MVP in 30 Days: A Framework for AI Startups
How to ship a working AI product in 30 days with instrumentation, pilot users, and measurable outcomes.
The Problem with Most AI MVPs
Most AI startups spend 6-12 months building before they get real user feedback. By the time they launch, they've built the wrong thing, burned through capital, and lost momentum.
The Hidden Layer approach is different: ship a working v1 in 30 days, instrumented and piloted with real users.
The 30-Day Framework
Week 1: Diagnose
Before writing a single line of code, get crystal clear on:
- ICP and buyer persona: Who exactly is the buyer? What triggers them to look for a solution?
- Workflow map: What's the current process? Where does it break?
- Success metrics: What does "better" look like? How will you measure it?
- Data sources: What data do you need? Where does it come from?
- 30-day build plan: What's the absolute minimum that proves value?
Output: A one-page spec with buyer, workflow, metrics, and build plan.
Week 2-3: Build
Focus ruthlessly on the core value loop:
- User input → What's the minimum data you need from the user?
- AI processing → What's the simplest model/prompt that works?
- User output → What's the one thing that proves value?
Don't build:
- User management (use magic links or OAuth)
- Complex UI (start with forms and tables)
- Scalable infrastructure (use serverless, pay per use)
- Multiple features (one workflow only)
Do build:
- Instrumentation from day one (track everything)
- Error handling and logging
- A way to collect feedback
- A simple onboarding flow
Output: A working prototype that completes the core workflow.
Week 4: Pilot
Get 5-10 real users through the flow:
- Onboard manually: Walk them through it, watch them use it
- Collect qualitative feedback: What worked? What didn't?
- Track quantitative metrics: Time saved, accuracy, completion rate
- Document learnings: What surprised you? What would you change?
Output: Pilot results with metrics and iteration plan.
What "Done" Looks Like
After 30 days, you should have:
- A working product that completes one valuable workflow
- 5-10 pilot users who have used it
- Instrumentation that tracks key metrics
- Qualitative and quantitative feedback
- A clear iteration plan for the next 30 days
Common Mistakes
Mistake 1: Building for scale before proving value
You don't need Kubernetes. You need users who care.
Mistake 2: Building multiple features
One workflow, done well, is infinitely better than three half-baked features.
Mistake 3: Skipping instrumentation
If you can't measure it, you can't improve it. Build tracking from day one.
Mistake 4: Waiting for "perfect"
Ship something embarrassing. You'll learn more in one week with real users than in six months of planning.
The Hidden Layer Difference
When we run an "MVP in 30 Days" sprint, we bring:
- Product expertise: We've shipped dozens of MVPs. We know what to cut.
- AI infrastructure: Pre-built evaluation, routing, and cost controls.
- GTM readiness: Pilot plan, onboarding flow, and feedback loops baked in.
- Instrumentation: Dashboards and metrics from day one.
Ready to Ship?
If you can commit to shipping in 30 days, we can help you build it.