I like the way you've framed the problem, and it's actually an issue I bring up with designers that I work with, not that they go directly to screens, but that they go from problem to ideation too quickly.

We work in hardware, so we don't have UI to work with. UX isn't just UI, which I'm sure you know. I'd like to see something like your product to help guide people through the right questions, rather than finding the solution.

One of the challenges I have with many AI subscriptions is that when you price in credits, I have no idea how many questions, or what kind of workflow that gives me. 10 credits. That could be 3 questions.

This was actually the business model issue we had with our last business, where we had to pay for map tiles, and we loaded thousands of them. For our B2B customers, we came up with a pricing model which said "per 1000 scenes" and they knew what a scene was. We still had no idea how big their scene was going to be, but we priced so that they could understand what they'd get, and they could verify, yes we opened 40,000 scenes.

For our B2C customers, we had a simple monthly subscription because they would only likely use so much. We barely made any money on the consumers, but it helped offset the costs.

This isn't just a you problem. But it is what prevents me from using a lot of, what may be, very good tools.

I like that you’re positioning this as an “AI PM that happens to design” instead of yet another screen generator. Most tools are great at producing artifacts and terrible at preserving the reasoning behind them. If Figr could reliably spit out a tight decision log/constraints list from each session (what we considered, what we rejected, and why), that alone would replace a lot of hand-wavy product docs.

The 200k UX pattern corpus sounds powerful, but that’s also the scary part: pattern bias overpowering the specifics of a product. The more you can show “this suggestion came from your own data” (analytics, funnels, support tickets) and let teams tune how opinionated the pattern-matching is, the easier it is to trust it for things like onboarding and billing flows rather than just happy-path demos.