The 80/20 rule for your whole life

On building a boring foundation and a laboratory on top

In 2012, I was a junior engineer at Google with an experimental code folder larger than most engineers’ entire code contributions. (Not that LoC is the right metric to look at, especially not these days!) That same year, I owned 110,000 shares of a company called Converted Organics. Total value: $110. One tenth of a penny per share.

These two facts are related.

Around the same time, I was sitting in a room learning Tibetan meditation from a teacher who spoke in long silences. I didn’t know what I was looking for, exactly. I knew I hadn’t found it yet.

The 80/20 principle

In 1896, the Italian economist Vilfredo Pareto noticed that roughly 80% of Italy’s land was owned by 20% of the population. The pattern kept showing up: 80% of effects from 20% of causes. The Pareto principle became one of the most widely cited ideas in business and economics.

A century later, Google formalized a version of it as a management philosophy. Engineers were encouraged to spend 80% of their time on core projects and 20% on self-directed experiments. The policy produced Gmail, Google News, and AdSense. It also produced thousands of projects that went nowhere, and that was fine. The 20% wasn’t supposed to have a perfect hit rate. It was supposed to create the conditions for unexpected breakthroughs.

I used my 20% time aggressively. My experimental folder was enormous. My lines of code, even as a junior engineer, exceeded those of distinguished engineers; not because I was a better programmer, but because I was running more experiments. Most of them produced nothing. A handful reshaped my career.

It took me years to realize I’d unconsciously applied the same architecture to the rest of my life. The brokerage account. The meditation practice. The pattern was always the same: a stable foundation taking up most of the space, with a laboratory running alongside it.

That architecture; a stable 80% with a laboratory running in the other 20%; shaped three habits I’ve built my life around. The habits aren’t brilliant or original. They compound. And underneath all three sits a single principle that keeps the whole thing from falling apart: judge the portfolio, not the position.

The three habits are:

1. Expand your knowledge

2. Master your decisions

3. Build and grow

Here’s how they work.

Expand your knowledge

The most valuable asset you own isn’t in your brokerage account or your retirement fund. It’s the mental model you carry into every decision. That model either appreciates through constant learning or depreciates through complacency. There’s no neutral zone.

The practitioners, engineers, and investors I admire most share a common trait: relentless intellectual curiosity across domains. The deep kind where you follow a thread for weeks, months, and even years because it interests you, with no immediate payoff in sight.

I learned this first in the most personal domain of my life: the search for a contemplative practice.

I grew up moving through phases of Christianity; Protestant, Methodist, charismatic. Each tradition gave me something I kept. None gave me a reason to stop looking. So I kept looking. I took Tibetan meditation classes, read the texts, sat with teachers who spoke more in silence than in words. Then I encountered Theravada Buddhism, and something shifted. The approach was more direct, more empirical. It resonated in a way the others hadn’t.

The years of spiritual exploration weren’t wasted. They were the research phase. Every tradition I moved through sharpened my sense of what I was looking for, even when (especially when) I realized it wasn’t what I’d found. The Tibetan practice wasn’t a dead end. It was calibration: I learned what stillness felt like, which is how I recognized it when Theravada offered a more direct path to it.

The same curiosity-driven approach shaped my technical career at Google. The company had a formal structure for it: 20% time. One day a week, you could work on something outside your core job. Something experimental.

Most engineers used their 20% sparingly. I used mine like it was oxygen.

My first 20% project started because I was curious about public transit data. Singapore had bus schedules in no format Google Maps could ingest. So I ported them: converted the raw schedule data into the standardized format, built a proof of concept, and showed it could work. A small project. Nobody asked me to do it. I did it because the problem was sitting there and I wanted to see if I could solve it.

Then I got curious about structured data inside wikis. I built a Wiki markup parser using lex and yacc, the classic compiler tools, because I wanted to extract semantic information from wiki-formatted text. That parser folded into my main project, using the then-nascent translation technology to improve cross-language information retrieval. The same approach I’d built for one wiki became the basis for extracting structured knowledge from Wikipedia at a Google-wide scale when someone found my codebase and built on top of it.

Then deep learning caught my attention. This was before the current AI wave, when neural networks were still a niche interest among most engineers. I studied the fundamentals, ran experiments, and applied what I learned to help build the first query-less feed ranking system in Google Search; a system that could surface relevant content without the user typing anything.

Not all of them worked. Plenty of experiments in that overflowing folder went nowhere. I was disappointed every time. But I wasn’t staking my career on any single experiment, so the disappointments were tuition, not trauma.

The same pattern drove my financial education. In 2010, I opened a brokerage account and started buying $500 lots of individual stocks; not because I had a thesis about beating the market, but because I wanted to understand how different businesses worked. I read Ethereum’s whitepaper before most people had heard the term “smart contract.” I deployed tens of thousands of dollars across hundreds of peer-to-peer loans on Prosper and LendingClub because I wanted to understand credit risk from the lender’s side, and applied machine learning to invest intelligently in high-credit-risk loans. I invested in early-stage startups through crowdfunding platforms because I wanted to see how venture math worked with my own money on the line.

