The books Four Thousand Weeks: Time Management for Mortals and Wanting: The Power of Mimetic Desire in Everyday Life are two new-ish "self-help" books that seem designed to be read together, or at least with awareness of each other.

Both books are written by men who have attempted, in different ways, to "win" the rat race but instead suffered various kinds of setbacks that led them to question the track they were on, pivot, and then publish books about it.

The author of Four Thousand Weeks is Oliver Burkeman, a US-based British writer and productivity guru who had a column at the Guardian for several years called This column will change your life (hopefully ironically self-aware). Burkeman's attempts to "master his inbox" and his schedule led him to the discovery that these pursuits left him burned out and unfulfilled. This further led him to exploring his relationship with time and how he spent it.

The author of Wanting is Luke Burgis, an entrepreneur-turned-social-theorist. Burgis' big pivot happened when the big deal that was going to change his life forever (the sale of his company to Zappos) fell through, after which he experienced a crisis of meaning. He lost the will to go on fighting for the life of his business, and realized that the things he was pursuing were not rich with meaning for him, but rather goals that he had seen modeled for him by influential people around him.

Both these books are oriented around the idea of "meaning", in the sense of "doing something meaningful with your life". Burkeman's attention is focused on how to live and work in ways that imbue life with meaning, and how to accept the fact that we can't do it all, or even very much. Burgis is focused on discovering meaning, which he calls "thick desires" (juxtaposed with "thin desires", which are shallow and unfulfilling). Burgis orients this exploration around the work of Rene' Gerard on "mimetic desire" (desires that come from comparing ourselves to others). Together, these books would seem to offer a full solution to the problem of modern life: here's how to (a) discover what's meaningful and (b) spend your time on those things.

Lurking underneath the advice in these books is a tacit understanding that meaning is constructed, i.e. that the importance of things is not inherent but rather assigned. The process by which things become meaningful is really interesting. It's both conscious and unconscious. Our experiences, especially in childhood, shape our definitions of meaning in unconscious ways, and our analytical minds shape them in more conscious ones. For example, something that is meaningful to me is the idea of "fatherhood". I now have a whole set of cogitatively-derived beliefs that enforce something that, before, I just felt intuitively. Somehow fatherhood has always seemed like a meaningful pursuit. Now I have a bunch of natalist beliefs that back up that intuition.

(Quick note: I'll be using "models" in the sense that Burgis uses it, which seems to also be how Gerard uses it. In this sense, a model is someone we use as a source of inspiration or goal-setting. In the "keeping up with the Joneses" setting, we are using the Jones family as our model.)

It seems clear that the primary architects of meaning have changed over time, from the family, the neighbor, the tribe, the wise elder, to the clan, the church, the temple, the king, to the theorist, the state, to the talk-show host, the entrepreneur, the social media influencer. We live in a time in which many of the traditional architects of meaning have been discredited, and in which there are many potential new sources of meaning. To an extent greater than ever before, meaning creation has become monetized, and the method of delivery is more immediate and omnipresent (our phones). In the constant arms race of propaganda/advertising and our resistance to it, businesses and performers have gotten really slick, and there's a wider body of models than ever before. There are also more things we can do with our time than ever before, and we have access to a wider family of possibilities than we've ever had before. Late stage capitalism has given us an enormous menu of possibilities. Social media has flattened many of our relationships into followed-follower dynamics, such that we see extreme outlier behavior and outcomes as more proximate. Moreover, unprecedented freedom of choice and our belief in a meritocracy (legitimate of not) has made it easy to internalize a feeling that if you're not on of the edge, not part of the happening, then you and your work don't have value. Thus, if you're plugged in, it's easy to lose yourself and become completely overtaken.

But, like a cult member who realizes the cult founder is a self-interested psychopath, or like a grizzled veteran realizing that the war is all a sham, we are occasionally awoken to the shallowness of our models and the thin-ness of our desires (Burgis' term). It turns out that diving deep into any one thing means forgoing a thousand other things, and that running in all directions at once results in going mostly nowhere, and that pursuing the vision of a unprincipled leader leads to moral morass, and that basing your personal growth on all the trends of your time leads to deep feelings of inadequacy.

