GitHub spent this month turning the coding agent into a dropdown. Under the "Agent HQ" banner, Copilot now lets you run Claude or Codex — alongside Copilot's own agent — inside VS Code, the JetBrains IDEs, and Copilot CLI, chosen from an agent picker per task rather than wired in when you picked your tool (GitHub). If you build software with one, the practical question isn't "which is best" — it's "what does a swappable model actually free me from, and what still holds me?"
Short answer, up front: the model is now genuinely portable, and that kills the cheapest kind of lock-in. But the lock-in moved one layer up — into the harness you configure around the model — and that layer is the one your team actually depends on.
What shipped#
The rollout landed in pieces over June and July. Claude arrived as an agent provider in the JetBrains IDEs in a June preview (changelog); Codex followed on July 7 as a selectable provider (changelog). The mechanics are deliberately boring: install the provider's CLI on your machine, point Copilot at its path in settings, and pick the agent from the session picker. No re-tooling, no new editor.
Two quieter changes in the same wave matter more than the headline. First, approval settings are now configurable for Copilot CLI sessions, and hooks and MCP servers can be managed directly in "Agent Customizations" for those sessions — the guardrails and the tool surface are becoming first-class config. Second, GitHub expanded bring-your-own-key (BYOK) in the JetBrains IDEs (changelog), so the model choice extends to your own provider credentials. Alongside it, agentic browser tools went generally available in VS Code — agents can navigate, screenshot, and validate a running web app in-editor (changelog).
The lock-in didn't leave — it moved up a layer#
The instinct is to read "pick your agent" as the end of vendor lock-in. It isn't, and it's worth being precise about why, because the mistake costs you later.
Swapping the model was always the shallow layer. It's the same lesson we drew in Provider-Agnostic AI Agents: the lock-in isn't where you think — a one-line model swap is true for a chatbot and misleading for an agent, because the behavior you actually tuned lives above the model call. Agent HQ makes the shallow layer trivially portable, which is real and useful. But look at what it simultaneously pulls into GitHub's surface: your approval rules, your hooks, your MCP server list, your custom instructions. That's the harness — and the harness is what your team builds muscle memory and automations against.
A coding agent's value on your codebase is 20% the model and 80% the scaffolding: which files it's allowed to touch, what it must ask before running, which internal tools it can call, the conventions baked into its instructions. When that scaffolding lives only in a vendor's settings pane, "the model is a dropdown" is cold comfort — you can change the engine, but the chassis is bolted to one garage.
The founder move#
Two habits keep the freedom real:
- Treat the model as swappable, and prove it monthly. The whole point of a dropdown is that benchmarking Claude vs Codex is now a click, not a migration. So actually do it — on your real repo, on the tasks you run (a multi-file refactor, a flaky-test fix, a dependency migration), scored on cost per completed task, not a public leaderboard. We walk through why one headline number lies in How to Benchmark LLM Inference; the same discipline applies to agents. Cheaper-per-token loses to fewer-retries every time.
- Keep the harness in version control you own. Put your hooks, MCP config, and custom instructions in files in your repo and treat GitHub's Agent Customizations as a place you load them into — not the only place they exist. That's the difference between a model choice that's portable and a workflow that's captured. If you're weighing tools more broadly, Cursor vs Windsurf vs GitHub Copilot vs Claude Code frames the four as architectural postures — and the posture, not the model, is what you're really choosing.
Agent HQ is a genuinely good change: it makes the expensive experiment cheap. Just don't mistake a portable engine for a portable car. Own the chassis.
