FG-0503 Asset Review Pipeline
Description
Establish a multi-stage, human-in-the-loop review process for AI-generated assets. Not everything an AI produces should go directly to production. The Asset Review Pipeline defines stages: generate, review, approve, archive. Different asset types may require different review rigor: code might need automated testing plus human review; creative content might need brand consistency checks; documentation might need accuracy verification.
Implementation
Define asset categories and the review stages each requires. Establish who reviews at each stage (human, specialized agent, automated tool). Create a clear approval mechanism that distinguishes 'reviewed' from 'approved.' Archive approved assets in a versioned, retrievable system. Track review throughput to identify bottlenecks.
Success Indicators
- No AI-generated asset reaches production without defined review
- Review stages are proportional to asset risk and impact
- Review throughput is measured and optimized
- Archived assets are retrievable and versioned
Failure Modes
- Review bottleneck: all assets wait for one reviewer
- Review theater: reviewing without actually catching issues
- No review for 'low risk' assets that turn out to be impactful
- Review process so slow it impedes the collaboration's throughput advantage