Why Crypto Companies Hire and Fire in Cycles

The mechanism, stated plainly

A conventional startup raises a fixed amount of currency. Runway is arithmetic: money divided by burn. It shrinks predictably, and a hiring plan made in January is still affordable in June unless spending changed.

A company holding its reserves in a volatile asset has a runway that moves without anyone deciding anything. The same holdings that funded eighteen months of a larger team fund considerably less after a drawdown, and nothing about the team's performance caused it.

That produces the pattern from both directions. When the asset appreciates, runway extends on paper, headcount plans expand to match, and hiring accelerates into what looks like abundance. When it falls, the same arithmetic runs backwards, and the correction lands on the largest controllable cost, which is people.

So the cycle is structural. It is not primarily about bad management, though bad management makes it worse, and it is not confined to companies you would consider unserious. Any organization whose reserves revalue faces this, and the ones that avoid it are usually the ones holding a meaningful portion in stable form deliberately.

What to ask before accepting

These are fair questions, the answers are knowable, and reluctance to answer any of them is itself informative.

What is the runway denominated in? Stable assets, a volatile token, or a mix. This single answer predicts more about your employment stability than the product roadmap does.

How many months at current burn? And separately, how many months if the treasury fell by half. A company that has modeled the second number is managing the risk. One that has not is exposed to it without knowing.

Where does revenue come from? Users paying for something is different from a treasury drawing down, and different again from grants or ecosystem funding, which have their own cycles and end dates.

How large was the team a year ago? A team that has grown and shrunk repeatedly is telling you the pattern applies here.

What happened during the last downturn? How they handled it, whether they communicated early, and what severance looked like. Past behavior under stress is the best available predictor of future behavior under stress.

Asking these is not adversarial. Founders who are managing the risk deliberately usually appreciate the question, because it is the same one they have already answered for themselves.

Compensation structure changes your exposure

Where part of the package is a token, the exposure compounds in a specific way worth naming.

In a conventional startup, equity is illiquid and correlated with the company's fate, so a bad outcome costs your equity and your job together. That is already concentrated risk.

With token compensation the correlation can be tighter and faster. The same price move that reduces the treasury, and therefore the headcount budget, also reduces the value of what you are being paid, in the same weeks. Your income, your holdings, and your employment can move together, and the vesting schedule keeps you exposed to all three for years.

None of that makes token compensation unacceptable. It makes it something to size deliberately rather than accept as offered.

Practical version: understand what portion of the package is stable and what portion is not, what the vesting looks like, and whether the stable portion alone is enough for your circumstances. Financial fragility is the most common reason people leave before vesting anything, which forfeits the upside that justified the structure in the first place.

This is general information rather than a recommendation about any specific offer or asset.

How to work in the sector without being whipsawed

The engineers who do well across cycles tend to do the same few things.

They prefer companies with users paying for something, since revenue that comes from customers rather than from a balance sheet behaves very differently in a downturn.

They keep skills that transfer. Almost all of the engineering does transfer, and the ones who go deep only on domain-specific tooling have a narrower fallback exactly when they need a wide one.

They build a public record continuously rather than when they need one. In a sector where hiring can stop abruptly, having verifiable work already visible is the difference between a search of weeks and a search of months.

And they treat the cycle as a known property of the environment rather than as a personal failure when it arrives, which matters because it will arrive at some point regardless of how well anyone performed.

HireOnChain is a job board for AI and onchain work built around reputation and credentials that can be confirmed rather than claimed, which is most valuable in precisely this situation: a market where employment can be interrupted for reasons unrelated to your work, and where the fastest recovery belongs to people whose record does not need explaining.