How to Split AI-Drafted Docs from Human-Owned Claims in API Pipelines

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A structured documentation pipeline can reduce errors by clearly dividing what AI models may draft from what human reviewers must own. Factual, code-verifiable content such as function signatures, CLI flags, and error codes can be safely drafted by AI, while normative claims like deprecation timelines, security properties, and behavioral guarantees require human sign-off. The pipeline runs on every pull request touching a public API and includes four steps: drafting reference sections, validating symbols against the codebase, classifying claims by ownership, and committing with a reviewer sign-off. A drift-check script compares documented names against the actual code structure, catching mismatches before they reach a human reviewer. This division of labor addresses a structural gap in most merge pipelines, where documented surfaces are never automatically compared against the actual code surface.

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ProgrammingDEV Community ·

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ProgrammingDEV Community ·

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ProgrammingDEV Community ·

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