AI coding agents are hard to supervise safely across projects
Developers running coding agents across repositories struggle to see what agents are doing, keep parallel work isolated, and review or recover changes when things go wrong. Current workflows often mean babysitting CLI sessions, maintaining custom rules, juggling worktrees, or manually reviewing and correcting output. A local control layer could improve visibility and safety, but it would not fix model quality, provider-imposed context limits, or usage caps.
For developers running multiple AI coding agents across repositories. Mentioned from Jan 2024 to Sep 2026 on Bluesky, product forums, GitHub and Hacker News.
92 different people described this problem in 87 separate discussions.
- Indie fit
- 6.0/10
- Pain
- 6.3/10
- Frequency
- 10.0/10
- Willingness to pay
- 1.8/10
- Momentum
- 6.9/10
- Who pays
- Professionals
- Competition
- High
- Build difficulty
- High
What people said
Quoted word for word. Follow a link to read the whole discussion.
whenever i try to parallelize, they clash while editing files simultaneously, i lose mental context of what's going on, they rewrite tests etc
deepdarkforest on Hacker NewsJul 2025Improvements in long duration, multi-turn unattended development would save me lot of babysitting and frustrating back and forth with Claude Code/Codex. Which currently saps some of the enjoyment out of agentic development for me and requires tedious upfront work setting up effective rules and guardrails to work around…
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