GitHub Launches Agent HQ: Unified Platform for Managing Multiple AI Coding Agents

GitHub's huge 'Agent HQ' upgrade brings Codex, Claude, and Jules together - here's how

Also: I got 4 years of product development done in 4 days for $200, and I'm still stunned But wait, you may ask (as I did), "Isn't Codex already integrated into GitHub?" I mean, I used it and wrote about it months ago. See, that was then and this is now. Months ago, in AI terms, is like decades to the rest of the world. GitHub is making some monster announcements, and Codex fits into those. It's the fit that's new, not the idea that Codex is available for GitHubbers. GitHub is announcing what they're calling their "next evolution," an agentic development platform. At the same time, OpenAI is announcing that Codex will be available directly from the paid GitHub Copilot Pro+ subscription. Alexander Embiricos, Codex product lead at OpenAI, says, "Our collaboration with GitHub has always pushed the frontier of how developers build software. The first Codex model helped power Copilot and inspired a new generation of AI-assisted coding." (Disclosure: Ziff Davis, ZDNET's parent company, filed an April 2025 lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.) According to an email conversation with the GitHub folks, I was told, "This is a move only GitHub can realize because it's the only place that combines the community, the code context, and the complete workflow needed to make any AI agent a truly impactful teammate." The core approach is what GitHub calls an "Agent HQ," where coders and AI agents work together. Given that many (maybe even most) developers build their projects using GitHub's source control and scaffolding, this is a fairly logical, if ambitious, extension. Also: 10 ChatGPT Codex secrets I only learned after 60 hours of pair programming with it One thought I had while writing this piece is that GitHub serves two key purposes for the software development world: a giant repository of open-source code (and some private code as well) and what is probably the single largest collaboration community in history (and that is not hyperbole). During my big four years of coding in four days project sprint, I talked about how coding with Codex did feel collaborative. Yes, granted, it was like collaborating with a brilliant, if stubbornly obtuse, colleague, but that's what collaborating with many developers is like anyway. So, if you think of AI agents as members of the programming team, then it makes sense that they be tightly integrated into the GitHub environment. But to make this work, GitHub and the various coding agent models can't be walled gardens. Also: The best AI for coding in 2025 (including a new winner - and what not to use) Mike Krieger, chief product officer at Anthropic, addresses this concern. He says, "We're partnering with GitHub to bring Claude even closer to how teams build software. With Agent HQ, Claude can pick up issues, create branches, commit code, and respond to pull requests, working alongside your team like any other collaborator." GitHub is announcing that they wish to welcome (their term) "every coding agent to integrate directly into GitHub." They're starting with OpenAI's Codex and Anthropic's Claude. I'm told that more coding agents will be integrated into GitHub in the coming months. Don't let this little bit of news float past you like all those self-satisfied marketing pitches we semi-hear and ignore. If it works and remains reliable, this is actually a very big deal. OpenAI's product lead Embiricos expanded on this: "We share GitHub's vision of meeting developers wherever they work, and we're excited to bring Codex to millions more developers who use GitHub and VS Code, extending the power of Codex everywhere code gets written." Also: The best free AI courses and certificates in 2025 - and I've tried them all Tech companies, especially the giant ones, often like to talk "open" but then do their level best to engineer lock-in to their solution and their solution alone. Sure, most of them offer some sort of export tool, but the barrier to moving from one tool to another is often huge. According to Kathy Korevec, director of product at Google Labs, "Developer tools should accelerate your workflow, not slow it down. With Agent HQ, Jules becomes a native assignee, streamlining manual steps and reducing friction in everyday development." She says, "This deeper integration with GitHub brings the Jules agent closer to where developers already work, helping them move faster and stay focused on building." The AI companies are engineering their own lock-in in fairly subtle ways. The most effective may well be the AI "memories" that chatbots are starting to build up about you and your conversations. The idea is that you can go back and the chatbots know who you are, what you're working on, your style, your interests, etc. On one hand, that's helpful. On the other hand, that's terrifying at an almost primal level. Also: What Bill Gates really said about AI replacing coding jobs But for productivity, the growing memories each AI has of you can save a lot of time. When I did my coding sprint, Codex did not maintain context across sessions, but you could engineer some context retention through the AGENTS.md file that many AI agents support. Over time, coding agents will build up their memories of you the same way your favorite chatbots do. So, the idea that you can continue to use your favorite agent or agents in GitHub, fully integrated into the GitHub tool path, is powerful. It means there's a chance developers might not have to suffer the walled garden effect that so many companies have strived for to lock in their customers. GitHub is introducing Mission Control, which is a "unified command center" for your agentic coding work. It's designed to be available in whatever coding space you're currently working in, whether that's GitHub, VS Code, or your favorite terminal program. This is all well and good (actually quite good), but I do have a bone to pick with GitHub product management. Mission Control? Really? Roughly a third of all developers use Macs, and Mission Control is a standard Mac feature. Did they not know this? Could they not have come up with a different name? Also: I put GitHub Copilot's AI to the test - its mixed success at coding baffled me Anyway, let's move on. Most AI coding agents now allow you to assign them a batch of asynchronous work projects that they're able to run with and report back when done. GitHub's new Mission Control can do that, too, except now you can do so across agents and agentic AI language models. So if you happen to like Claude Code for certain kinds of work, and Codex for other work, you can assign work from the same interface to both tools, track what's being done, and work with it. GitHub is adding new branch controls for better oversight of agent-created code and better management of AI-generated continuous integration (CI) tasks. They're also adding identity features that help clarify which agent is doing what, help manage access, and help control policies. Basically, they're giving you the same tools you'd use to manage human developers, but for AI agents. Also: How to use GPT-5 in VS Code with GitHub Copilot There are a lot more technical details in this unified announcement, but the core of it all is that GitHub is engineering coding agent-agnostic AI deep into the core GitHub experience. I think Anthropic's Krieger sums it all up nicely. He says, "This is how we think the future of development works: agents and developers building together, on the infrastructure you already trust." What do you think about GitHub's move to integrate AI agents like Codex and Claude directly into the core development workflow? Do you see agent collaboration as a genuine productivity boost or more of a novelty? How do you feel about the idea of an "Agent HQ" managing multiple AI teammates across tools? Is it exciting, a little unsettling, or both? And do you think GitHub's approach to keeping the platform agent-agnostic can really prevent the kind of lock-in we've seen from other tech ecosystems? Let us know in the comments below.