This has led some, especially in my age bracket and older, to deliberately opt out. Frustration with the toxicity that is so prevalent online, and suspicion of the perverse incentives that make up the business models of modern media platforms, have led a number of my peers to unplug. There's a widespread distrust of the dominant models, and a retreat into more traditional forms of meaning creation: family, community, etc. There's a deliberateness about this that is really attractive to me. I recall the example of Donald Knuth, a famous computer scientist, who is well-known for forgoing email (and presumably most other forms of digital connectedness), as made famous in Deep Work by Cal Newport. This intentional retreat from the happening gives us an opportunity to discover our own sources of meaning, and to cut ourselves off from the things that distract us from that. It also seems to be the key to living a satisfying life.

But...

There's something that bugs me about he advice of "cut yourself off and you'll be happy". Perhaps it's just my extroverted brain, but there seems to be immense value in staying at least somewhat connected to the churn of one's times. Even if one's goal is to spend as much time "deep working" or "flow-state-ing" as possible, doing so successfully would seem to require that you're at least aware of the context that surrounds you, unless you're independently wealthy or otherwise unconstrained. In our society, it is only when our work is correlated with value creation for others that we are given "permission" (by financial circumstances, successful grant applications, tenure status, etc.) to continue grinding at our groove. If our work is totally uncorrelated with the spirit of our times, then the circumstances associated with that work are poised to be quite strained (think Van Gogh or Kafka, both famously poor and unhappy, the latter of which is used as an example in Four Thousand Weeks).

Both of these books get this. They aren't recommending that you cut yourself off to become a monk or farmer, or that you quit your stable job to become an artist. What I appreciate about these books, especially Four Thousand Weeks, is that they're modest. Ultimately, they encourage the reader to think deeply about what moves them, to do their best to distances themselves from the things that don't -- to not be distracted by the things that don't, and to simply focus a bit more on what is meaningful.

I haven't written very much about the actual content of these books here. Both are worthwhile. Four Thousand Weeks is much better overall, a more perfectly sculpted set of ideas. I really loved some sections, and I'll share some quotes:

"Once you truly understand that you're guaranteed to miss out on almost every experience the world has to offer, the fact that there are so many you still haven't experienced stops feeling like a problem."

Wanting had a few vignettes that I struggled with (specifically: one really long involved metaphor involving a toaster and a swimming pool to illustrate the scapegoat mechanism made me totally zone out), but then other moments felt revelatory (specifically: I loved the recommendations for how to identify "thick desires" and core motivations).

Both are written for a distracted generation, and both are pointed in the direction of helping their readers be more self-aware and more intentional, which is doing right by me.

With so many intense emotions at work and important decisions in the balance, interviews are one of the areas where our natural biases can be most exposed. To pull some terminology from Thinking Fast and Slow, short-term human-to-human interaction can be rife with System 1 thinking (quick judgments based on heuristics) instead of System 2 thinking (methodical deliberation). In fact, there are names for the types of biases that might emerge during an interview, including Confirmation Bias, Optimism Bias, the Halo Effect, the Regression Fallacy, and many others. If we think back to interviews we’ve been a part of (on either side), I’m sure we can recall instances where these biases were at play.

In addition to our (completely and forgivably human) tendency towards bias, we also must recognize that interviews are an environment of high variance. When a candidate is preparing for interviews, especially technical interviews, they’re making guesses on which topics to review and how to prepare. They may have a rough idea of what will be covered, but the chance that they’ve set up time to master the specific topic of any particular interview is pretty low. Moreover, anyone’s confidence with how to proceed on a given question is subject to the specific context of that question. For example, despite the fact that a technical question ultimately just amounts to arithmetic, one’s ability to realize that might depend on how the question is set up, whether they fully understood the question as asked, and also whether they understand arithmetic. As a result, a candidate’s performance might be highly dependent on the specific circumstances of that question, of that interviewer, of that time of day, etc.

Finally, the interview process is a matter of estimation. An interview day usually involves interacting with four to six interviewers, each asking a different set of questions and potentially evaluating against a different set of expectations. So what’s the right way to combine these evaluations into an overall decision to hire or not hire? How should one balance the candidate’s stellar performance in one person’s interview against the lackluster performance in another? What is the appropriate way to weigh each interview to reach the best decision?

