Where would a control layer actually fit in your AI coding workflow?

[Keesan12]

We built MartinLoop to put hard budget caps, verifier gates, and inspectable run records around AI coding agents.

The open question is where that control layer is most useful in real teams.

If you are using Claude Code, Codex, Cursor, Cline, Aider, GitHub Actions, or your own wrappers, I would love your blunt take on any of these:

• Where do you want governance to live: local CLI wrapper, MCP boundary, CI gate, or somewhere else?
• What is the first failure mode you most want stopped: runaway spend, false-success claims, flaky retry loops, unsafe file changes, or weak auditability?
• What would make this worth installing in under 10 minutes?

If you want a fast way to evaluate it, two easy starting points are:

npm install -g martin-loop
npx martin-loop doctor

or:

npx -y @martinloop/mcp

If you try it, feel free to reply with:

• your stack
• where it felt strong
• where it felt annoying or unclear
• the one integration you would most want next

The more concrete and critical the feedback, the more useful it is.