Why We Keep Rewriting AI-Generated Tech Product Briefs
Why We Keep Rewriting AI-Generated Tech Product Briefs
"A brief that reads well isn't the same as a brief that's right."
Over the last year, a new kind of first meeting has become routine at Elemental. A founder arrives with a document. It's often twenty or thirty pages long, well formatted, confident in tone, and clearly the product of hours spent prompting ChatGPT, Claude, or Gemini into producing a full technical brief for their web, mobile, or software platform. They hand it over expecting a quote and a start date.
We understand why. These tools are genuinely good at producing something that looks like a specification. Headings are in the right places, the language sounds technical, and the structure resembles documents we'd expect from an experienced product team. If you've never commissioned custom software before, there's no obvious reason to doubt it.
We've now reviewed enough of these briefs, across healthTech, property, EdTech and finTech founders in particular, to recognise the same handful of problems showing up almost every time. None of them are visible to the person who wrote the brief. All of them become expensive if nobody catches them before development starts.
The Missing Gaps
Almost every AI-written brief we review is missing entire categories of thinking that never occurred to the person prompting it. Scaling beyond an initial user base, exception handling when something goes wrong mid-transaction, permission structures for different user types, what happens when a third-party integration fails. These aren't edge cases a founder would think to ask about, because they've never had to design software that needs to survive real usage.
One brief we reviewed had two genuinely distinct user types at its core, merchants on one side and consumers on the other, yet it never once described how either of them actually got into the system. There was no sign-up flow for either group, and no mention of how a new merchant would be approved or moderated before being allowed onto the platform. That's about as fundamental a starting point as software design has, and neither the founder nor the AI writing the brief had thought to include it. We've written separately about why fail-safes and exception handling deserve as much attention as the features themselves, and it's rarely present in a brief someone has written alone.
The Contradictions
Because these briefs are usually built across several separate prompting sessions, often over days or weeks, different sections quietly contradict each other. A user permission model described in one section doesn't match the workflow described three pages later. A monetisation approach in the business overview doesn't line up with the feature list. Nobody notices because nobody is holding the whole document in their head at once, they're just refining one section at a time.
What The Founder Wants vs. What The Brief Says
When we sit down with a tech founder and ask them to talk us through their vision in their own words, it frequently sounds different to what's written in the brief. Not because they've changed their mind, but because the AI tool filled gaps in the conversation with plausible-sounding assumptions rather than asking a clarifying question. The founder never sees this happen. They just end up with a document that drifts slightly, and sometimes significantly, from what they actually meant.
Confidently Wrong
This is the one founders find hardest to believe, because it's the one they have no way of checking. If an architect tells you a beam needs to be a certain size, you trust them, because you have no basis to question it.
The same thing happens with an AI-written brief. It might over-engineer a part of the system that never needed the complexity, or under-engineer something that will buckle the moment real users arrive, and it will describe both with exactly the same confidence.
We've seen this play out in very concrete ways. One brief assumed that data would simply "arrive" from the app into a third-party support platform used to help users, described as a straightforward handoff.
In reality and after some research, that kind of integration is far more complex than a single line in a brief suggests, and building to that assumption would have meant discovering the real complexity mid-project rather than before it started. Another brief specified exactly how certain card payment and transaction data should be captured and validated. When our senior developers reviewed it, some of what was described simply wasn't possible to obtain or validate in the way the document assumed.
As our head of development put it after reviewing a batch of these briefs: "We are seeing a common pattern where so many items that are included in these AI written briefs are either not possible or they are simply the wrong way to implement certain solutions, from a structure and coding perspective. Any complex bespoke web or mobile app needs such a meticulously thought out structure and plan, however deviating from that means the project would start off on the wrong foot and significantly increase the chances of problems or even failure down the line."
The founder isn't a software engineer, so there's no reason they'd know the difference, and that's precisely the problem.
Solving Too Many Problems At Once
Perhaps the most consistent issue, and often the root cause of the contradictions above, is that these briefs try to please everyone. Every stakeholder's idea gets folded in, every feature that sounded useful in a prompting session gets kept, and the result is an "MVP" that's actually trying to solve four or five different problems simultaneously.
We saw this clearly with a HealthTech founder who came to us with several genuine USPs, each one reasonable on its own. The difficulty was that every attempt to narrow the brief down to a single, sharp MVP still left multiple distinct offerings bundled together. Each time we worked through it with him, the result kept circling back to a platform trying to be several products at once. Users would have struggled to understand what the platform was actually for, the messaging had no single clear hook, and the reason to sign up in the first place got lost somewhere between all the things it could theoretically do.
What Actually Works
We don't throw these briefs away. They're usually a genuinely useful starting point, they tell us what the founder cares about and where their thinking currently sits. What we do instead is run our Discovery and Consulting process against it: a structured series of conversations that surfaces the gaps, resolves the contradictions, and gets everyone, founder and development team, aligned on one clearly defined problem before a single screen gets designed.
This has played out with three recent clients in almost exactly the same way. Loads of questions on our side because of what's missing, loads of suggestions because of what doesn't hold together, and inevitably, a return to the beginning so the foundation is right before anything gets built on top of it.
The Fintech Founder Who Came Back Around
One of those three stood out. A founder approached us with a brief, built almost entirely through AI prompting, for a mobile cashback app connecting retailers and consumers. It was confident and detailed on the surface, close to build-ready in his mind. We ran our full Discovery process with him, and he was genuinely delighted by how thorough it was. For the first time, he understood what needed to be considered when things inevitably go wrong inside a financial product, the kind of exception handling and fail-safes we've written about separately, and he left with a clear, realistic roadmap for his platform well beyond the initial MVP.
About two months later, planning the next phase, he came back to us with a new brief, again written with AI. This time it contradicted something we'd carefully worked through together during Discovery: how the payment flow itself should actually work. The approach he now wanted, prompted into a fresh document without us in the room, pulled in a different direction to the model we'd already aligned on and built the early phases around.
Not because he'd lost confidence in the process, but because the habit of turning to an AI tool for a quick draft is an easy one to fall back into, especially under time pressure. We went through the same education process again: walking through why the new payment approach conflicted with the direction he'd already committed to, and helping him see the trade-offs he couldn't see on his own.
It's a useful reminder that Discovery isn't a single interaction. It's an ongoing relationship. A founder can fully understand the value of proper thinking during Discovery and still default to the fastest available tool when the next idea shows up. That's not a failure of the process, it's exactly why an experienced team needs to stay involved well beyond the first phase.
The Brief Isn't The Finish Line
None of this means AI-written briefs are a bad idea. If anything, they've made the case for structured Discovery stronger, not weaker. When it takes minutes to produce something that looks like a finished specification, the risk isn't that founders stop thinking about their product. It's that they stop questioning a document that sounds authoritative but was never actually challenged by anyone with the experience to know where it's wrong.
The brief was never the hard part. Knowing what's missing from it is.
If you've got an AI-written brief sitting in your drafts folder, or you're about to start one, don't wait until the first round of development to find out what it missed. Bring it to us before a single screen gets designed. We'll go through it properly with our Discovery and Consulting process, tell you honestly what's solid, what's missing, and what needs to change, and make sure your platform starts on a foundation built to last rather than one that needs rebuilding six months after launch.
Get it right the first time. Talk to us about Discovery.
