Justifying the High Salaries of Early-Career Professionals

The following are anecdotes of a typical work schedule for young professionals in established, tracked professions.

Following these profiles, I provide explanations for why young professionals command such high compensation, relative to what their work product would indicate.

Adam: SWE at a gaming company

Adam has been a SWE for four years. He first started coding when he was a young boy and quickly found that he had a knack for solving puzzles. He always loved video games and was excited to learn that he could have a lucrative career that included programming the very games he enjoyed growing up.

His day consists of pushing updates to backend servers in Go and writing relevant Typescript client code. Most problems don’t require much brainpower, meaning that he can push a change and spend the next 30 minutes on TikTok. Typically, when he refocuses himself, he finds that he one-shots the problem and moves on to the next problem. A good day would be merging a couple of PRs and some friendly Slack banter.

Adam has compounded his skills over the years, thanks to a strong culture, well-defined tasks, and a competent manager. He has a good work-life balance as he is able to finish projects quickly, though most do not even have hard deadlines. He makes sure to not work too fast or set expectations too high. This is an implicit learned behavior from his boss, who is also competent and not incentivized to ask for or create more work.

On average, Adam puts in 0-10 hours of deep work a week. The rest of his work hours are spent mindlessly coding, listening in on various meetings with his camera off, and on TikTok.

Adam went to a large engineering school. He was much sharper than his fellow students and didn’t have to work too hard to get good grades. He leveraged his connections and grades to eventually work at the gaming company he’d always dreamed of.

His typical week includes merging a couple of PRs and periodically managing a few interns. He generally prefers to work alone. He is conflicted about whether to go the IC route or the manager route. He’ll probably go the manager route because his manager told him it is the path of least resistance.

Adam thinks AI and AI-adjacent tools are crutches. He does not use Twitter.

Brenda: Writer at a marketing firm

Brenda is a writer at a marketing agency, helping top brands with positioning and providing materials for advertising campaigns.

Brenda works in a hybrid setting, working from the office three days a week. She likes the hybrid split as it enables her to see her peers and collaborate more effectively while allowing her to take it easy on Mondays and Fridays.

A standard week typically includes writing an internal memo and reviewing peer’s assignments. Some weeks are more skewed towards her individual contributions, writing out full reports and sometimes presenting the result. These reports are sometimes fully internal facing while others are external to clients.

The clients love Brenda – she is young and in tune with Gen Z culture. She offers unique insights like “Instagram DMs are out” and “Being cringe is cool”. Her boomer clients run every piece of marketing material by her to avoid the never-ending cultural landmines and to be perceived as cool.

Brenda went to a good school, with many friends working in similarly prestigious positions across various industries. She takes frequent bathroom breaks to catch up and react in her five active group chats.

Likely future career paths include climbing the corporate ladder, working at a client’s company, or going to graduate school.

Carl: Strategy Consultant at a Big 4

Carl is a consultant at a Big 4 firm. He has worked on two projects during his first year as a consultant.

His first project was not very demanding, with vague deadlines as the product was still years out. Carl took advantage of the additional time afforded to him by meeting other people at his firm as well as networking with the client in person. This proved to be very helpful as Carl is responsible for finding his own projects so that he is not idle and riding the bench.

He networked his way onto his second project, which is somewhat more demanding. Some days he has to get to the office at 9 and works until 7.

Carl often asks himself what his real skills are. Most of his work is produced by some combination of AI tools including ChatGPT, Claude, and Perplexity. Deep Research has been especially useful for creating well-written scripts that he can read off during virtual presentations. He happily pays for these tools out of his paycheck.

Carl’s company issues him a work laptop, which soft-prohibits AI tools. Most of his day includes prompting Claude on his phone and typing the results from his phone to his work laptop. He prefers to work at home so he can use his second laptop, making copying easier and enabling him to have a YouTube video in the background.

Carl’s most difficult decision is deciding which burrito to order for lunch. He excels at navigating cultural contexts and is now fluent in corpo-speak. He always makes sure to align on strategic north stars and leverage whatever framework is in vogue.

Carl has his eyes set on getting an MBA. It's both what he wants to do and what his parents, managers, and friends unanimously recommend. He is in talks with his company to see if they can pay for business school.

Adam, Brenda, and Carl are archetypes of co-workers one would encounter in a prestigious post-college environment in cities across the US. In fact, they are some of the most competent co-workers one might encounter in the corporate world and represent the top ~5% that society has to offer.

In any major city, compensation for these roles typically ranges from $100,000 to $300,000. We know that we have gotten better at running The Sort, matching individuals to occupations where they can maximize their productive potential, as measured by income. However, it is highly unlikely that individuals are producing work output commiserate with their salaries from an efficient labor market perspective.

