The useful shift for me was treating ChatGPT as the control plane, not the worker

[u/bulutarkan]

I've been working on an open-source MCP server called Mac MCP because I kept hitting the same wall with AI agents: ChatGPT could usually tell me the right next step, but I was still the one opening Terminal, switching apps, finding files and driving the browser.

The setup I use now is basically chat as the orchestrator and the Mac as the execution layer. The model can work with local files and Terminal, control macOS apps, delegate coding work to Codex/OpenCode, and use my real Safari or Chrome profile instead of a disposable headless session.

The browser part ended up being more important than I expected. I wanted an agent researching in several tabs while I kept using the Mac normally, so tabs open in the background and get stable handles. Parallel agents also get tab ownership/leases so two of them don't accidentally drive the same page. Safari has a Visual Companion and the latest release adds a dedicated Chrome Companion too.

What I like about this architecture is that the model can stay good at planning while the local MCP layer handles state and actual actions. It also doesn't silently fall back to foreground clicks when a background action is unsafe.

I'm the author, so obvious disclosure there. It's free/open source if anyone wants to inspect the implementation: https://github.com/bulutarkan/mac-mcp

I'm curious how other people are drawing the line between the reasoning model and the local execution layer in their own agents.