2026-10-12 18:54 UTC

JetBrains claims its newly announced Air system will connect IDE agent execution, team workflows, and cross-vendor governance through shared context, policies, and cost visibility, reducing fragmentation without requiring teams to standardize on Junie.

state: watchingheat: lowuncertainty: mediumconvergesscott: highagent-harnesses agent-orchestration developer-toolsJetBrainsKirill Skrygan

What is this?

JetBrains has bundled its agentic-development work into 'Air', a system spanning an agent-native development environment (built on its earlier Fleet experiment), Air Teams, and Air Governance, backed by JetBrains Central as an enterprise control plane. Air lets developers run multiple third-party agents — Claude Agent, Codex, Gemini CLI, and JetBrains' own Junie CLI — concurrently in one workspace, in isolated Docker containers, Git worktrees, or cloud sandboxes, and is built on the open Agent Client Protocol (ACP) so teams aren't locked to Junie. Central adds governance, policy enforcement, audit logging, and per-agent cost attribution for organizations. The snippets give slightly conflicting framings (some present Central as the platform and Air as the IDE, others fold governance under the Air brand), and dates range from a March 2026 debut to a Q2 2026 Central early-access program, so exact product boundaries and timelines are fuzzy in the supplied material.

Why it matters to Scott

JetBrains is productizing, at enterprise scale, the exact architecture Scott has argued from first principles: untrusted agents inside disposable isolated runtimes (Docker/worktrees/cloud sandboxes), a deterministic control plane for policy, audit and cost attribution, and an open protocol (ACP) so no single vendor's agent is load-bearing — this is SiloOS, governance-as-code, and the padded-cell pattern arriving as a shipped IDE-vendor platform, which is a dated-receipts publishing opportunity and a signal the 'agent workshop + deterministic membrane' position is becoming the default enterprise shape. It also extends what the radar already tracks piecemeal (Junie, Zed Xanadu, AgenticOS, Grafana agento11y) by consolidating execution, coordination, and governance into one cross-vendor system, so it bears on how he'd weight those smaller open cases.
ip:framework.siloosip:source.governance-as-codeip:source.why-code-execution-beats-mcpip:concept.runtime-containmentradar:jetbrains-junie-local-macradar:jetbrains-context-repository-intelligenceradar:concept.agent-governanceradar:concept.agent-interoperabilityradar:concept.agent-sandboxingradar:zed-agentic-xanadu
queries asked of Scott's wikis
  • agent harness and orchestration patterns for running multiple coding agents concurrently
  • agent context sharing and agent-maintained project memory across tools and sessions
  • Agent Client Protocol / open protocols for vendor-agnostic agent interoperability
  • sandboxed agent execution via Docker, Git worktrees, and cloud runtimes
  • agent governance, cost attribution, and observability for LLM tooling
  • IDE-as-harness vs terminal/CLI agent workflow tradeoffs (Fleet, Junie CLI)

Measured heat

now 0 pts/hpeak 0 pts/hcomments 0/hpeers p50momentum: steady2 platformsage 509h
points/hour across evidence · reading as of 2026-10-13 05:35:48.225472+11:00 · deterministic, not a model opinion

How the heat travelled

09-21 14:00⭐ origin echo-reconstructedJetBrains is bringing its agentic-development work together as Air, comprising IDE experiences, Air Teams, and Air Governance, with availabl
Kirill Skrygan on blog (echo) · attributed from hn.story.49799287
—
09-22 11:00first on hacker news · published · +21.0hJetBrains Air: A System of Products for Agentic Software Development
FinnLobsien
—
09-22 11:00amplified on hacker news 👑hn.story.49799287
FinnLobsien
peak 75 · 123 comments · 99% of case engagement
09-25 11:46amplified on hacker newshn.story.49843261
Aireen5858
peak 2 · 0 comments · 1% of case engagement
09-22 11:20our radar first saw it · +21.4hdiscovery anchor: hn.story.49799287—
pace: p74 vs 1037 stories at the 336h mark (now 509h old) — ahead of typesafe-macos-computer-use (1.0x), behind ftc-agent-developer-liability (1.0x)

Evidence (3) — ⭐ canonical anchor

sourceobjectauthorscorecomments
🟧 hnJetBrains Air: A System of Products for Agentic Software Development
Retrieved article excerpt

Open article · Retrieved 2026-09-23T12:21:56.943105+00:00

[Blog logo

## Company](https://blog.jetbrains.com/blog/)

[Follow](https://blog.jetbrains.com/blog/2026/09/22/introducing-jetbrains-air/)

- Follow:
- [*X* X](https://twitter.com/jetbrains)
- [*Facebook* Facebook](https://www.facebook.com/JetBrains/)
- [*Linkedin* Linkedin](https://www.linkedin.com/company/jetbrains/)
- [*Instagram* Instagram](https://www.instagram.com/jetbrains/)
- [*Youtube* Youtube](https://www.youtube.com/user/JetBrainsTV)
- [*RSS* RSS](https://blog.jetbrains.com/blog/feed/)
- [*Tiktok* Tiktok](https://www.tiktok.com/@jetbrains?lang=en)

[Visit jetbrains.com](https://www.jetbrains.com/)

