I have stopped asking whether an AI-generated MVP "looks good."
That question is too easy to satisfy.
What I care about now is whether the prototype creates a false sense of readiness. After testing flows in NxCode, I usually run three checks before I let the idea turn into sprint tickets.
1. A polished first screen with no proof screen
If the landing screen is clean but I still cannot point to the screen that proves the job is done, the MVP is not ready.
For a client-intake workflow, the proof screen is not the hero section. It is the board where I can verify:
- owner
- next action
- due date
- status
If that screen is weak, the prototype is still presentation-grade.
2. A happy path with no recovery path
I look for one annoying but ordinary failure:
- missing owner
- blank due date
- duplicate lead
- item blocked waiting on approval
If the flow has no visible recovery behavior, it is only showing me the demo path.
3. Too many fields that nobody will trust yet
The first version does not need a full data model. It needs the smallest set of fields that the team would actually trust on day one.
My cutoff is usually:
- source
- owner
- priority
- due date
- short note
When the prototype contains advanced settings, analytics, permissions, and reporting before this core is believable, it is pretending to be further along than it is.
The decision I write down
Before I move forward, I force one sentence:
Keep the intake board, manual status update, and next-action handoff. Cut reporting, permissions, and notification rules from sprint one.
That sentence tells me whether the prototype deserves implementation time.
I have been using NxCode for this because it gives me something concrete to inspect instead of debating a blank spec:
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