GitHub Agent HQ and the Moment AI Agents Became Default

Every week brings another model release, another research demo, another promise. Most are interesting. A few change defaults.

GitHub Agent HQ is one of those. When agents live inside the place where teams already review, plan, and ship code, they stop being experiments. They become the workflow.

The News in One Sentence

GitHub launched Agent HQ in public preview, bringing Anthropic Claude and OpenAI Codex into Copilot so teams can run multiple AI agents side by side inside GitHub, GitHub Mobile, and VS Code.

Why This Is the Hottest Story Right Now

Distribution beats novelty. GitHub is the center of gravity for software teams. It is where issues are triaged, pull requests get reviewed, and history gets recorded. Embedding agent workflows there is a bigger shift than any single benchmark win.

Agent HQ also lowers friction. You can start agent sessions from issues, pull requests, or the Agents tab, which means the work stays anchored to the task, not to a separate chat window.

What Agent HQ Actually Does

GitHub is positioning Agent HQ as a control room for agentic workflows. In practical terms, it gives teams a shared place to run and compare agents without leaving the repo context.

• Start agent sessions directly from issues or pull requests
• Run agents inside GitHub, GitHub Mobile, or VS Code
• Compare results from different providers on the same task
• Keep the work tied to the repo and the review process

This is the bridge between experimental agent tools and the workflows that ship production software.

Claude and Codex Are First-Class Inside GitHub

GitHub is not picking a single model. It is putting top-tier agents side by side. In the public preview, Claude and Codex are available to Copilot Pro+ and Copilot Enterprise users, with no extra subscriptions required. Each agent session consumes one premium request, which keeps cost and usage visible.

GitHub also signaled that more partners are on the way, including Google, Cognition, and xAI. That makes the platform strategy clear. Let teams choose the right agent for the task, then manage it in one place.

What This Changes for Real Teams

This is how I see it landing inside production orgs.

1. Delegation becomes normal. Teams will create tasks with the expectation that an agent can do the first pass.
2. Review becomes the bottleneck. The most valuable skill is now judgment, not typing speed.
3. Model choice becomes tactical. You can route design, refactor, or test tasks to different agents and compare outputs.
4. Work gets closer to the repo. When the agent lives in GitHub, context and accountability stay in one place.

My Takeaway

GitHub Agent HQ is the strongest signal yet that AI agents are moving from side tools to the default workflow. This is not just a new model. It is a new place for models to live.

If your team already uses GitHub for everything, this is the moment to pilot agentic workflows in the same space you already trust. The teams that learn to supervise agents inside their existing process will move first.