Finally, if we zoom out, we can see that the goal of the hiring process is* to maximize the probability of hiring highly competent people, while minimizing the search cost and the probability of mistakenly hiring incompetent people, all while being humane and fair.* This is a constrained optimization problem.

Hopefully I’ve been able to show how interviews involve challenges pertaining to bias, variance, *estimation, *and optimization. Naturally, this is a case for some data science thinking :) Let’s consider how we can design an interview process to take on these challenges.

Core Skills

First and foremost, what are we hiring for? What does it take to be good at the job? Answers to this question can often start out quite vague — a project coordinator needs “to interface effectively with stakeholders”, while a project director might need to “manage a complex project with many moving pieces”, while a software engineer needs to “write performant software”.

It’s useful to break these high level ideas into their lower-level components. To do that, think about what this person will actually be doing on the job. What does “interfacing effectively with stakeholders” really require? It sounds like it might involve persuasive and logical writing, public speaking, and the ability to negotiate effectively between competing priorities without offending anyone. Similarly, “managing a complex project” involves having technical expertise in the project area, an ability to effectively order dependent processes, and an ability to forecast and design systems of redundancy for when things go awry. Finally, “writing performant software” involves knowledge of a computer language or framework, a familiarity with software architecture, an ability to debug and troubleshoot, and an ability to implement efficient solutions to technical problems.

For each of these examples, the breakout into specific components represents an effort to identify and define the core skills associated with the role. For every role or title, the hiring manager should have a sense for what the core competencies are for the position (the “principle components” if you will) and design a body of interviews to test these core competencies.

Ideally, these core skills should be “orthogonal”, meaning that they are independent from each other. For example, being a persuasive writer is different from being a persuasive speaker, and any individual might exhibit a high level of competence at either, none, or both of these skills. Similarly, knowing a computer language is very different from knowing about software architecture, and while most candidates who have knowledge in the latter will also have knowledge in the former, it is possible for that not to be the case. This orthogonality is desirable because it allows for more independent measure of performance in interviews, as explained in the next section.

Core skills should also be “atomic” or “modular” in the sense that they represent a low-enough level representation of a skill that it can effectively distinguish between different roles. What that means will be different company to company. More specialized roles might have a more specialized definition of core skills. Despite a high area of overlap, a “Psychiatrist” job is different from a “Child and Adolescent Psychiatrist”, and has a slightly different set of core skills. It’s my recommendation that one not get too specific with such distinctions until the context requires it, which most frequently happens in academia and medicine, where organizations set out to hire specialists in very specific domains, but can also happen in the technology industry.

As part of identifying a definition of core skills, we should recognize that, even within the same profession, different practitioners might have varying levels of expertise across the skills associated with it. Moreover, some skills might be more essential to effective performance than others. For example, while I certainly prefer having a surgeon that is both kind and competent, it is far more important that she be competent. So, along with having a definition of core skills, we should give weights to these skills when defining a given role, and also develop a scale for measuring competency. My favorite scale is that of [Novice, Beginner, Intermediate, Advanced, Expert].

• Novice — Knows the existence of a concept

• Beginner — Knows how to define a concept

• Intermediate — Knows how to apply a concept

• Advanced — Knows how to teach a concept

• Expert — Knows how to adapt a concept for any scenario

Below is an example of some of the core skills we might want to assess, and how we might weigh them, for the roles mentioned earlier. You don’t need to agree with the weighting shown here. Hopefully your team can develop its own definitions and systems.

Project coordinator

• Ability to write persuasively and logically High priority

• Ability to speak persuasively and logically to a group Medium priority

• Ability to adroitly negotiate tradeoffs, i.e. prioritize High priority

Project director

• Technical expertise in the project domain High priority

• Ability to plan execution and account for bottlenecks High priority

• Ability to design redundant systems, and forecast Medium priority

Junior software engineer

• Competency with a computer language High priority

• Knowledge of software architecture Medium priority

• Ability to debug Medium priority

• Ability to design and implement efficient solutions High priority

This framework is applicable to any profession, except perhaps those that don’t rely on skills but rather on one’s network or relationships. The “network effect” (knowing the right people, or having the right people vouch for you) can become a major contributor to one’s professional success. This makes sense, as the ability to recruit or lead other competent people can depend on having a good network and reputation. In the best scenarios, this is the result of building a community of advocates based on a history of competence and good judgement, but it’s easy for it to become a shortcut for making heuristic judgements, like someone being hired based only on being connected to powerful people (which is how many of the new-grad sons and daughters of politicians and celebrities get hired).

