Use AI as a Tool. Keep the Thinking Human.

AI can generate user stories and requirements docs fast, but someone still has to understand them. How PMs and clients can use AI without creating AI slop.

Kendal Secrest, Director of PMO · October 16, 2026

AI can write the document. You still have to understand it.

AI can be an incredibly useful tool. It can help us organize messy thoughts, improve a draft, explore ideas, and spend less time staring at a blank page.

But being able to generate something quickly doesn’t mean we’ve done the work behind it.

In software development, that distinction matters. A polished document can still contain unclear requirements. A well-formatted user story can still describe the wrong behavior. And a detailed product plan can still include features no one actually asked for.

This is where “AI slop” becomes a problem: content that looks complete but hasn’t been meaningfully reviewed, understood, or validated by the person sharing it.

Someone eventually has to make sense of that content. Often, that someone is the team expected to build it.

A user story is only useful if you understand the product

For project managers, AI can help turn notes into user stories, suggest acceptance criteria, or identify questions we may have missed.

But writing the story is only one part of the job.

We need to understand who the user is, what they’re trying to accomplish, which rules apply, and how the requested behavior fits into the larger product.

If a PM uses AI to generate a ticket but can’t explain what it means, why it matters, or how it should work, the ticket isn’t ready for development.

The formatting might be right. It might even follow the team’s preferred structure perfectly. But developers and QA still need accurate information about preconditions, business rules, expected behavior, and exceptions.

A useful test is simple: Could you walk the team through this story and answer questions about it without relying on the generated text?

If the answer is no, there’s more work to do.

More documentation can create more work

The same issue can show up before a project even begins.

Imagine receiving an 80-page requirements document generated with AI. At first glance, it looks thorough. There are workflows, feature lists, technical suggestions, and detailed descriptions.

But a human still has to read all 80 pages.

They have to separate actual requirements from suggestions, identify contradictions, and figure out which details reflect the client’s intentions. Sometimes, that includes asking about requirements the client didn’t even realize were in the document.

An AI-generated suggestion can quietly become an apparent commitment simply because it appears under a heading labeled “Requirements.”

That creates confusion around scope, estimates, priorities, and expectations.

Clients don’t need to arrive with perfect documentation. Helping clarify their ideas is part of our work. But an AI-generated document is most useful when the person sharing it has reviewed it and can distinguish what they want from what the tool proposed.

A shorter document with clear priorities and honest open questions can be much more valuable than 80 pages of apparent certainty.

Use AI to support your thinking

Responsible use doesn’t mean avoiding AI. It means staying involved.

That can look like:

• Start with what you know. Give AI real context, constraints, and decisions instead of asking it to invent the product.
• Keep questions visible. Missing information should become a question to resolve, rather than an assumption presented as fact.
• Review for meaning. Check whether the output is accurate, relevant, and aligned with what was actually discussed.
• Separate suggestions from requirements. An interesting idea is not automatically approved scope.
• Consider the reader’s time. Remove repetition and unnecessary detail. Generating content is fast; reviewing it takes effort.
• Own what you share. If your name is on the document, you should be able to explain and stand behind it.

One of the most useful ways to work with AI is to ask it to challenge a draft: What’s unclear? Which assumptions need confirmation? What questions would a developer or QA tester ask?

Those prompts help us do the thinking our roles require.

Understanding is still the work

There’s real value in using AI well. It can make our work clearer, help us spot gaps, and give us more time for conversations and decisions.

But we should judge its value by whether it helps people understand and act, not by how many pages it produces.

Before sharing an AI-assisted document, ask yourself: Do I understand this, have I checked it, and will it make the next person’s job easier?

AI can help us write. The responsibility for what we send is still ours.