What changes between a prototype and production?

Make the surrounding workflow real

A prototype may use a prepared document and a single user. Production needs the right inputs to arrive consistently, the right permissions to apply, and the output to reach a useful destination. Map the integrations and the people who own them. Agree what happens when a source is late, an API fails, or the model cannot produce a usable response.

Turn quality into a repeatable check

Create a set of representative tasks and expected properties of a good result. Include incomplete inputs, ambiguous questions, and cases that should be escalated. Keep the evaluation connected to the business objective rather than relying on the appearance of an individual answer. Re-run relevant checks when prompts, models, tools, or knowledge sources change.

Make changes reversible where possible

Version the configuration that affects behavior and record the release being used. Roll out changes to a controlled scope and watch the result. Define the route back to a known working version and how in-flight tasks are treated. Reliability comes from understanding state and dependencies as much as from the model itself.

Assign an owner for the next day

Someone must review issues, update approved knowledge, manage access, and decide whether an improvement should ship. Establish these responsibilities before launch. A handover should include operating guidance, evaluation examples, and the context behind important decisions. The aim is a capability your team can keep using and improving.