The Wave Carried Them

Hiring someone from the earliest wave of a fast-growing sector looks like a shortcut. Their resume has outcomes nobody else can show: steep growth curves, margins that sound made up, products that went from zero to widespread use. The numbers are real, which is why they mislead.

In the first phase of a new market, demand runs past supply so hard that average work produces great outcomes. Distribution is cheap because nobody else is bidding for it. Competition is thin because the best teams have not arrived yet. Customers forgive flaws because the product has no real rivals. In that world, the tide lifts every boat, even the leaky ones.

Then the wave passes, the market cools, and those people enter the hiring pool with paper claiming rare skill. Some of them earned it. Most of them were standing in the right place.

Beta dressed up as alpha

Finance solved this puzzle decades ago, and tech hiring rarely borrows the tool. As an illustrative baseline, portfolio managers split returns into beta and alpha. Beta is what the broader market handed everyone. Alpha is what the manager added on top. A manager who made twenty percent in a year when the index returned nineteen percent added almost nothing. A manager who made eight percent in a flat year showed real skill.

Resumes present top-line outcomes without a baseline. “Scaled revenue forty times” sounds like rare skill, but the market context is missing. What did the median team in that sector, with the same cash and user demand, do during the same window? In the first wave of a hot category, the baseline was often forty times as well. The outcome was mostly market beta. The hiring loop treats it as individual alpha because standard interviews have no column for the market tide.

The observational evidence supports the split. In Chasing Stars (2010), Boris Groysberg tracked more than a thousand top analysts over a decade. When star performers moved to rival firms, their performance plunged immediately and their odds of maintaining top ranking fell by nearly half. It stayed lower for years. Hiring firms paid peak pay for people whose results came from internal tools, brand reach, and market momentum rather than portable skill. The research tracked equity analysts, but the lesson transfers cleanly: teams confuse firm resources with individual talent.

It is a quiet cousin of survivorship bias. Survivorship bias hides failures; market attribution mislabels the drivers of success.

Mediocre people from a great wave will beat great people from a flat market in any resume screen you run.

Innovators and passengers

A major expansion carries two distinct groups. One group builds the foundation: making the core loop, the pricing model, and the architecture that competitors copy later. A much larger group joins after the initial lift. They execute playbooks that were already running before they touched the keyboard.

Both groups leave with the same logos on their resumes and similar growth metrics. On paper they look identical. That creates the hiring trap, because their value to you will diverge completely. The innovator builds new momentum in uncertain conditions. The passenger needs an engine built by someone else, and a cooling market stops providing that lift.

The observational data on venture cycles reinforces the divide. In Investment Cycles and Startup Innovation (2013), Ramana Nanda and Matthew Rhodes-Kropf showed that startups funded in hot market peaks fail at higher rates than those funded in cold markets. Cheap capital hides loose work and structural flaws. When cash dries up, teams built on easy growth collapse, while teams with disciplined unit economics survive.

If your interview cannot correct for a market surge, you are not selecting for talent; you are selecting for tenure during an expansion.

Telling them apart

The good news: you can spot the difference if you ask about mechanism instead of outcome.

Start with decision rights rather than results. What did you own that was not already working when you arrived? What did you change, and what pushed back against the change? Passengers narrate outcomes. Owners narrate decisions, including the bets that went wrong.

Then ask the counterfactual: if someone else held your seat for those three years, what would have happened? Strong operators have thought about this and answer with clear honesty. Weak ones treat the question as an attack, because it threatens their only story.

Asking why it worked is just as revealing. Innovators can explain the mechanism from first principles: why that channel was mispriced, why that product fit that moment, what everyone else got wrong. Passengers just list what happened, step by step. That depth is hard to fake for more than a few minutes.

Weight the post-wave years heaviest. The cleanest signal in the file is what the person did after the tide turned. Someone who produced results in the boom and kept producing them in the downturn showed real alpha. Someone whose output went flat the moment the market slowed showed the opposite. Their earlier numbers need a steep haircut.

The point isn’t cynicism

None of this means avoiding early-wave people. The innovators of the last wave are among the best hires in the world. Even honest passengers know how fast-growth environments feel and run. The wave inflates everyone’s paper equally, so paper is the wrong tool for reading it.

Outcomes tell you what happened. Skill is what would have happened anyway, somewhere else, without the tide. Hire the person who can make a wave, or at least explain one. Be careful with the person who can only tell you what it was like to be carried.