Stop Asking AI to Write Your PRDs. Try This Instead.

You’ve just been handed a massive, unfamiliar project. You don’t know the industry, you don’t know the legacy code, and you have two days to produce a product strategy. So, you do what any modern knowledge worker does: you dump 100 pages of documentation into an AI tool and hit ‘summarize.’

We’ve all been there. The panic, the drowning in documents, the desperate hope that AI will save us from the drudgery. And it does. It spits out a beautifully formatted, comprehensive PRD. It generates a polished prototype. It looks brilliant. It looks complete.

It is incredibly dangerous.

The real danger of AI isn’t that it will replace you, but that it will confidently hallucinate the business rules you forgot to clarify.

Most Product Managers are obsessing over the wrong thing. They want to know which AI tool generates the prettiest UI or the longest PRD. They treat AI like a hyper-fast intern, happy to let it fill in the blanks. But when a business stakeholder says, ‘I want a batch export feature,’ and your AI immediately drafts a flawless specification, who defined the permissions? Who decided which fields could be exported? Who handled the error states?

The AI did. And it guessed.

A complete document generated by AI isn’t a finished project; it’s a list of unverified assumptions dressed up in professional formatting.

The more complete and polished the AI’s output looks, the higher the risk that you’re injecting fabricated rules into your product. This is the illusion of completeness. It’s the trap that turns PMs from strategic thinkers into careless document machines.

It’s time to flip the script. Stop asking AI to be your writer. Make it your auditor.

Instead of using AI to generate documents, use it to interrogate your thinking. Build custom ‘Skills’—prompt frameworks that force the AI to act as a strict requirement auditor. When you hand it a vague idea, it shouldn’t write a PRD. It should ask you questions. It should separate the known facts from its own assumptions. It should highlight exactly what is missing.

I’ve built this exact workflow. When I feed it a feature request, my AI Skill first repeats its understanding in three sentences, explicitly dividing what I told it from what it assumes. Then, it asks 5 to 10 categorized questions: What’s the business goal? What’s the user scenario? What are the role permissions? What happens when the API fails? It forces me to confront the gaps in my logic before a single line of documentation is written.

This changes everything. You stop outsourcing your thinking to a machine, and you start using the machine to expose your blind spots.

Of course, you still need tools for the heavy lifting. I use Codex for keeping project context and prototyping, and GPT Plus for generating UI concepts and assembling PPTs. Tools like Kimi are great for front-end visuals, but remember: generating a page from scratch is easy; iterating on an existing page without breaking it is where the real work happens. Don’t burn your credits on zero-shot generation; use them on iterative refinement.

But the tool doesn’t matter if your workflow is broken. Don’t just hand AI a blank page and hope for the best. Hand it your business rules, your edge cases, and your requirement templates. Make it do the mechanical labor of organizing, but force it to leave the business decisions to you.

When writing documents and drawing prototypes is no longer hard, your only remaining value is knowing why those documents exist in the first place.

The ultimate relief of AI isn’t that we can finally stop writing PRDs. It’s that we finally have no excuse not to talk to our users, understand our business, and think deeply about the problems we’re solving. The document machine is dead. It’s time to be a Product Manager again.