Developer shares 7-point checklist for safely reviewing AI coding agent output

A developer has published a practical checklist for reviewing AI coding agent output, addressing a growing bottleneck teams face as agents produce large volumes of code changes. The checklist covers seven key concerns, including viewing changes as diffs, knowing the agent's working directory, tracking commands run and network access, verifying credential sources, and ensuring reproducibility. The author learned the hard way after letting an agent work directly in a live codebase, which led to an unnoticed dependency change that only surfaced at deployment. Based on these lessons, they built an open-source tool called TaskHandoff, a self-hosted control plane that gives each task its own isolated workspace and delivers Git changes as reviewable branches. The project is licensed under Apache-2.0 and documented at docs.thandoff.com.