Keeping AI workflows maintainable

AI workflows need boring infrastructure around them: versioned prompts, clear review steps, source records, and a visible fallback path. Without that, teams get impressive demos and fragile operations.

Treat every generated output as part of a workflow, not the whole workflow. Decide what the system should know, what it should ask, and when a human should approve or correct the result.

Maintainability comes from making the work inspectable. When people can see inputs, decisions, and outputs, they can trust the system enough to improve it.