I Built an AI Agent With Claude Code, Then Had Claude Review Its Own Work

Short summary

The author built an open-source AI agent project with Claude Code that auto-generates a Work Breakdown Structure from a stated goal, then had Claude independently review its own output. The review confirmed the safety design was genuinely implemented but also disclosed real limitations: deployment phases are simulations, the self-optimization index is a rule-based score, and a real auth bug was found. The takeaway is that AI self-review can surface honest limitations when left unedited.

• •Built an open-source WBS generator with Claude Code combining a reasoning agent and a deterministic nine-stage Python pipeline
• •Claude's self-review confirmed safety features were real but also disclosed limitations: deployment is simulated, self-optimization is rule-based
• •Unedited AI self-review can produce a useful quality signal by surfacing honest limitations alongside positive findings

Generated with AI, which can make mistakes.