64% of Unattended Claude Code Agent Failures Traced to Git Push, Not AI Errors

A developer team running 13 scheduled GitHub Actions workflows without human oversight logged 72 job failures since June, finding that 46 of them occurred at the git push stage rather than during model inference or API calls. Only 2 failures were attributed to the core task each agent was designed to perform, challenging the common assumption that AI decision-making is the primary risk in automated pipelines. One high-frequency polling job accounted for 60 of the 72 failures, largely because it ran often enough to collide with concurrent write operations. A concrete example involved a duplicate article being published after an idempotency key existed only in an uncommitted local file for 99 minutes, leaving the remote repository unaware the task had already been completed. The team concluded that engineering effort in unattended agent setups is better directed at write serialization and state consistency than at prompt robustness or tool-call error handling.