From feature idea to AI MVP

Most teams overbuild their first AI release. The fastest path is to scope one workflow, define one success event, and optimize for confidence over feature count.

Start with one high-friction workflow

Choose a user task that is frequent, painful, and already partially documented in your support channels.

• Keep the first release to a single workflow.
• Design for a clear handoff when confidence is low.
• Track completion rate and manual correction rate from day one.

Design the fallback before the prompt

AI features fail when fallback behavior is undefined. Build deterministic fallbacks first so users never hit dead ends.

Instrument everything

Use lightweight logging around prompt input, model output, tool calls, and user corrections. The first two weeks are mostly about feedback quality.