GitHub is launching a hub for multiple AI coding agents

GitHub is giving developers access to third-party AI coding agents with the launch of a new "Agent HQ." Instead of just using GitHub Copilot, developers will get to try OpenAI's Codex, Anthropic's Claude, Google's Jules, xAI, and Cognition's Devin within GitHub in the coming months. Developers with a GitHub Copilot subscription will be able to access a new "mission control" dashboard, where they can control, manage, and track multiple AI coding agents. "With the new set of AI controls, we're providing a control plane for all of the agent use on GitHub, whether you're using the GitHub coding agent or one of our partners' coding agents inside the platform," GitHub COO Kyle Daigle tells The Verge. GitHub's new Agent HQ will also allow developers to run multiple AI agents in parallel as they complete the same task. That way, developers can choose which agent's work they like the best. Ahead of Agent HQ's official launch, GitHub is making OpenAI Codex available to Copilot Pro Plus users who are part of the VS Code Insiders program. Additionally, GitHub is launching a few other tools, including a new Plan Mode in VS Code that uses Copilot to create a step-by-step plan for a task that its AI coding agent will later execute. GitHub is also adding a code review step to Copilot, allowing the agent to access tools, such as CodeQL, that it can use to evaluate code before passing it along to a developer.

GitHub launches Agent HQ to bring order to AI-powered coding

The platform unites AI coding agents in one environment to streamline enterprise workflows and enhance governance, security, and productivity. GitHub is taking a major step toward redefining enterprise software development with the launch of Agent HQ, a platform that lets developers manage and orchestrate multiple AI coding agents from OpenAI, Anthropic, Google, and others directly within the GitHub environment. The move suggests a new phase in enterprise AI adoption, as organizations look to govern, audit, and scale AI-driven coding within their existing DevOps workflows instead of using separate tools. The new platform introduces centralized mission control, code quality monitoring, and governance features that give CIOs and development leaders greater visibility into how AI contributes to code creation, review, and deployment across their organizations.

