A developer-led checklist for supervising AI coding agents has been published to help teams manage the supervision bottleneck that emerges when agents work across multiple files and sessions.

What happened: Useful Softworks has released a public repository containing a practical checklist and guidance for overseeing AI coding agents (such as Claude Code, Cursor, and Aider) across branches, worktrees, code reviews, and approval gates. The checklist covers eight core steps: defining scope before the agent starts, isolating work in branches or worktrees, knowing which files the agent may touch, establishing pause/interrupt capability, reviewing diffs before merge, verifying tests, checking for leaked credentials, and requiring human approval before changes reach the main branch.

Why it matters: As AI coding agents become capable enough to run sessions lasting hours and touch many files in parallel, the bottleneck has shifted from code generation to supervision—knowing which agent is working on what, who has reviewed it, and when human intervention is needed. Most developers do not have good answers to these questions, making this checklist a response to a real gap in current developer workflows.

What to watch: The repository is maintained by Useful Softworks and includes detailed documents on failure modes, what worktrees do and do not solve, and sample review-log formats. The team is also developing AgentLeash, a local-first control layer for AI coding agent supervision, with private beta applications open at https://agentleash.dev/.