How to keep a knowledge base up to date when the product changes every day

Rapid product development, accelerated by AI coding agents, has made it difficult for support knowledge bases to remain accurate, as traditional methods such as pull-request documentation checkboxes, quarterly audits, engineering changelogs, and customer-reported errors cannot reliably keep pace with multiple daily releases. The author argues that codebase-scanning AI tools introduce risks by potentially exposing internal details, lacking visibility into the actual user interface, and requiring broad source-code access. As an alternative, the article proposes a “product agent” that uses the live product through a standard user account, continuously validates documentation steps against visible workflows, identifies stale or missing articles, and drafts updates for human approval. Frigade says it uses this approach internally after releases to maintain its own help center and plans to offer the capability to other companies.

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