Each experiment taught me something no textbook could. The P2P lending account, which wound down as defaults crept up and the industry folded, taught me the difference between yield and return. Crypto taught me that conviction and position sizing are two different skills. Startup investing taught me that portfolio-level math can work even when most individual bets fail.

The common thread across all three domains: deliberate exposure to things outside your core. Read beyond your field. Study adjacent disciplines. Spend time with people who’ve already achieved what you want to achieve.

The varied inputs create connections between seemingly unrelated concepts, and those connections are where the breakthroughs live. A wiki parser built from compiler tools. A meditation practice refined by years of comparative exploration. A machine learning approach to peer-to-peer lending. None of these would have happened inside a narrow lane.

Master your decisions

Expanding your knowledge is necessary but not sufficient. The harder skill is knowing what to do with it: when to push an experiment forward, when to walk away, and how to avoid staking your identity on any single outcome.

I learned this most clearly in my brokerage account.

In 2012, I went through an options phase: selling puts on Amazon and Goldman Sachs, buying calls, collecting premium, feeling sophisticated. Then I realized options require monitoring, and monitoring requires time, and time was the one resource a full-time engineer didn’t have in surplus. I stopped. Not because options are bad, but because I recognized the mismatch between the strategy and my life circumstances. A decision about fit, not about the instrument.

I traded Sears like it was a day job; buying and selling a few hundred shares here, then a hundred more later. The company went bankrupt in 2018. Whatever I made on the round-trips, I spent more in attention and commissions than it was worth. The lesson was clean: trading isn’t investing, and the line between them blurs when you’re not paying attention.

But I held ADP, the payroll services company. Bought 40 shares in May 2010 at $38. Added more in 2012. And then I did nothing. Nothing changed about the business that made me want to sell. So I didn’t. Fifteen years later, one position bought with experiment money was worth more than every failed experiment combined, many times over.

The decision to hold ADP wasn’t brilliant analysis. It was the absence of a reason to act. And that’s its own kind of decision mastery: recognizing when the best move is no move at all.

The options taught me to match strategy to circumstances. Sears taught me to distinguish trading from investing. ADP taught me the power of inaction. Three positions, three different lessons about the same underlying skill: calibrating when to move and when to stay.

The same calibration mattered at Google. My 20% projects required a constant stream of judgment calls. The Wiki markup parser worked as a standalone tool for my team. Should I push to expand it Google-wide? That meant advocating to leadership, navigating organizational politics, and risking the project getting killed by people who didn’t share my enthusiasm.

The spelling correction project drew the most skepticism. Google’s web spelling system was built for short queries; a few words at a time. Extending it to full documents wasn’t an obvious move. The first reaction from senior engineers wasn’t “how would this work?” It was closer to “why would we even do this?” Google Docs already had basic spell-check. The web-scale approach seemed like overkill for a productivity tool.

But I’d built the prototype, and the prototype made the argument I couldn’t. The web-based approach caught errors conventional dictionaries missed; proper nouns, technical terms, emerging slang; because it drew on the same corpus powering Google Search. Once senior engineers saw it working, the skepticism dissolved fast. It wasn’t a hard sell once there was a demo. It made the product obviously better. The gap wasn’t between a good idea and a bad one. It was between an idea that sounded unnecessary in the abstract and one that looked inevitable in a demo.

That experience taught me something about conviction: it’s not enough to believe you’re right. You need to build the thing that shows you’re right. Persuasion follows demonstration.

The meditation journey required the same calibrating skill. Moving from Tibetan practice to Theravada wasn’t a failure of commitment. It was an honest assessment that one approach resonated more deeply than another. There’s a version of spiritual seeking that treats every change as evidence of flightiness. I see it differently. Each transition was a decision informed by direct experience, made without guilt or identity crisis.

The connecting thread: good decisions require detaching your ego from your experiments. Uncertainty is the default condition, not an obstacle to overcome. Think rationally about probabilities rather than emotionally about outcomes. Reflect on past decisions to extract patterns, not to berate yourself for the ones that didn’t land. And above all, don’t confuse the decision with the result. A good process can produce bad outcomes, and a bad process can get lucky. Judge the process.

Build and grow

Knowledge and good decisions matter because of what they enable: compounding. Not financial compounding alone, though that’s the most visible kind. Compounding of skills. Compounding of relationships. Compounding of inner stability.

The principle is the same across every domain. Make consistent deposits into a foundation. Protect that foundation from catastrophic loss. Give it time. The returns arrive slowly, then all at once. It’s little wonder compound interest is the eighth wonder of the world.

In my career, each 20% project added to my toolkit in ways I didn’t fully appreciate at the time. Porting bus schedules taught me to build proofs of concept fast. The wiki parser taught me tools built for one context can be repurposed at scale. The spelling correction project taught me how to stretch a working system into a new domain, and that a working demo is worth a thousand arguments. The deep learning work taught me to place a bet on an emerging technology early, before the organization was ready to believe in it.

