Build a self-improving software workflow

A self-improving software workflow should begin with a narrowly defined, recurring maintenance problem, a reproducible failure, clear ownership, and an established human review process, using automation initially to gather evidence and propose corrections rather than expanding its authority. The illustrative example involves an agent incorrectly editing generated files instead of their source inputs, with success defined by changing the proper source, regenerating outputs, and passing consistency checks independently. Teams should establish explicit scope, permissions, stop conditions, and evidence requirements, while retaining sensitive information securely and avoiding automated decisions when ownership, failures, or duplicate reports are uncertain. Durable improvements should be small, evidence-based, versioned instructions or reusable procedures such as documented generator commands and validation steps, rather than vague reminders or records of every prior interaction. Validation should separately test the immediate patch and the reusable lesson through clean reproductions, neighboring cases, repository-specific checks, and continued human approval. After acceptance, teams should monitor later tasks, including blocked and failed runs, evaluate changes on tasks not used to develop the correction, watch for new costs or stale guidance, and expand to additional repositories or triggers only when the workflow demonstrably reduces repeated human redirection.

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