In the absence of something like the core skills framework, it is natural for two things to happen. First, people tend to interview only along their own areas of competence and familiarity, which is not always what the job will require. Second, in the absence of clear criteria, people tend to retreat into likeability assessments, gut feels based on how they felt during the conversation with the candidate. These types of judgements are unreliable.

Designing Assessments and Interviews

So we’ve done the work and identified the role we’re hiring for and defined the core skills associated with that role. Now we want to create a set of assessments that measure candidates’ competencies in these areas.

Let’s recall the overall goal of the hiring process: to* maximize the probability of hiring highly competent people, while minimizing the search cost and the probability of mistakenly hiring incompetent people, all while being humane and fair*

Hiring competent people requires, first and foremost, that we are able to assess competence. Avoiding hiring incompetent people means that we must set criteria around those measures of competence. Minimizing costs means that we make sure people’s time is well-spent (potentially biased based on whose time is more costly). Being humane and fair means that we treat everyone with kindness and respect and that we commit to constantly improving and debiasing the process.

Designing a panel

Each interview in a panel should be grounded in our definition of core skills. If we find ourselves defining an interview unaffiliated with at least one core skill, then we should take a look at the interview or the core skills to find out why they don’t align. Neither the candidate or interviewers should be burdened with interviews focused on things we don’t care about, and even “behavioral interviews” should be oriented around an underlying competency we are attempting to measure.

First, an aside.

Many companies have behavioral interviews checking for “cultural fit”, a notoriously fraught and difficult-to-define concept. These interviews often end up being likeability tests or strange “belongingness” checks, which are where a lot of biases (both conscious and unconscious) can show up. The way to resolve this is not to abandon the idea of cultural fit, but rather to be explicit about what is meant by it. If fluent communication in a language is going to be important, then make it explicit. If direct delivery of bad news is important to your organization, then find a way to evaluate a candidate’s decision-making process when presented with competing incentives. If the position involves interfacing with a group of Ivy-league investors who are temperamental and judgmental, then it might make sense to check if candidates can stand up to the kind of “status checks’’ that they’ll be subjected to on the job. If profanity or high levels of informality at work is a part of your company’s culture, then define that explicitly. Depending on the position, these more amorphous qualities can in fact represent “core skills”. Making them explicit can remove much of the bias commonly associated with testing for cultural fit. On the other hand, if you find that your efforts to be explicit about cultural fit direct you to definitions based on immutable characteristics or legally protected categories (such as race, sex, age, religion, etc.), then that’s a warning sign that you probably need to adapt your company’s culture to be more inclusive.

Back to interview design.

Somewhat counterintuitively, we don’t actually want to use each interview to cover just one core skill. Ideally, each interview should cover at least two, and the whole panel should provide overlapping coverage across the entire set of core skills. The reason to do this is two fold. First, when you measure something more than once, you reduce variance in the measurement. Second, getting independent measures allows for even better estimation, and over time also allows for you to measure and control for the biases of any particular interviewer.

Another thing we want is for our interview results to contain lots of information, in the technical sense. Consider an interview in which the candidate was asked to find the result of a simple math problem: 2+2. The pass rate would be about 100% and a candidate passing wouldn’t tell you anything about their skills. Similarly, imagine an interview in which the candidate flipped a coin to determine whether they passed or not. The results of such an interview would be about 50%, and the results would still be meaningless.

The problem is that these assessments do not discriminate between high and low performers. And while these examples are extreme, many real-life interviews also suffer from this problem. Assessments should reveal a lot about the candidate in relation to the core skills they’re trying to measure. They should be* deep and adaptive*, allowing us to accurately measure a candidate’s performance on the whole spectrum of expertise (from Novice to Expert). That means that, as opposed to merely testing for basic proficiency, a good assessment should give the candidate an opportunity to impress the interviewer by pushing the boundaries of expertise in the domain. This can be done by creating questions with extensions that can be brought into play if a candidate is performing well. This makes the interview adaptive, allowing a deeper measure of the candidate’s competency in a specific domain if the candidate is ready for it. Through this, we can create assessments where “high performance” is a meaningful indicator of real expertise, and where we also have meaningful information across the gradient of low, medium, and high levels of expertise.

