Your AI prototype works. Is it a product yet?

A happy path is not a system

A prototype proves possibility. A product must survive missing inputs, slow dependencies, failed model calls, and users who do not follow the script. Start by mapping the failure paths of one critical user journey.

Make the boundaries explicit

Keep UI, application logic, model orchestration, and data access separate. Validate inputs before they cross each boundary. Treat model output as untrusted data, and validate its structure before using it.

A prototype proves possibility. A product survives reality.

Know what good looks like

Create a small evaluation set drawn from realistic tasks, including edge cases. Track correctness, latency, and cost together. A prompt change that improves one example can quietly break another.

Ship the smallest reliable slice

Choose one end-to-end workflow. Add authentication where needed, narrow data permissions, timeouts, and clear recovery states. Launch that slice before adding a second agent or another integration.