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

GitHub's Agent HQ is a new architecture designed to unify and manage multiple AI coding agents from various providers. This platform acts as a central control plane, allowing enterprises to orchestrate agents from companies like OpenAI, Google, and Anthropic. It transforms GitHub into an open ecosystem, integrating these agents directly into existing workflows and security perimeters. This approach avoids forcing developers into a single agent experience, instead offering an orchestration layer for a fragmented AI coding landscape. Agent HQ represents GitHub's "wave two" of AI-assisted development, moving beyond simple code completion. A key component is Mission Control, a unified interface for assigning tasks, tracking progress, and managing permissions across all integrated agents. Security is a primary focus, with granular access controls and sandboxed environments to protect enterprise data. GitHub is also enabling custom agents through AGENTS.md files, allowing organizations to codify specific rules and standards for AI behavior. Native Model Context Protocol support facilitates agent communication with external services. New features like Plan Mode promote collaborative project planning with AI, and agentic code review leverages tools like CodeQL to identify bugs and maintainability issues. Agent HQ offers enterprises vendor flexibility and reduced lock-in risk, enabling them to consolidate AI tools without replacement. The recommendation for enterprises is to start with custom agents to establish organizational standards.