Nine Common AI Coding Agent Failure Patterns and Pre-Execution Validation

A Reddit post from r/LocalLLaMA details nine failure patterns observed in AI coding agents and proposes a validation approach to catch them before code execution.

Identified Failure Patterns

The author lists these specific issues:

• C1 — Incomplete enum handling: Agent references status values that don't exist in the codebase.
• C2 — Silent null paths: Optional parameters get skipped silently with no documentation.
• C3 — SSE auth pattern mismatch: Browser EventSource can't send custom headers — agent uses wrong authentication.
• C4 — Unbounded text fields: No truncation on columns that receive full task descriptions or diffs.
• C5 — Event/DB race condition: SSE event fires before the DB write completes. Frontend queries empty row.
• C6 — Schema/ORM mismatch: SQL type says nullable, ORM field says required.
• C7 — Untestable expectations: Test requirements with no implementation path in the spec.
• C8 — Non-idempotent inserts: Retry logic creates duplicate rows.
• C9 — Hallucinated imports: Module doesn't exist in the codebase.

Validation Approach

The author states they now run these patterns as a validation pass after planning and before execution. This approach reportedly catches approximately 70% of failures before any code runs. The post concludes by asking if others are building similar pre-execution validation into their agent pipelines.