The concept of alpha in finance is straightforward. And almost impossibly difficult.

Alpha is the portion of return that cannot be explained by the market. It emerged from the Capital Asset Pricing Model in the 1960s, when Michael Jensen tried to measure whether fund managers produced returns beyond simple exposure to market risk.

The goal was to answer the question, “What percent of these returns are due to manager skill vs simple market performance?” Put another way: What is the portion of returns that directly connects to the special value of their ideas vs the simple generalized increase in human productivity expressed through market gains.

Some managers did indeed produce alpha. Most did not.

Investors have always chased it. Founders romanticize it. Peter Thiel reframed it in Zero to One as the secret. The important truth very few people agree with you on.

Alpha, by definition, requires divergence. And divergence is socially uncomfortable.

If alpha is divergence, the modern venture ecosystem is convergence.

Funds articulate similar theses. Decks converge toward a standard template. Entire sectors become mandatory. Every company is “AI-native.” Every downturn produces the same rhetoric about discipline and efficiency.

The phrase I hear often is “playing the game on the field.”

It sounds competitive. It sounds pragmatic.

But structurally, it means doing what everyone else is doing at the same time, with the same assumptions. Which, when you think about it, is a curious way to pursue differentiation. The entire premise of venture capital is to find ideas that are new, experimental, strange, divergent. But somehow what’s intended to be the most exploratory and exciting asset class has become the most dominated by herd mentality.

The data makes this visible.

That is not a diffuse search for secrets. That is concentrated capital flowing into a narrow set of narratives. When that much money crowds into a small number of themes and companies, behavior synchronizes. Outcomes correlate.

And correlation eliminates alpha.

The paradox is obvious. Venture capital exists to find contrarian ideas. To produce uncorrelated returns. To generate alpha. Yet the behavior of the ecosystem increasingly rewards conformity.

“Playing the game on the field” sometimes means burning capital because that’s what the cycle rewards. Sometimes it means forcing AI into your strategy because that’s what the narrative demands. Sometimes it means building to match comps instead of building to match customers.

Of course, it also means hearing thought leaders echo the same sentiments over and over about mandatory growth rates, what you’re supposed to be doing, why your company is likely worth 0 if you don’t follow their advice, and so on.

But let’s be clear: the definition of the phrase is “do what everyone else is doing.” Hearing it from the supposed stewards of contrarian capital has a certain academic elegance to it.

Here’s the thing about convergence: It’s a nice place to hide. If the market is rising, you may track the market mean. But if your goal is simply to track the market, the best strategy is to buy an index.

Starting a company is not an index strategy. It’s a risk strategy. It’s supposed to be asymmetric.

And asymmetric outcomes do not come from synchronized behavior.

The hardest part about alpha is not understanding the definition. The hardest part is being different.

There is a deep psychological preference for correlation. Shared error is socially survivable. Independent error is reputationally expensive. It’s easier to be wrong together than to be wrong alone.

This is not just cultural. It has been studied for decades. In the 1950s, Solomon Asch ran a series of experiments where individuals were asked to compare line lengths, a task with an objectively correct answer. When confederates in the room intentionally chose the wrong answer, a significant percentage of participants conformed, even when the correct answer was obvious.

They did not lack intelligence. They lacked social insulation.

Economists later formalized this dynamic as “information cascades.” In a foundational 1992 paper, Bikhchandani, Hirshleifer, and Welch showed how individuals rationally ignore their private information and follow the crowd once enough others move in one direction.

And Keynes famously described markets as a beauty contest where participants try not to choose the face they personally find most attractive, but the face they believe others will find attractive. That dynamic appears to have accelerated in venture capital circles.

When capital crowds into a category, deviating looks reckless. When everyone is posting daily, silence looks irrelevant. When every deck says AI, omission looks naïve.

This is how herds form. Not because everyone is foolish. But because deviation carries visible short-term cost.

Alpha, however, requires tolerating that cost.

Let’s undertake a simple thought experiment. We can list out the various elements of modern herd behavior and then list its natural opposite. If you were to invert the dominant behaviors of this cycle where dominance implied conformity, the elements of alpha, the behaviors that would run counter to consensus, might look something like this:

Some of this may sound self-serving. I don’t run an AI-native company growing 500% a year. I’m aware of that. But I also don’t believe alpha in 2026 comes from trying to out-AI the AI-native companies.

I believe it comes from choosing a different axis. Listening to customers. Building something durable enough that it compounds independently of market volatility.

That is the path I’m choosing.

There is another dimension to this, and it relates to time.

Alpha often requires a longer horizon than the market’s default attention span. If your investors expect liquidity on a certain cadence, if your peers evaluate progress quarterly, if your personal identity is tied to visible acceleration, then your decisions will tend to compress toward what can be validated quickly.

And the market’s attention span has, in fact, compressed.

The average holding period for U.S. equities has fallen dramatically over the past several decades, from years to, in many cases, months, as trading velocity and capital mobility increased. Andrew Haldane of the Bank of England has written extensively about this shift toward financial short-termism and the way it changes corporate incentives.

Shorter holding periods produce shorter feedback loops. Shorter feedback loops produce synchronized behavior.

But some of the most durable forms of advantage compound quietly. Brand built through consistency rather than virality. Trust built through years rather than campaigns. Teams built through shared standards rather than opportunistic hiring. Products refined through iteration rather than rapid expansion.

This isn’t just philosophical. McKinsey studied companies over a 15-year period and found that firms classified as “long-term oriented” significantly outperformed their peers on revenue growth, earnings growth, and market capitalization. Long-term orientation is not romanticism and I’m not being “soft” by writing this. It’s empirically associated with outperformance.

Of course, markets do not immediately reward this posture. In fact, they may penalize them in the short term. What other reaction can be taken from prominent investors berating companies for growing at less than explosive growth rates in the age of AI?

But. That’s precisely why it can work.

If everyone else is optimizing for the loud game: Attention, speed, narrative. Maybe there’s alpha in playing the long game.

Alpha is not contrarianism for sport. It is not reflexively rejecting consensus. It’s being deliberate about where you allow yourself to be correlated and where you insist on independence. Behaving this way requires confidence, self-awareness, a certain type of introverted “aloofness,” and deep conviction about the needs of your customer.

In a world increasingly synchronized by capital, algorithms, and shared information, structural independence may be one of the few remaining edges left.

So, the real question is simple:

Are you building something that can be fully explained by the current market?

Or are you building something that, if it works, will not be easily explained at all?

One path feels safer.

The other is rarer.

And rarity is where alpha lives.

This article was originally published by Sam Jacobs on Substack, Feb. 22, 2026. It is reproduced here with permission. Read the original article here.

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