JetBrains has officially unveiled JetBrains Air, an open product ecosystem designed to orchestrate, monitor, and govern AI-driven software development across individual engineers, teams, and whole organizations.

As autonomous AI agents take on a larger role in coding and software delivery, JetBrains Air aims to connect existing tools with upcoming features into a unified platform.

Moving Beyond the Individual Developer Workbench

Historically known for its suite of developer-centric IDEs, JetBrains is broadening its focus to manage the entire lifecycle of AI-assisted engineering.

“For 26 years, we have focused primarily on the individual developer workbench. Now, we are building for the wider system through which agentic work is initiated, executed, coordinated, reviewed, and governed,” stated Kirill Skrygan, CEO of JetBrains.

Core Components of JetBrains Air

The JetBrains Air suite will feature three primary pillars:

• Air in JetBrains IDEs: A dedicated environment within familiar IDEs that allows developers to direct, orchestrate, and verify the output of AI agents directly inside their workspace.
• Air Teams: A collaborative system tailored to coordinating and automating complex software delivery pipelines handled by a mix of human developers and autonomous agents.
• Air Governance: Formerly known as JetBrains Central, this tier provides enterprise-level control—offering visibility, audit trails, organizational policy enforcement, cost management, and accountability for agentic workflows.

What’s Next for JetBrains Air?

JetBrains plans to roll out JetBrains Air incrementally through a series of progressive updates. Moving forward, the roadmap includes:

• Cross-Environment Continuity: Extending access to mobile and remote interfaces so engineers can initiate, monitor, and review agent activities seamlessly across different devices.
• Deeper Context Awareness: Feeding richer situational data into AI workflows—drawing insights from codebase structures, software architecture, repository history, runtime metrics, and internal documentation.
• Intelligent Work Routing: Optimizing how tasks are assigned and routed between human developers, AI models, autonomous agents, and background services.