The following are possible explanations of why young professionals command such high wages:

1. The productivity of outlier employees covers everyone else and they don’t negotiate higher salaries for themselves.

Assume Adam, Brenda, and Carl are your typical employees, each being a 1x employee. Each company has a small percentage of employees that are 1000x more productive and do all the work. The company can not determine ex-ante which person is a 1x or a 1000x employee.

1000x employees are present in all companies and do not negotiate for higher pay or leave.

Furthermore, in post-product-market fit companies, it is difficult for any individual contributor to make a meaningful difference to the bottom line. The barriers to basic maintenance of the product typically do not hinge on a select few, and companies are incentivized to structure their companies such that this is not true.

Compensation impact: Low

2. A single breakthrough covers everything.

A worker comes up with the idea of a widget that increases internal productivity 1000-fold or creates a new product that everyone wants. The firm asymmetrically benefits from capturing the economic value of this breakthrough and does not compensate the employee proportionally to the value they’ve created.

You don’t know who will do this ex-ante (and neither does the employee) so you have to pay everyone an inflated salary to attract the innovator.

Compensation impact: High in select industries, low otherwise

3. Talent is finite and firms are paying everyone they can so someone doesn’t start a competitor.

Every person implicitly decides whether to work for your company or start a competitor. If they start their own company, they have an X% chance of starting a company that puts your company out of business in 10 years.

Your company believes that people can be financially persuaded to work for you and not start their own company, even if it is economically rational for the person to do so. Risk aversion and expected utility exist, and you take advantage of this.

You’re happy to offer higher salaries across the board to reduce the risk that talented employees might leave to start competing businesses.

Compensation impact: Medium-high in tech/select other fields, low otherwise

4. Firms are very concerned with mitigating downside risk; high salaries are a form of insurance.

The worst employees impose a large negative equity value on the firm. This can be through pushing a change to production that nukes your product, incessantly distracting your earnest employees, or acting inappropriately with clients.

You systematically pay a premium to hire better employees who command higher wages. The people that you hire are on average less likely to carry out negative equity value events.

This model would explain most of the difference in salaries between a worker based in the US and India in an increasingly globalized world. While the work between a US and Indian employee is of similar quality for the vast majority of cases, US workers are more contextually competent and less likely to initiate these value-destroying events.

Compensation impact: Low-medium

5. Society wants to maximally incentivize people to join the elite labor force to find the next generation of new elites.

The greater the monetary delta between a low-skill and a high-skill job, the more people are incentivized to pursue the high-skill profession. In a world where everyone gets paid the same regardless of their profession, nobody has any incentive to work harder to get a high-skill job and befriend other elite talent.

The labor market works decently well at finding talented, ambitious people over long time horizons. It’s a sorting mechanism for finding, developing, and unlocking ambitious high-productivity talent.

Adept high-skill workers will outcompete their counterparts and accrue more capital, on average. Capital is one of the main determinants of power, and this is the best way to allocate financial power.

Firms would have to implicitly agree that this is a collective action problem worth paying a premium for. Coordinating this scale would be nearly impossible without defectors who would reap the benefits of larger profit margins.

Compensation impact: Low

6. Firms are one of the many actors complicit in a systemic status subsidy scheme.

Higher education is a complete sham and elite human capital does not exist. People in positions of power across industries are working together to keep the scheme going, financially for educational credit repayments and socially for elite formation.

Society has to justify the investment of 20+ years of education and we have determined it is better to cover the scheme up. People need to feel a sense of self-actualization and fulfillment that this scheme provides.

Firms knowingly add a premium to workers’ wages, increasing costs, and lowering profits to perpetuate the scheme. While this may occur in some niche, protected industries, it is unlikely that this is occurring at scale.

Compensation impact: Medium for specific jobs, negligible otherwise

7. High wages are the preferred intergenerational wealth redistribution mechanism.

High salaries for young professionals allow educated elites to maintain cultural capital while preventing social unrest that might result from more obvious inequality.

These jobs provide high enough compensation to sustain consumption-focused lifestyles without requiring genuine adult responsibility or productivity, keeping otherwise unproductive young professionals politically and socially compliant. UBI is already here, it’s just not evenly distributed.

While high wages help obfuscate inheritance mechanisms to perpetuate the illusion of fairness, this is likely not happening on a global level. A firm could easily decide not to pay the premium and hire similarly competent individuals.

Compensation impact: Negligible

Exercise for the reader: Which of these compensation rationales are durable in the context of AI?

Clinton Foreign Policy, $TRUMP and $MELANIA, and the Foundations of the Internet

This post is about how relationships, emotions, and incentives drive real-world outcomes over reason, ethics, lawful behavior, and market forces.