GitHub unites OpenAI, Google and Anthropic AI agents in one place to bring 'order to the chaos'

Thomas Dohmke, CEO of Microsoft-owned GitHub, speaks at the Collision conference in Toronto on June 27, 2023. Microsoft's GitHub unit on Tuesday announced Agent HQ, a new "mission control" interface that will allow software developers to manage coding agents from multiple vendors on a single platform. An artificial intelligence agent is a tool that can independently complete tasks on behalf of a user. Several companies, including GitHub, have built and released popular agents that are specifically designed for programming. Developers have a range of new capabilities at their fingertips because of these agents, but it can require a lot of effort to keep track of them all individually, said GitHub COO Kyle Daigle. Developers will now be able to manage agents from GitHub, OpenAI, Google, Anthropic, xAI and Cognition in one place with Agent HQ. "We want to bring a little bit of order to the chaos of innovation," Daigle told CNBC in an interview. "With so many different agents, there's so many different ways of kicking off these asynchronous tasks, and so our big opportunity here is to bring this all together."

GitHub's Agent HQ aims to solve enterprises' biggest AI coding problem: Too many agents, no central control

GitHub is making a bold bet that enterprises don't need another proprietary coding agent. They need a way to manage all of them. At its Universe 2025 conference, the Microsoft-owned developer platform announced Agent HQ. The new architecture transforms GitHub into a unified control plane for managing multiple AI coding agents from competitors including Anthropic, OpenAI, Google, Cognition and xAI. Rather than forcing developers into a single agent experience, the company is positioning itself as the essential orchestration layer beneath all of them. Agent HQ represents GitHub's attempt to apply its collaboration platform approach to AI agents. Just as the company transformed Git, pull requests and CI/CD into collaborative workflows, it's now trying to do the same with a fragmented AI coding landscape. The announcement marks what GitHub calls the transition from "wave one" to "wave two" of AI-assisted development. According to GitHub's Octoverse report, 80% of new developers use Copilot in their first week and AI has helped to lead to a large increase overall in the use of the GitHub platform. "Last year, the big announcements for us, and what we were saying as a company is wave one is done, that was kind of code completion," Mario Rodriguez, GitHub's Chief Operating Officer, told VentureBeat. "We're into this wave two era, and wave two is going to be multimodal, it's going to be agentic and it's going to have these new experiences that are going to feel AI native." What is Agent HQ? GitHub has already updated its GitHub Copilot coding tool for the agentic era with the debut of GitHub Copilot Agent in May. Agent HQ transforms GitHub into an open ecosystem that unites multiple AI coding agents on a single platform. Over the coming months, coding agents from Anthropic, OpenAI, Google, Cognition, xAI and others will become available directly within GitHub as part of existing paid GitHub Copilot subscriptions. The architecture maintains GitHub's core primitives. Developers still work with Git, pull requests and issues. They still use their preferred compute, whether GitHub Actions or self-hosted runners. What changes is the layer above: agents from multiple vendors can now operate within GitHub's security perimeter, using the same identity controls, branch permissions and audit logging that enterprises already trust for human developers. This approach differs fundamentally from standalone tools. When developers use Cursor or grant repository access to Claude, those agents typically receive broad permissions across entire repositories. Agent HQ compartmentalizes access at the branch level and wraps all agent activity in enterprise-grade governance controls. Mission Control: One interface for all agents At the heart of Agent HQ is Mission Control. It's a unified command center that appears consistently across GitHub's web interface, VS Code, mobile apps and the command line. Through Mission Control, developers can assign work to multiple agents simultaneously. They can track progress and manage permissions, all from a single pane of glass. The technical architecture addresses a critical enterprise concern: security. Unlike standalone agent implementations where users must grant broad repository access, GitHub's Agent HQ implements granular controls at the platform level. "Our coding agent has a set of security controls and capabilities