The New Early-Stage Math: Why AI Makes Product Your First Hire

AI flipped early-stage hiring leverage from engineering to product, and that shift can dramatically improve your odds of reaching product-market fit before the money runs out.

What’s the Problem? is publication exploring the future of product building, written by a longtime product leader whose experience spans both the largest (Amazon, Airbnb, CBS) and the smallest (Haven, SET, Jacent) companies around. Like any good product discussion, we start with the question: What problem are we trying to solve?

What’s the problem? What hiring strategy gives us the fastest path to product-market fit?

The startup wisdom of the last decade has been clear: do not hire product until you have found product-market fit. Let the founder and engineers drive early discovery, keep the team small, and avoid adding “process people” too soon. And honestly, that was not crazy advice in many situations. But AI has completely rewritten that equation. In an AI-accelerated world, the highest-leverage early hire is no longer engineering. It is product.

The Case Against Hiring Product Managers Early

There are a few common arguments for why early-stage startups should not hire PMs, and why even a few large companies like Airbnb avoided them. The first is that PMs gravitate toward delivery, project management, and process (I mostly disagree), and those things do not matter pre-product market fit and can even slow you down. The second is the belief that founders and engineers can cover product themselves. Founders should not outsource the search for product-market fit (true), and great engineers should think like PMs and generate strong product ideas as they build (also true).

What That Logic Gets Right (and Wrong)

Partly. Some of the logic is fair, and some of it is not. First, you should not hire your first PM to run delivery or keep Jira tidy, and I would argue you should never hire a PM for that. Most of it barely matters pre-PMF. Second, should the founder act as the PM before PMF? Maybe. If they have real product experience, absolutely. But having a product idea is not the same as knowing how to scope, prototype, test with users, or work efficiently with engineers. And regarding the idea of hiring product-minded engineers: yes, you should. That is the only kind of engineer I ever want to hire at any company, at any stage. But it is still a tradeoff, and they are doing two jobs, only one of which they are world-class at.

The Leverage Shift: From Engineering to Product

So why does the old hiring logic fall apart now? Because early-stage startups only care about two things: finding product-market fit and not running out of money. Those two forces are not just important. They are opposing forces locked in a cage match. You have to explore fast enough to beat your burn rate before it beats you.

Most teams do not get to PMF on their first attempt. Or their second. Or their third. You are running a series of small, rapid bets, not building for scale. In fact, technical scalability matters very little at this stage (usually), especially since you might throw away the early versions entirely.

Here is the good news. In 2025, satisfactory engineering talent is essentially free, but it is no longer a differentiator, at least for junior-level work. The only real leverage left is product: taste, judgment, and the ability to run the right tests quickly. Product is now the highest-leverage function you can add early, and we are a long way from AI taking that wheel.

For years, founders hired engineers first not because engineers were better at product, but because someone had to build the thing. Engineers could fake PM work better than PMs could fake engineering. That is no longer true. A PM with strong product instincts and an AI coding agent can now explore more ideas, and do it faster, than an engineer-heavy team could just a few years ago.

And what about scale? Yes, eventually you will need to build a technically robust, scalable product. But that comes after PMF. An early-stage team made up of engineers with AI support can absolutely rebuild or upgrade your early PMF winner with far more focus and far less wasted time.

Just to be clear: yes, you still need engineers. I like them. I used to be one. None of this means engineering is easy. Senior engineers and strong tech leadership matter more than ever. They should be at the top of your hiring list. But if your instinct is still “only engineers at my startup,” you are running the 2025 playbook with 2015 assumptions. AI makes building cheap. Wrong turns are what kill you. Bring in product early, and your chances of beating the burn-rate monster go way up. That is where the leverage lives now.

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