Thirty days is enough to ship a real AI MVP — but only if you treat the deadline as a scoping tool, not a stretch goal. The teams that make it aren't faster coders; they're more ruthless about what they don't build. Here's a week-by-week plan that has taken AI ideas to paying-user-ready in a month.
Before day one: pick one job
An AI MVP that tries to be a platform ships nothing. Choose a single job the AI does — summarize these documents, answer questions over this knowledge base, draft this kind of content. Write it as one sentence. If you can't, your scope is still too wide, and no schedule will save you.
Decide the shape too: is this a workflow (fixed steps, predictable) or does it genuinely need an agent? Almost always, it's a workflow. Build that.
Week 1: prove the core AI loop
Ignore auth, billing, and UI polish. Prove the one thing everything depends on: does the AI actually do the job well enough?
- Wire up the model call and get a rough prompt working end to end.
- If it's a RAG feature, stand up retrieval with pgvector on PostgreSQL and test it against real questions.
- Build a tiny internal harness — even a script — to eyeball output quality on real inputs.
If the AI can't do the job by end of week one, that's the most valuable thing you could learn this early. Fix the approach now, not in week four.
Week 2: wrap it in a thin product
Now make it usable. Put the core loop behind the smallest real interface:
- A Next.js front end with just the screens the core flow needs.
- Auth and data on Supabase so you skip building infrastructure.
- A typed TypeScript service around the model call, with logging and retries.
Resist every settings page, admin panel, and "nice to have." They are week-five problems, and week five doesn't exist.
Week 3: harden the AI
A demo becomes a product when it handles being wrong. This week is about reliability:
- Ground answers in your data and constrain outputs to formats you can validate.
- Add a fallback for low confidence — a graceful "I'm not sure" beats a confident hallucination.
- Put in guardrails: scope the model, filter inputs, and gate any real action behind confirmation.
- Track cost per request and cache repeats so the bill doesn't surprise you at launch.
Week 4: polish the critical path and ship
Spend the final week making the signup-to-value path feel finished — and nothing else. Fix the rough edges users will actually hit, seed sample data so the product isn't empty on first login, and set up basic analytics so you can learn from real usage.
Then launch. Not when it's perfect — when the core path works and is stable. The whole point of a 30-day AI MVP is a fast, honest answer to one question: does this deliver enough value that people want more?
The shortcuts that make this possible are all the same idea: buy infrastructure instead of building it, and defer everything off the critical path. If you want a team that can hold this line and ship your AI MVP in a month, let's talk.
Originally published on the Doktouri Agency blog. We build web, mobile, SaaS, and AI products — let's talk.
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