Foreign policy is guided by sex and approval

In 1995, Bill Clinton had a very public affair with Monica Lewinsky. In response, Hillary Clinton did not speak with Bill for many months due to the affair and the second-order effects of his infidelity.

The re-commencing of their relationship and the eventual forgiveness by Hillary is claimed to be traced back to her strong-arming her husband to bomb Serbian villages: [1]

Bombing Serbia was a family affair in the Clinton White House. Hillary Clinton revealed to an interviewer in the summer of 1999, “I urged him to bomb. You cannot let this go on at the end of a century that has seen the major holocaust of our time. What do we have NATO for if not to defend our way of life?” A biography of Hillary Clinton, written by Gail Sheehy and published in late 1999, stated that Mrs. Clinton had refused to talk to the president for eight months after the Monica Lewinsky scandal broke. She resumed talking to her husband only when she phoned him and urged him in the strongest terms to begin bombing Serbia; the president began bombing within 24 hours. - Source

The primary source here is shaky at best. But is something like this really beyond the realm of possibility for one of the most ambitious and socially intelligent Western female leaders with a long history of hawkish foreign policy tendencies? Hillary’s love language could very well be acts of war.

Founding stories are a psyop

Early-stage startups run on secrets and secrets often spread like wildfire. NDAs are only as good as the ability to enforce them. Your favorite application (Facebook, pump.fun) has a much more complex founding story than is publicly available, likely with some questionable espionage-esque behavior as a core propellant to reaching their heights.

Most participants understand this social contract and end up contributing and extending in-group dynamics. This includes connected individuals carefully crafting narratives for public consumption.

The founding stories of successful companies including Paypal, Flexport, and Notion are well-documented and leveraged as lore to attract customers and prospective employees. How much of these stories reflect reality versus a curated Girardian story to persuade others of their divine purpose?

Verkada God mode

Verkada is a security camera company founded in 2016 and is currently valued at $4.5 billion. They offer a full-service physical security solution to institutions, installing and managing the logistics of their security camera operations.

Clients include the Los Angeles state government, prisons, Tesla factories, Equinox, healthcare systems, and leading biotech firms.

It was reported that Verkada has a God mode – exposed by hackers – enabling anyone with the password to access every security camera in the Verkada network. As is typical in startup land, shortcuts were taken, and God mode was gated by a single hard-coded secret with rudimentary security practices. [2]

Trump and Melania memecoin launch

At midnight of January 18, during his inauguration ball, Trump released an official memecoin. The token achieves virality in hours, reaching a total valuation of over $70B. Trump re-ignites himself as the main character, kicking off his upcoming term with a soon-unlocked infusion of financial capital, and once again cements himself as the most powerful man in the world.

Melania, who cannot stand her husband on a personal level, and is driven by envy that her husband is one-upping her, decides that she wants to launch her own memecoin. She gets in contact with one of the most extractive token-launching cabals and launches $MELANIA 43 hours later.

She then delivers the knockout punch to cement her social dominance: a retweet from the president’s official X account. This legitimizes her token, and more importantly, transforms her persona from the socially submissive tradwife to a culturally adept individual who demands our respect in the attention economy:

Tweet

Within days, billions are extracted from retail participants worldwide – including via siphoning liquidity from Trump’s own token – by insiders to satisfy Melania’s insecurities. [3]

What should we be cynical about now?

Embryo selection for the powerful is underway

One can make a good argument that universities, institutions, and churches are wrappers around assortative mating. The incentive stems from many traits being highly hereditary.

Assortative mating – i.e. picking a partner – has historically been the only lever you can control. However, with the assistance of modern medicine, you can take this one step further with embryo selection.

Embryo selection and modification are likely already well underway today, but it is hard to determine the extent and state-of-the-art technical capabilities. It is typically categorized into two groups: disease prevention and enhancement.

Disease prevention is concerned with eliminating the likelihood of negative qualities that affect quality of life (e.g. HIV) and traits that typically put a strain on the public welfare system. This is generally less controversial of the two.

Enhancement means specifically selecting for or modifying genes to increase traits such as athleticism and IQ.

When one of the leading experts is ostracized for ethical transgressions, this should provide some clues that incentivize powerful groups to at least understand the technological capabilities.

Is this something Elon would consider? How should we model the next generation of powerful kids against the empirical evidence of some level of mean reversion in intelligence and ambition amongst families?

Elliptic-curve cryptography has always been broken

Elliptic-curve cryptography (ECC) underpins much of the internet today including public-key cryptography, digital signatures, and pseudo-random number generation.