that are built natively into the platform, and that's what we're providing to all of these other agents as well," Rodriguez explained. "It runs with a GitHub token that is very locked down to what it can actually do." Agents operating through Agent HQ can only commit to designated branches. They run within sandboxed GitHub Actions environments with firewall protections. They operate under strict identity controls. Rodriguez explained that even if an agent goes rogue, the firewall prevents it from accessing external networks or exfiltrating data unless those protections are explicitly disabled. Technical differentiation: MCP integration and custom agents Beyond managing third-party agents, GitHub is introducing two technical capabilities that set Agent HQ apart from alternative approaches like Cursor's standalone editor or Anthropic's Claude integration. Custom agents via AGENTS.md files: Enterprises can now create source-controlled configuration files that define specific rules, tools and guardrails for how Copilot behaves. For example, a company could specify "prefer this logger" or "use table-driven tests for all handlers." This permanently encodes organizational standards without requiring developers to re-prompt every time. "Custom agents have an immense amount of product market fit within enterprises, because they could just codify a set of skills that the coordination can do, and then standardize on those and get really high quality output as well," Rodriguez said. The AGENTS.md specification allows teams to version control their agent behavior alongside their code. When a developer clones a repository, they automatically inherit the custom agent rules. This solves a persistent problem with AI coding tools: inconsistent output quality when different team members use different prompting strategies. Native Model Context Protocol (MCP) support: VS Code now includes a GitHub MCP Registry. Developers can discover, install and enable MCP servers with a single click. They can then create custom agents that combine these tools with specific system prompts. This positions GitHub as the integration point between the emerging MCP ecosystem and actual developer workflows. MCP, introduced by Anthropic but rapidly gaining industry support, is becoming a de facto standard for agent-to-tool communication. By supporting the full specification, GitHub can orchestrate agents that need access to external services without each agent implementing its own integration logic. Plan Mode and agentic code review GitHub is also shipping new capabilities within VS Code itself. Plan Mode allows developers to collaborate with Copilot on building step-by-step project approaches. The AI asks clarifying questions before any code is written. Once approved, the plan can be executed either locally in VS Code or by cloud-based agents. The feature addresses a common failure mode in AI coding: starting implementation before requirements are fully understood. By forcing an explicit planning phase, GitHub aims to reduce wasted effort and improve output quality. More significantly, GitHub's code review feature is becoming agentic. The new implementation will leverage GitHub's CodeQL engine, which previously largely focused on security vulnerabilities, to identify bugs and maintainability issues. The code review agent will automatically scan agent-generated pull requests before human review. This creates a two-stage quality gate. "Our code review agent is going to be able to make calls into the CodeQL engine to be able to then find a set of bugs," Rodriguez explained. "We're extending the engine and we're going to be able to tap into that engine also to find bugs as well." Enterprise considerations: What to do now For enterprises already deploying multiple AI coding tools, Agent HQ offers a path to consolidation without forcing tool elimination. GitHub's multi-agent approach provides vendor flexibility and reduces lock-in risk. Organizations can test multiple agents within a unified security perimeter and switch providers without retraining developers. The tradeoff is potentially less optimized experiences compared to specialized tools that tightly integrate UI and agent behavior. Rodriguez's recommendation is clear: start with custom agents. Custom agents let enterprises codify organizational standards that agents follow consistently. Once established, organizations can layer in additional third-party agents to expand capabilities. "Go and do agent coding, custom agents and start playing with that," he said. "That is a capability that is available tomorrow, and it allows you to really start shaping your SDLC to be personalized to you, your organization and your people."

