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What you are probably seeing
You notice that your initial prompt works for simple tasks but fails when the logic gets complex.
You see your local repository filled with broken files after the agent tries to implement the full feature set in one go.
Why it happens
The agent lacks a structured review process to catch logical gaps before code generation begins.
Without a smoke test phase, the agent ships code that passes the initial prompt but fails in the real environment.
What changed recently
Step by step
1. Draft a detailed implementation plan document before giving any coding instructions to the AI agent.
2. Ask a second AI model or a senior developer to red-team the plan and list potential failure points.
3. Review the red-team findings and update the plan to address every identified edge case and logical gap.
4. Run a local smoke test script on a minimal version of the planned feature to verify the core logic works.
5. Set up a merge gate in your version control system that requires human approval before the agent commits code.
Ways to go further
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Other problems readers raise
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