Building the MVP
Ship the smallest thing that delivers the full magic trick.
An AI MVP isn't a stripped-down version of your vision. It's one perfect workflow that makes someone's jaw drop.
What you'll learn
- How to scope an AI MVP that ships in 2-4 weeks
- The one-workflow rule for AI products
- Handling AI failures gracefully
- Building trust through transparency
The One-Workflow Rule
Your MVP does one thing. Not three features. Not a platform. One workflow, end to end, from input to output. If your product summarizes documents, the MVP takes a PDF and returns a summary. That's the entire product on launch day.
The temptation with AI is to build a "do anything" tool. Resist this. ChatGPT already exists. Your product wins by being the best at one specific job, not mediocre at twenty.
The AI MVP Checklist
Input capture: How does the user give you data? File upload, text input, API connection, or screenshot. Make it frictionless. Every extra step is a drop-off point.
Processing: Your AI pipeline. Prompt engineering, context assembly, model call, output parsing. This is your engine. Optimize for reliability over cleverness.
Output delivery: How does the user get the result? In the UI, via email, as a downloadable file, through a Slack notification. Match the delivery to the user's workflow — don't make them come to you.
Error handling: AI fails. Models hallucinate. Tokens run out. Your MVP must handle these gracefully. A clear error message and a retry button are minimum requirements.
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