GitHub Unveils Agent HQ Amid Record 180 Million Developers Worldwide | AIM

GitHub unveiled its next-generation agentic platform to unify AI collaboration across tools like Copilot and VS Code. GitHub has introduced Agent HQ, its next evolution as an agentic platform, at GitHub Universe 2025, changing the way developers build and collaborate with AI. The company also revealed that it now has 180 million developers globally, its fastest growth ever, with one new developer joining every second. Of these, 21.9 million developers are building on GitHub in India, making it the second-largest developer community in the world after the United States. The company projected that the number will reach 57.5 million by 2030. According to GitHub COO Kyle Daigle, "India's rise as a global technology leader is undeniable, driven by its surging developer community and the new possibilities of agentic AI." He added that AI is "expanding what developers can do, accelerating how fast they ship, and empowering millions more in India to begin their software development journey." Agent HQ is GitHub's new open ecosystem that connects multiple AI agents, including those from Anthropic, OpenAI, Google, Cognition, and xAI, directly within GitHub through the existing Copilot subscription. The goal, Daigle said, is to make AI collaboration "powerful, secure, and seamlessly integrated into the workflow developers already trust." The new platform brings together a mission control feature that lets developers assign and track multiple AI agents, whether in GitHub, VS Code, mobile, or the CLI. This command centre enables them to manage AI-driven coding tasks, with finer controls over identity, access, and merge conflicts. A new VS Code update introduces Plan Mode, helping developers co-design step-by-step coding plans with Copilot before implementation. "Agent HQ isn't about the hype of AI. It's about the reality of shipping code," said Daigle. GitHub is also focusing on governance and transparency. A new Copilot metrics dashboard allows organisations to measure AI's impact on productivity, while the Code Quality preview provides visibility into maintainability and reliability across projects. Enterprise administrators gain more oversight through a dedicated agent control plane that governs AI access and model usage.

GitHub tackles vibe coding chaos with a control center for AI coding agents - SiliconANGLE

GitHub tackles vibe coding chaos with a control center for AI coding agents Microsoft Corp.'s GitHub unit is trying to get a grip on the growing mass of uncoordinated artificial intelligence coding agents, launching a new control center known as the Agent HQ. It's meant to serve as a kind of "mission control", where software developers can manage multiple third-party coding agents in one place. These coding agents are tools that are used by developers and software engineers to complete programming tasks autonomously with only minimal supervision. They've become incredibly popular in the last couple of years, giving birth to the concept of "vibe coding", where human developers simply prompt AI to write code on their behalf and review it afterwards to try and accelerate their productivity. Numerous companies, including GitHub itself, have released coding agents, and the result is that some teams are managing several of them at once. But when users have multiple agents all working on different tasks, it takes a lot of effort to keep track of them all, and that's what GitHub wants to help with. The GitHub Agent HQ gives developers a place to manage AI coding agents from companies including OpenAI Group PBC, Google LLC, Anthropic PBC, xAI Corp. and Cognition Inc., along with GitHub's own Copilot, all in one place. GitHub Chief Operating Officer Kyle Daigle told CNBC that the idea is to try and bring a bit more order to the "chaos of innovation" that has arisen from juggling so many agents. "With so many different agents, there's so many ways of kicking off these asynchronous tasks, and so our big opportunity is to bring this all together," he explained. Agent HQ provides users with a command center from where they can assign new tasks to agents, steer them and monitor their work. They'll be able to use it to observe what each agent is working on in real time, and correct its course if they see it going off track or doing something it shouldn't. It will also help developers to see which agents are more effective. For instance, they can assign each supported agent the same coding task and have them all do it in parallel, so they can compare the results. There are security benefits to having a command center too. Whereas standalone coding agent implementations require users to grant broad repository access, the Agent HQ allows granular controls to be implemented at the platform level. In this way, the third party agents will inherit the enterprise security and governance of GitHub Copilot. This means they'll run within sandboxed GitHub Actions environments secured by firewalls and operate under strict identity controls, the company explained. Even if an agent goes rogue, the firewall will stop it from accessing external networks or stealing data. GitHub said Agent HQ will launch initially for Copilot Pro+ subscribers later this week, with support for OpenAI Codex. In the coming months, it will add support for the other coding agents. In addition to Agent HQ, GitHub announced a new Plan Mode in Microsoft's Visual Code Studio platform that uses GitHub Copilot to create step-by-step plans for tasks before it goes ahead and executes them, so users can review it first. It's also added a code review feature to Copilot that allows it to access tools such as CodeQL and evaluate its own code before passing it to a human developer.