Testing and calibrating

To do this effectively, the interview panel needs to calibrate effectively on what is a good question and how that question should be graded. Creating good assessments is a challenging process. As the sections above indicate, it requires careful consideration of core skills and the design of how to test those skills in a deep and adaptive manner.

Once an assessment has been designed, it should be tested. If you have time and a team to help, the best way to do this is to do it internally, within your team, first. This involves giving the assessment to colleagues and calibrating performance expectations around their results. This is great, but many companies don’t have time for this level of process, so most calibrating happens “in the wild” with real candidates. This calibration process might be regarded as the “learning phase” of the assessment. If every candidate is knocking your interview out of the park, then you might need to add some extensions to get a better read on high-performing candidates. Similarly, if only a small percentage of candidates get even part way through your interview, then it might be better to reconsider how rapidly the interview progresses into advanced content. Remember, the goal of an assessment is to reveal information, not to stress someone out with difficult brain teasers, and not to make someone feel smart.

There’s a bit of a caveat here, because aggregate candidate performance on a given assessment will depend not only on the calibration of the interview, but also on the distribution of skills among the candidate pool. For instance, on-campus recruiting or recruiting directly from training programs will result in a candidate pool with a certain set of biases (usually great theoretical knowledge and very little practical knowledge), while targeted recruiting of people with more experience will lead to an interview pool with a significantly different distribution of skills. It’s important to be mindful about such differences, and potentially consider that when designing assessments. If you feel confident in your assessments but find there’s misalignment between the expected and actual performance of candidates, you should consider a new recruiting strategy.

Making a decision

So, you’ve got a definition of the role in terms of core skills, a set of assessments that you feel confident in, a group of calibrated interviewers to help conduct the interviews, and a pool of promising candidates to evaluate. You’re almost there! The question remaining is how to make a good decision about hiring or not hiring, and the associated questions of seniority, salary, and so on.

Once we have estimations of a candidate’s proficiencies across all of the core skills, we can make a decision. Recall that, in our definitions of the role in terms of core skills, we gave ourselves the leeway to weigh different skills differently. Similarly, a candidate’s performance across the skills may not be equally distributed. They might be “spikey”, where the candidate has high performance around a specific domain but lower elsewhere, or they could be more “well-rounded”, exhibiting Intermediate or Advanced proficiency across many skills, but not Expert in any. Both might be appropriate for the role under consideration, depending on how we weigh the importance of each skill.

Despite the fact that it may seem that only two decisions (try to hire, don’t hire) exist for a candidate at this point, there are in fact many more gradations. The company can shape its decision — in terms of salary, title, leveling, etc — to account for different levels of interview performance. Another advantage of the core skill definitions is that it allows for reasonable benchmarking based on current team members.

Given the two candidates above, how do you make a decision? Different companies have very different rules on that. In the The Hard Thing About Hard Things, Ben Horowitz strongly recommends keeping final hiring decisions in the hands of the hiring manager. On the other hand, some companies practice majority or consensus models, where the entire hiring committee needs to be a “yes” on a candidate for an offer to be made. In most cases, I recommend something like the majority model, with some caveats.

There are a few reasons for this:

• First, if you’ve thought deeply about the core skills and designed a good interview process, you should be able to trust the hiring panel to make good decisions.

• Second, it’s best when your colleagues are excited about a candidate joining the company, and not have resentment or misgivings. Hiring is not just about individuals, but about building teams.

• Third, showing trust in your processes begets trust in your processes. Good patterns of decision-making start from the top. Even though, as the hiring manager, you may feel differently about a specific candidate than the rest of the panel, trusting your team to make good decisions will make them more likely to trust each other.

In summary (TL;DR)

That’s it! You’ve made it. Here’s some bullet points to summarize the big takeaways.

• Define core skills for each role

• Make those core skills atomic and orthogonal

• Design interviews that cover at least 2 core skills each, motivated by real-world or close-to-real-world circumstances and constraints

• Interviews should not be gimmicky or arbitrarily stressful

• An individual interview should aim to assess at least one core skill, ideally more than one

• An panel of interviews should provide at least one, and ideally more than one, measure against each core skill

• Decide on a process for making hiring decisions, and stick to it, even when it hurts