How to Have AI Write Your PRD Before It Writes a Line of Code

You have probably done this. You describe an app or a feature to your AI tool, it builds something close to what you pictured, and a few prompts later you are untangling code that drifted away from what you meant.

The fix is older than AI, and it is simple: write the plan before the build. A PRD, a product requirements document, is that plan. It says what you are building, who it is for, why it is worth doing, and how you will know it worked. Learning to write one is a practical entry point into The 7 Levels of AI Proficiency, and it is more approachable than it sounds.

Here is what a PRD is, when it is worth one, and how to have your AI tool draft it with you in about twenty minutes. There is a reusable PRD skill and a worked example to download near the bottom.

What a PRD actually is

A PRD is a short document that describes a build before it gets built. It is not code and it is not a technical design. It is the plain answer to four questions: what are we making, who is it for, why now, and how will we know it worked.

A PRD is a living document. The best one is the one you get feedback on early and often, from the people who matter, as you edit it. So you start simple. A first version covers a handful of sections, each one short:

• Business context and the problem you are solving
• Who it is for, and why now
• Success outcomes and KPIs: how you will prove it worked
• Requirements, written as the jobs the thing needs to do
• Out of scope, and the open questions still to settle

That is the whole shape. The downloadable skill and the worked example below lay out all ten sections, but you do not need them all on day one.

When it is worth writing one

Not every task needs a PRD. A one-off script does not. The test is whether something will be built and lived with. An app, a feature, an automation, anything you will hand to a tool or a teammate, is a candidate.

The clearest sign you need one is drift: you keep re-explaining the build, the result keeps coming back a little off, and you are not sure why. A PRD is the shared answer everyone, including your AI tool, can build from.

Why a PRD does more with AI

An AI coding tool is fast and literal, and it cannot infer what you left out. If your plan does not say "do not build user accounts in this version," the tool may add them anyway, because most apps have them. Every boundary has to be written down on purpose.

That blind spot is where a lot of AI builds go sideways. A 2026 Lightrun survey of engineering leaders found that 43 percent of AI-generated code changes still needed debugging in production, even after passing tests. In his guide on writing specs for AI, Addy Osmani describes the shift this way: your job is to steer, and the coding agent does the bulk of the writing. Whoever writes the spec is steering, and the PRD is how you take the wheel.

Have your AI write the PRD with you

You do not start from a blank page. The fastest path is to let your AI tool interview you, then draft from your answers. Five habits make the result solid.

Do it now: two prompts

Paste this into your AI tool and fill in the one blank. It will interview you, then draft the PRD.

I want to plan a build before you write any code. Help me create a PRD
(product requirements document) for it.

The build is: [describe what you want to make in one or two sentences].

First, interview me. Ask up to seven questions, in one batch, to understand:
1. the business reason this is worth doing,
2. the exact problem it solves,
3. who will use it,
4. why it is worth doing now,
5. what success looks like and how we would measure it,
6. what it must do, and
7. what we are deliberately NOT building in this version.

If I cannot answer something, add it to an Open Questions list instead
of guessing.

Then write a short PRD with these sections: business context, problem
statement, who it is for, why now, success outcomes and KPIs, assumptions,
requirements (as Jobs To Be Done), out of scope, and open questions.

Keep it simple. Do not start coding yet.

Read the draft once and tighten the problem statement and the out-of-scope list, because those are the two parts you know better than the tool does. Once the PRD looks right, turn it into a build plan with this second prompt:

Here is the PRD we just wrote: [paste it].

Turn it into a build plan I can hand back to you.

1. Break the requirements into 3 to 5 phases, foundations first, so each
   phase can be built and tested before the next.
2. For every phase, list what to build and, just as clearly, what NOT to
   build yet. State each boundary as a positive instruction, because you
   cannot infer a limit from silence.
3. Add a short checkpoint after each phase: how we will know it works.
4. Flag anything in the PRD that is still too vague to build from.

Do not write code yet. Show me the plan first.

Now you have a plan the tool can build from, in an order it can follow, with the limits stated. The build still needs your eye, but it starts from what you meant.

A reusable skill and a worked example

Two things to take with you. The first is the PRD as a reusable skill file: drop it into your tool once, and from then on you type "write a PRD" and it runs the same interview every time. It works across Claude, Cursor, Codex, Gemini, and Copilot, because the SKILL.md format is an open standard.

The second is a worked example: a real PRD for one of our own builds, the content engine that researches and drafts these articles before a person approves them. We did not write this PRD before we built the engine, so this is the version we would write now. It shows the full recipe filled in at the simple altitude.

Three mistakes worth skipping

A few patterns trip up almost everyone on a first PRD. You can step around them.

The first is writing a novel. A long PRD slows the build and stops getting read. Keep the first version to about a screen per section, and add depth only where the build needs it.

The second is leaving boundaries unsaid. The "do not build this yet" lines feel optional until a tool spends an afternoon building something you never asked for. Write the out-of-scope list before the requirements.

The third is treating the PRD as finished. It is a living document. Revisit it when the build teaches you something new, and move answered questions out of the open-questions table as you settle them.

Where this fits into the bigger picture

I came to this the slow way. I am a creative by wiring, and for years my builds started as scattered, in-the-moment workflows that I rebuilt from memory every time. What changed was learning to design the process before building the thing, and to improve it on purpose instead of by accident. Writing the plan first felt like a tax at the start. It turned into the cheapest hour in the whole build.

That habit, turning a messy workflow into a designed one you keep refining, is the heart of Level 4 and Level 5 in The 7 Levels of AI Proficiency: building the systems around the work, then designing the work itself before you automate it. Writing a PRD before your AI tool builds is one of the simplest places to start that climb. You are doing something more durable than getting one good answer. You are deciding what good looks like before the machine decides for you.

If you want to see where you stand and what to practice next, the free 7 Levels of AI Proficiency assessment places you on the levels in about ten minutes and gives you a written next step.

Related reading: How to Write a Skills File for Claude (turn the PRD skill into one of your own). Why AI Projects Fail (the design-before-build case in full).

Sources

1. Aha! "What is a PRD (Product Requirements Document)?" Aha! Roadmapping Guide. Accessed June 9, 2026.
2. GitHub. "Spec Kit: Toolkit for Spec-Driven Development." GitHub. Accessed June 9, 2026.
3. Osmani, Addy. "How to write a good spec for AI agents." addyosmani.com. Accessed June 9, 2026.
4. Lightrun. "2026 State of AI-Powered Engineering Report." April 14, 2026.
5. The 7 Levels of AI Proficiency assessment.

Harrison Painter

Executive AI Advisor. Founder, LaunchReady.ai and AI Law Tracker.

Harrison is an Indiana AI Advisor who helps business owners and executives get their time back by building AI systems that run the work for them. Nearly 20 years in business and author of You Have Already Been Replaced by AI. Creator of The 7 Levels of AI Proficiency.

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