Debug production issues with AI agents
Agents are strongest at debugging when they're forced to be systematic: reproduce, isolate, hypothesize, verify. Left unprompted they guess-and-check like a junior at 2am. The fix is encoding the discipline as a skill the agent must follow.
THE PAIN
- ✗ Agents propose fixes before understanding the bug
- ✗ Context evaporates between debugging sessions
- ✗ The same class of bug recurs because nothing was written down
THE PLAYBOOK
- 01
Force reproduction first
The skill's hard gate: no fix proposals until the failure reproduces in a minimal case.
- 02
Isolate with bisection
Have the agent binary-search commits, inputs, or config until the trigger is pinned.
- 03
One hypothesis at a time
Each hypothesis gets a falsifiable test before any code changes. The agent logs what it ruled out.
- 04
Write the post-mortem
The agent ends by appending the root cause and fix to a debugging journal — future sessions read it first.
RUNS ON
Prompt Ops: 150 Production Prompts
150 production prompts, annotated — the failure modes documented for every one.
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Skill Forge
43 production agent skills — plus the framework and test harness to write your own.
43 skills · 219 failure modes
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MCP Debug Kit
Fix MCP tools that never show up — layered diagnosis, error atlas, 5-client matrix.
2 skills · 10 failure modes
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Agent Guardrail Pack
Nine controls for agents you don't babysit — they refuse the commands that deleted other people's work.
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The Workflow Arsenal
Every paid kit — all nine, one price, plus every new kit for 12 months.
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