Government, Russia, Mathematics as Propaganda, and other resources can all be used to piece together a more likely origin story for the foundational primitives and incentives of the early internet.

Bitcoin

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The world is a museum of passion projects, stewarded by the powerful to serve their wants and needs. It has never been better to be a billionaire or similarly powerful person.

As a recovering efficient markets enthusiast, the base case that you are being adversely selected against by a group of well-connected and smart individuals is a good assumption in theory but incomplete and naive in practice. [4]

The truth is closer to: reality is path-dependent, messy, littered with incompetence, and guided by human relationships and emotions.

[1] The whims of the powerful are now felt worldwide via mechanisms including cryptography and drone strikes.

[2] Uber had a similar well-documented God mode, paying a paltry $20,000 fine for a tool used to spy on reporters and key individuals in a position to negatively affect the company.

[3] This is not meant to imply that Melania has unique insecurities but rather she has her own ambitions and desires to be viewed as a certain kind of person.

[4] Powerful individuals are increasingly interconnected. Previously, this meant physical colocation, living in the same country club, and frequenting the same events. Now, the world runs through networks of individuals who aren’t necessarily co-located, aligned by ideologies or shared goals. Group chats rule the world.

There’s a graph from Tim Urban that I think about often:

It never ceases to amaze me that you can literally see all the weeks of your entire life on a single sheet of paper. You have a very finite number of weeks in your life. [1] Every decision matters.

Time is the one scarce resource that affects everyone equally. Regardless of your background or socioeconomic status, everyone plays by these same constraints. [2]

However, reality is even more pernicious than what this graph shows. As you cross off each week of your life, you falsely believe that you are operating in a linear regime where each week is an equal proportion of your perceived life. In reality, your perception of time in life is better modeled on a logarithmic scale rather than a linear one.

At age 5, one additional year is another 20% of your life. At age 50, one additional year is only 2% of your life.

While our perception of time is not perfectly logarithmic, talking to people older than me leads me to believe that this heuristic is at least directionally true.

What should we do about this? How can we maximize our ability to get what we want in our lives?

Career implications

As early as possible, you should develop a thesis for what you want to do given your risk profile, work/life balance, and skillset. Your thesis can and should evolve as you grow older.

Intelligence is getting what you want out of life, and most people complain they aren’t getting what they want without any evidence of even a modicum of effort. You can get ahead of basically everyone in any field by putting in an ounce of effort. No one is even trying.

Don’t spread yourself too thin, but realize that there are unexpected returns to being a polymath and deriving cross-pollination insights. Choose 2-3 areas to do ten times as much in life. Deliberate practice over 2-3 areas for even a few weeks will put you at a massive advantage over the vast majority of the population. Compounding is still greatly underrated in practice, even though everybody knows about it.

Assuming you have some basic education, you can learn most things rewarded by the free market in a very short period of time. Most people dramatically underinvest in “temporal leverage points” – where small investments of time can radically alter the trajectory of your life. Examples include: spending time really understanding how the talent system works in your given industry, learning the basics of probability theory, having lunch with someone 30 years older than you in your field, or starting a podcast. All can be done within a week with unbounded upside.

If you’re reading this, you’re likely stressing too much about exactly what you’re working on. There is such a thing as decision paralysis. Anecdotally, it’s much more important to be able to let the compounding effects occur and reach the frontier of a given field than to always be jumping around and never coming close to the frontier.

Personal life implications

The standard YOLO advice about seizing the day fundamentally misunderstands time perception. The real arbitrage opportunity is doing things that seem boring to others but have massive long-term returns. Learning Portuguese or exploring the Dark Forest on a new chain might seem like wasting your precious weeks, but these detours can yield the highest returns through unexpected recombinations.

Most arguments boil down to different time preferences. Understand your temporal discount factor and find others that match it.

By age 18, you will have spent 93% of the actual time you'll ever spend with your parents. On a logarithmic perception scale, you’ll have experienced 98-99% of your perceived time with them.

Location decisions become increasingly sticky as we age, as social and professional roots grow deeper. The optimal time to experiment with living in different cities or countries is often earlier in life when our perception of time is more expansive (and our commitments are more flexible).

Hobbies and personal interests should be cultivated deliberately, as they often provide the texture and meaning that make our finite weeks feel richer. Starting a creative practice or learning an instrument at 25 means you could have decades of enjoyment ahead, while the same decision at 45 comes with a different psychological weight.

Health investments made early can have large exponential returns. The good habits we build in our youth compound over decades.

[1] I have seen no evidence that immortality efforts such as Bryan Johnson’s will increase your lifespan by more than ~20%.

[2] Sure, billionaires can buy time by flying private, having personal chefs, etc. but they still age at effectively the same rate as the rest of us.