Individually, none of that sounds remarkable. But skills stack. A decade in, I wasn’t a specialist in any one of those areas. I was the person who’d done all of them, and that turned out to be more useful than being the best at any single one. The experimental folder wasn’t waste. It was compound interest on knowledge, paid out over years.

The financial compounding is easier to quantify. In 2010, I started feeding my 401(k) through Vanguard: total market index funds, international stocks, bonds, REITs. Then I did the hardest thing in investing. I stopped looking at it. Over the next decade, the account grew roughly 10x. Part of that was market performance; the S&P 500 roughly quadrupled over the same period with dividends reinvested. The rest was consistent contributions, compounding on top of compounding. I didn’t rebalance obsessively. I didn’t panic sell during COVID. I didn’t try to time anything. The returns came from three forces: consistent contributions, compound growth, and the stubbornness of not touching it.

That boring foundation made everything else possible. When 80% of your money is growing steadily, the remaining 20% becomes a sandbox where you can afford to take real risks, because the downside is capped by design.

The experimental brokerage account produced its own compounding story. ADP grew roughly a hundredfold over fifteen years. The magic was time and compounding, not brilliance. Meanwhile, the startup investments I made through crowdfunding followed venture math: most failed completely, but the winners more than compensated for the losers, and the overall multiple landed well above what I’d have earned in an index fund over the same period.

The meditation practice compounded too, though the returns are harder to measure on a statement. Years of exploration; moving through Christian denominations, studying Tibetan techniques, reading contemplative texts; distilled into a Theravada practice that became the non-negotiable foundation of my daily life. The exploration phase was the research. The daily sitting is the compounding. Each year of consistent practice builds on the last in ways that are subtle but unmistakable: steadier attention, less reactivity, a quieter relationship with my own mind.

And the principle that protects compounding is the same across all three domains: avoid catastrophic loss. In finance, this means living within your means, avoiding excessive debt, and keeping cash reserves so you never have to sell investments at the worst possible time. In a career, it means delivering on your core responsibilities before running experiments; the 80% has to be solid. In a contemplative practice, it means protecting the daily habit from the chaos of life, making it non-negotiable even when everything else is in flux.

You can’t compound what you don’t protect.

What I’d tell someone starting out

Secure the base first. In your career, be excellent at your core job before you start experimenting. In your finances, automate your savings and build a boring diversified foundation before you open a brokerage account. In your inner life, establish a daily practice before you chase peak experiences.

Size your experiments to learn, not to get rich. My early stock trades were $500 at a time. My early 20% projects were small proofs of concept. My early meditation experiments were evening classes, not retreats. Small enough that a total loss is tuition, not trauma.

Diversify your experiments, not your positions alone. I didn’t put my 20% into one area. In finance, I spread it across stocks, P2P lending, crypto, and startups. In my career, I explored data conversion, natural language processing, machine learning, and product advocacy. In contemplative practice, I moved through Christian traditions, Tibetan Buddhism, and Theravada. Each experiment taught me something different about risk, resonance, and my own psychology.

Keep notes. I have brokerage statements going back to 2010. In Google’s monorepo environment, the code from 20% projects is all saved. I have handwritten notes and journals from meditation classes and retreats. When I look at these records, I’m not nostalgic. I’m reading lab notebooks. Every entry tells me something about what I believed at the time, what I got right, and what I’d do differently.

And above all: judge the portfolio, not the position.

We’re wired to feel losses more intensely than gains. Behavioral economists call it loss aversion. A $110 loss on Converted Organics feels like a failure when you stare at it in isolation. A 20% project killed after three months feels like wasted effort. A meditation tradition you leave behind can feel like a spiritual dead end.

But zoom out. Check the aggregate. If the portfolio is growing; if your career is advancing, your net worth is compounding, your inner life is deepening; then the individual losses are doing their job. They’re the cost of exploration. They’re tuition.

The venture capital industry understood this decades ago. VCs expect most investments to fail. They don’t call those failures. They call them the cost of finding the winners. VCs invest other people’s money. I applied the same logic to my own life, with the safety net of a boring foundation underneath it all.

The experiments work only because the 80% exists. If you’re not building a solid career foundation before running side projects, the experiments are reckless. If you’re not maxing your tax-advantaged retirement accounts before trading individual stocks, the brokerage account is gambling. If you don’t have a consistent daily practice, the exploration is spiritual tourism.

The 80% keeps you solvent, employed, and grounded. The 20% keeps you curious, engaged, and growing. Without the 80%, the experiments are dangerous. Without the 20%, the foundation becomes a cage.

You need both.

The best investment framework isn’t the one that maximizes returns. The best career strategy isn’t the one that eliminates risk. The best contemplative practice isn’t the one that promises instant transformation. The best framework is the one you’ll stick with. For me, that’s been a boring foundation with a laboratory on top.

I still keep the brokerage statements, old code, handwritten notes from meditation classes. Not out of nostalgia. Every entry reminds me what I believed at the time, what I got right, and what I’d do differently. That’s the whole practice, really. Run the experiment. Write it down. Run the next one.