Shipping an AI MVP in 2 Weeks: A Step-by-Step Guide
The exact playbook we use for client AI MVPs that need to validate before scaling.
By Creative Genius
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7 min read
If you can't ship an AI MVP in two weeks, the scope is wrong. Most teams fail not by going too fast but by trying to ship too much. Here's the exact playbook we run on every client engagement.
Week 1 — Define and prototype
- Day 1–2: Problem statement in one sentence + single success metric. If you need a paragraph, the scope is too big. Cut.
- Day 3–4: Prototype against OpenAI or Anthropic directly. No framework, no orchestration library, no vector database unless absolutely required. The goal is to learn, not to engineer.
- Day 5: Three live user tests with real target users. Watch them use it. Take notes silently. The feedback in the first ten minutes will reshape your roadmap.
Week 2 — Harden and ship
- Day 6–8: Add the boring infrastructure — auth, rate limiting, error handling, logging, the one or two integrations that came up in user tests.
- Day 9–10: Production deployment with basic observability. Langfuse for traces, Sentry for errors, a simple dashboard for daily active use.
- Day 11–14: Iterate on real usage. Ship daily. Watch the metric you defined on day 1.
What to deliberately leave out of v1
- Multi-tenancy beyond what one customer needs.
- Admin dashboards (the team can use the database).
- Fancy retry logic (let things fail loudly).
- Any "AI agent" abstraction (a sequence of LLM calls is fine).
- Custom UI for the AI part if a chat or form will do.
The mindset shift
MVPs are not "v1 with fewer features." They're a different category of product whose only job is to test a hypothesis. If yours has more than one core hypothesis, ship the first one first, learn, then ship the second.
Where 2 weeks turns into 6
Three traps:
- Choosing a framework on day 1 instead of prototyping in plain code.
- Building evals before you have anything to evaluate.
- Trying to handle every edge case before any happy path is live.
Bottom line
Two weeks is enough if you ruthlessly cut scope and validate on real users. Anything longer and you're building, not learning.