easier to improve, rather than easier to measure, don’t choose it.

• If a process describes what it is, rather than what it is for, it has been optimized for a proxy.

• If it won’t be important in five years, it is a proxy.

• If it weren’t important for people one thousand years ago, it is a proxy.

• Doubt everyone whose core competency is a proxy (students whose competency is to pass exams, which are a proxy for knowledge; teachers whose competency is to get papers published, which are a proxy for teacher quality; financial advisors whose competency is looking trustworthy; the salesman who’s great at presenting a slide deck but not at actually making sales happen; speakers whose competency is to use words rather than choosing them; and so on)[^5].

These heuristics won’t be always true, but you’ll be better off by acting like if they did (that’s the point of heuristics).

This was an excerpt from my book “100 Truths You Will Learn Too Late.”.

Many thanks to Damian Ocean for providing insights to the first drafts of this post, which appeared on Twitter.

Notes

[^1]: Alexander Wolfe noted that “What people who don’t risk don’t understand is that it is better to risk and fail at something that resonates deep within than to do nothing”. To which I replied: “That’s the difference between external failure (proxy) and internal success (actual metric to consider).”

[^2]: This is not (only) a repetition of Goodhart’s law. Goodhart focused on people gaming the system once a regulator introduced a policy. My heuristic is more general and works in single-player scenarios too. It is because the easiest way to improve an unweighted metric is often to include items whose weight towards the ultimate goal is lower than the past (e.g.: in the example in the text, the easiest way to improve the number of followers is to attract those who won’t buy anything).

[^3]: As far as I know, Marshall Goldsmith made the expression famous, in his homonymous book.

[^4]: Living a diverse life means acknowledging that because of the problems of addiction and tolerance, pursuing a single proxy will yield diminishing returns over time and lead to dissatisfaction.

[^5]: Did you notice any similarity between this list and the contents of Nassim Nicholas Taleb’s Incerto? That’s because the Incerto is, too, about how to spot and get rid of proxies. Fooled By Randomness is about spurious correlations between proxies and real metrics; The Black Swan is about frequencies used as proxies for impact; Antifragile is about averages used as a proxy for distributions; Skin In The Game is about incentives (and proxies are incentives).