Your AI Coding Agent Needs a Dev Environment Too

I've been watching how AI coding agents actually work — not the demos, the real day-to-day usage — and something keeps standing out: we've optimized the wrong things. Agents have great editors now. They can read files, write files, run tests, search codebases, manage git. The tooling around code manipulation is genuinely impressive. What they can't do — what nobody seems to talk about — is run a development loop against the services their code depends on. And if you've built anything nontrivial in the last decade, that's where most real development happens. The development loop problem When you build a feature that talks to an external API — Stripe for payments, your team's user service, a third-party data provider — you need that service running and responding while you develop. You write code, test it, see what the API returns, adjust, test again. Tight loop. AI agents do this loop too. Except faster. A lot faster. A developer might hit an API endpoint 20–30 times while building a pa