Microsoft's GitHub Adds Access to Suite of Major AI Models

Microsoft's coding platform GitHub will start offering coding agents from several major AI companies as part of its paid subscription service. GitHub is launching Agent HQ, which will offer an open ecosystem for companies including Anthropic, OpenAI, Google, Cognition and xAI to make their AI models directly available on GitHub for customers with the Copilot subscription. GitHub Copilot is an AI-powered programming assistant that helps developers write and edit code. About 80% of new developers are using Copilot within their first week on GitHub, the company said. "AI isn't just a tool anymore; it's an integral part of the development experience," GitHub said. Agent HQ will have a single command center where users can assign, steer and track the work of multiple AI agents at once. Developers will also be able to plan and customize agent behavior in new ways, as well as track how the AI modeuls are impacting their work. Write to Katherine Hamilton at [email protected]

GitHub Agent HQ explained: How it aims to create specialized AI agents for developers

GitHub launches Agent HQ, creating unified control for AI agents When GitHub Copilot first landed on developers' screens in 2021, it felt like a quiet revolution - a coding partner that could autocomplete lines, write functions, and even refactor snippets on command. Fast-forward to 2025, and GitHub has now taken a much bigger leap: Agent HQ, a command-center built not just for Copilot, but for a whole ecosystem of AI coding agents. Think of it as the developer's "mission control," where OpenAI's models, Anthropic's Claude, Google's Gemini, and even xAI's Grok can all sit side by side, each one specialized for a different kind of coding task. Also read: Meet NEO: Humanoid robot designed as your home assistant for ₹18 lakh At its core, Agent HQ is GitHub's answer to a growing reality in software development: no single AI model can do it all. Developers increasingly switch between tools - Copilot for boilerplate, Claude for reasoning, Gemini for data structuring - and that friction adds up. Agent HQ promises to eliminate that problem by offering a unified dashboard where multiple AI agents can be connected, deployed, and managed within the same GitHub environment. Developers can select which agent to assign to a task, compare outputs from different models, and even run them collaboratively on the same repository. The interface acts like a real-time control tower, you can plan, test, and review AI-generated code without leaving your GitHub workflow. GitHub calls Agent HQ a "home for any agent, any way you work." But the deeper ambition here isn't just unifying vendors, it's about specialization. Where Copilot is a general assistant, the next wave of AI tools is moving toward task-oriented agents: one that writes documentation, another that reviews pull requests, a third that generates test cases. GitHub's new "Plan Mode" in Visual Studio Code, for instance, allows an agent to generate a full step-by-step plan before writing any code - an early sign of more structured autonomy. This shift from "prompt-based" to "mission-based" interaction is what makes Agent HQ so consequential. It marks the beginning of agents that don't just respond, they manage, delegate, and collaborate. Also read: Can ChatGPT really care? OpenAI wants to make AI more emotionally aware, here's how. For years, developers have been confined to whichever AI tool was integrated into their IDE. Now, they can choose the right agent for the right job. A Python backend? Use Claude. A front-end prototype? Maybe Copilot. A system design discussion? Gemini's multi-modal reasoning might help. That kind of modularity gives developers real agency and forces model makers to compete not on marketing, but on performance and reliability. Agent HQ isn't just a plug-and-play switchboard; it's an environment designed for orchestration. GitHub envisions teams where multiple agents work together, one writes, one reviews, another tests, supervised by a human developer. It's a step toward software projects that feel more like managing a digital team than typing alone in an IDE. Because Agent HQ is embedded within the GitHub ecosystem, it inherits the platform's strengths, version control, security audits, and collaborative review. This means AI agents can operate within the same pull-request flow as human contributors, making their output transparent and traceable. But Agent HQ also surfaces new questions that GitHub and the broader AI community will need to answer. There's also the issue of platform lock-in. GitHub's "hub of agents" could centralize developer workflows, but in doing so, it may tighten Microsoft's already dominant grip on the AI-coding landscape. Agent HQ represents a philosophical shift: AI isn't just assisting developers anymore, it's joining their teams. As specialized agents evolve, the act of coding could become more about orchestration than execution, where human developers act as creative directors managing a fleet of digital coworkers. For now, Agent HQ is still in its early stages. But if GitHub succeeds, it might redefine what it means to "build software" - turning repositories into collaborative ecosystems where humans and AI agents build, test, and ship side by side.