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To detect design drift, you can run an automated semantic audit that compares codebase changes against original proposals and PRDs. This process ensures code integrity by identifying where the implementation no longer matches the intended design without manual oversight.

A semantic audit is an automated verification process that performs a 6-dimensional check for design drift and documentation drift. It ensures code compliance by validating that the actual implementation matches the intended design specifications and PRDs.

You automate code verification by running a structured review pipeline that conducts structural, semantic, and behavioral checks. This validates syntax, performs end-to-end scenario testing, and generates a detailed quality report for developer actions.

Yes, automated verification can check documentation freshness as part of its structural verification process. It identifies documentation drift, ensuring that technical docs remain aligned with recent codebase changes without manual review.

The best way to audit behavioral compliance is through behavioral verification, which executes end-to-end scenarios. This ensures the code behaves as expected under varying conditions and summarizes outcomes in a detailed quality report.

Yes, original proposals and PRDs are required as baseline inputs for the semantic audit. The automated testing process compares actual codebase changes against these documents to accurately detect design drift and ensure code integrity.