TLDR
Most AI coding failures are predictable and preventable. The big ones: skipping the brainstorm, no quality rules, tasks too big, not enforcing the 8/10 minimum, circular debugging without starting fresh. Knowing the failure patterns lets you catch them before they become expensive.
Failure Pattern 1: Skipping the Brainstorm
Symptoms: Started building immediately. Now 3 weeks in and the scope is unclear, the architecture has been refactored twice, and the sprint plan doesn't match what's been built.
Recovery: Stop building. Open Claude. Describe the current state. Have the brainstorm you should have had at the start. Generate or update your foundation docs. Resume with clarity.
Failure Pattern 2: Weak Quality Rules
Symptoms: Tests are inconsistent (some tasks have them, many don't). Code style varies. AI keeps doing something you told it not to.
Recovery: Tighten your .clinerules. "Write tests" → "Unit tests are mandatory for all business logic. Minimum 3 tests per function. No exceptions." Then run a phase audit to find the gaps and fix them.
Failure Pattern 3: Tasks Too Big
Symptoms: AI produces 500+ lines for a single task. Some things work, some don't. Confidence score is 6/10. Not sure what to fix first.
Recovery: Split the task into subtasks, each with its own spec. Start a fresh conversation for each subtask. Apply the 8/10 rule to each one before moving to the next.
Failure Pattern 4: Ignoring the 8/10 Threshold
Symptoms: Multiple tasks at 6–7/10 "because we'll fix it later." Now you're on Task 15 and half the earlier tasks are broken in ways that affect everything built on top of them.
Recovery: Stop forward progress. List all tasks below 8/10. Fix them before continuing. Yes, it's painful. But it's less painful than building a tower on a cracked foundation.
Failure Pattern 5: Circular Debugging
Symptoms: Been trying to fix the same bug for 2+ hours. AI keeps suggesting variations of the same broken approach. Each fix introduces a new problem.
Recovery: Ask AI to write a context rescue document. Start a completely fresh conversation. Provide just the task doc, not the debugging history. Fresh eyes with no baggage.
Failure Pattern 6: Documentation Drift
Symptoms: ARCHITECTURE.md describes the schema that existed 3 sprints ago. AI generates code based on outdated schemas. Errors. Hours of debugging.
Recovery: Run a documentation audit (fresh Claude conversation). Ask it to compare the docs to the current codebase. Update everything. Add "update docs" to your task completion checklist.
Failure Pattern 7: AI Takes Over Decisions
Symptoms: Not sure how a feature works. AI made architecture choices you don't understand. Can't explain what the code does to anyone else.
Recovery: You're the architect. Ask AI to explain every major decision. Update ARCHITECTURE.md with explanations. If something was a bad choice, document why and either fix it or add a note that it needs fixing.
The Universal Recovery Protocol
- Stop adding new features
- Assess current state — what works, what doesn't, what's unclear
- Update your foundation docs to match reality
- Run a phase audit on the current codebase
- Create tasks for every fix needed
- Fix systematically, applying the 8/10 rule to each fix
- Resume with clarity
This protocol has saved projects that looked unsalvageable. The key is stopping the bleeding before it gets worse.