The AI-native PRD for building with AI tools

I’ve been watching people build with AI coding tools — Lovable, Bolt, Cursor, Claude — and the pattern is almost always the same. Describe what you want in a few sentences, hit enter, hope for the best.

Sometimes it works. Usually you get something that looks right on the surface and falls apart the moment you try to use it. Missing validation. Features nobody asked for. A data model that makes simple things impossible later.

The experienced builders know they need a spec. So they reach for the PRD — the format product management has used for decades. But traditional PRDs were written for humans. Engineers who ask clarifying questions. Designers who read between the lines. The whole format assumes a conversation, a shared understanding that develops over time.

AI tools don’t do any of that. They take what you give them literally. They fill gaps with assumptions. They don’t push back when your requirements conflict. And they love adding features you never asked for — Stripe integration, dark mode, an admin dashboard — because those patterns are everywhere in their training data.

The format needs to change. Not because PRDs are bad, but because the reader has changed.

After building with these tools and watching where things break, a few principles became clear.

AI doesn’t need the “why” behind your product strategy. It needs to know exactly what happens when a user clicks a button. “The experience should feel seamless” means nothing to a model. “Clicking Save writes the record and shows a toast for 3 seconds” means everything.

LLMs are great at building the happy path. They’re terrible at inferring guardrails. If you don’t say “expense amounts must be greater than zero,” that rule won’t exist.

Structure beats prose. A well-organized spec maps to how code works. Beautifully written paragraphs require interpretation, and interpretation is where things go sideways.

And the single most common failure mode is scope creep — initiated by the AI itself. Without an explicit “out of scope” list, the model will happily build things you never asked for.

So I put together a template — a spec format designed for AI tools. The AI-Native PRD. I’m sharing it publicly because the ecosystem benefits when builders have better starting points.

A few sections worth calling out.

The product overview acts as a system prompt for your entire product. Name, one-liner, problem statement, target user, success criteria. If this is vague, everything downstream is vague.

The data model is the highest-leverage section. Get your entities and relationships right, and the AI generates coherent code across your whole app. Get it wrong, and you’ll spend hours debugging issues that trace back to a flawed foundation. Most people skip this entirely and let the AI figure it out. It will — just not the way you’d want.

Instead of user stories, the template uses state transitions. [Landing Page] → clicks "Get Started" → [Sign Up Screen]. This is how code actually works — routes, state changes, side effects. When you describe your product as a state machine, the AI maps it directly to implementation.

Empty states matter more than you’d think. One of the most visible signs of an AI-built product: you create an account, land on a dashboard, and see nothing. No guidance, no prompt. Specifying empty states in your spec fixes this instantly.

Business rules are the AI’s blind spot. It won’t decide on its own that free users are limited to 3 projects, or that only admins can delete records. Every rule needs to be stated explicitly.

And the out-of-scope section is critical, not optional. Building a group expense tracker? Without fences, the AI might add receipt scanning, multi-currency support, and a chat system — none of which you asked for, all of which you’ll have to maintain.

The filled template runs between 1,500 and 3,000 words. If yours is longer, you’re probably building too much in one pass. Break it into modules and build iteratively.

This isn’t a replacement for product thinking. You still need to understand your users and your market. It just helps you communicate what you’ve decided to a non-human builder in a way that works.

Download the AI-Native PRD Template →

The tools are getting better every month. The specs we feed them should too.