Artifacts Over Files: Rethinking Agent Output Persistence for Production

As AI agents move from local development to production, relying on local filesystem paths for output fails—containers restart, serverless environments have ephemeral storage, and retries create duplicates. Production-ready agents require treating outputs as artifacts (file plus context) with metadata like run IDs and expiration rules, rather than simple filesystem paths that users cannot access.