[Agentic AI](https://blog.jetbrains.com/blog/category/agentic-ai/)
[AI](https://blog.jetbrains.com/blog/category/ai/)
[JetBrains](https://blog.jetbrains.com/blog/category/jetbrains/)
[New Products](https://blog.jetbrains.com/blog/category/new-products/)
[News](https://blog.jetbrains.com/blog/category/news/)
[Releases](https://blog.jetbrains.com/blog/category/releases/)

# JetBrains Air: Building a System of Products for Agentic Software Development

Kirill Skrygan

[Kirill Skrygan](https://blog.jetbrains.com/author/kirill-skrygan)

Read this post in other languages:

- [Español](https://blog.jetbrains.com/es/blog/2026/09/22/jetbrains-air-desarrollo-de-un-sistema-de-productos-para-el-desarrollo-de-software-agentico/)
,- [Français](https://blog.jetbrains.com/fr/blog/2026/09/22/jetbrains-air-construire-un-systeme-de-produits-pour-le-developpement-logiciel-agentique/)
,- [日本語](https://blog.jetbrains.com/ja/blog/2026/09/23/introducing-jetbrains-air/)
,- [Português](https://blog.jetbrains.com/pt-br/blog/2026/09/22/jetbrains-air-construindo-o-sistema-de-produtos-para-o-desenvolvimento-de-software-com-agentes/)

******AI can produce code. Organizations still have to produce software. Agentic development is changing how software gets made, but it hasn’t changed what it costs to be wrong.******

Six months ago, we began publicly experimenting with agentic development environments. Around the same time, we introduced [JetBrains Central](https://blog.jetbrains.com/blog/2026/03/24/introducing-jetbrains-central-an-open-system-for-agentic-software-development/) as an open control and execution system for agent-driven development. We subsequently began rolling out [JetBrains Central CLI](https://blog.jetbrains.com/blog/2026/07/07/jetbrains-ai-for-teams-and-organizations-from-fragmented-ai-usage-to-coordinated-software-development/), shared context, cloud agents, automations, governance, and AI cost controls for teams and organizations.

Today, we are bringing this work together as JetBrains Air: an open, coherent system of products for developers, teams, and organizations, inside and beyond JetBrains IDEs. It is multi-surface and multi-service. Each product solves a distinct problem, but the products work better together.

JetBrains Air marks a significant expansion in what JetBrains is building for. 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.

The IDE remains important to JetBrains’ future. The era in which the whole software development system can be contained in one window is ending. As part of our continued investment, we are now bringing the foundational agentic experience into JetBrains IDEs, giving professional developers an environment where they can work effectively with agents while understanding, changing, and verifying the resulting code. JetBrains Air connects the wider system developing around it.

That system is based on a core belief that the future of agentic development will be multi-vendor. No single model, agent, or service will be right for every developer, team, or task.

## ******From one product to an open system of products******

This strategic shift has a practical consequence: JetBrains Air cannot be just another agent or development environment. It must connect products for individual work, team coordination, organizational control, context, and process automation – and remain open to the tools and agents developers choose, including those JetBrains does not build.

JetBrains Air includes products that are available today alongside others that will be introduced as the system develops:

- **Air in JetBrains IDEs** – a complete agentic development experience for directing and orchestrating agents and verifying their work inside JetBrains IDEs.
- **Air Teams** – a new way to coordinate and automate software-delivery workflows involving developers and autonomous agents.
- **Air Governance** (formerly JetBrains Central) – organizational policy, visibility, auditability, cost management, and accountability for AI-assisted and agent-driven development.

**Junie** is JetBrains’ coding agent for professional software development. It will be supported across all Air surfaces.

Air in JetBrains IDEs gives developers the environment to direct agents and verify their output using JetBrains’ code intelligence. Air Teams turns individual agent activity into coordinated team workflows. Air Governance makes that activity visible, governable, and accountable across the organization.

But an open system cannot stop at JetBrains’ own products. The Agent Client Protocol ([ACP](https://www.jetbrains.com/acp/)) standardizes the connection between an IDE and an agent’s full harness, including its planning, logic, tools, model routing, and observability. Through the ACP Registry, developers can discover and run a growing range of compatible agents while continuing to work inside JetBrains IDEs.

Air Governance is designed to extend visibility and cost governance across providers and the different tools through which agentic work takes place. This means developers can choose the agent, model, or service suited to the task without forcing the organization to give up context, visibility, or control.

Together, the Air products allow work to move between developers, agents, tools, and environments without losing the context and controls surrounding it.

## ******Individual adoption has moved faster than organizational infrastructure******

Since March, our products have progressed significantly, but so has our understanding of what agentic development requires.

Developers have been adopting agents faster than organizations can build the infrastructure around them. Agent capabilities have advanced, and different models and agents have proven useful for different tasks. However, the context, coordination, governance, and cost management surrounding them have not kept pace.

For many developers, agents are already delivering practical value. At the organizational level, the economics are much harder to prove. The costs surface elsewhere – in review, rework, security, infrastructure, and spend.

Which agents can access company code? Where can data go? Which output requires human review? What happened while an agent was working remotely? Who approved the resulting change, and how was it verified?

Fragmentation at this level isn’t just irritating. It makes software development harder to understand, measure, and govern at exactly the point when more of the work is being delegated.

## ******The bottleneck is shifting with the work******

Code that’s obviously wrong gets caught quickly. That part of the system still works. The harder problem is code that’s almost right: plausible, capable of passing a superficial check, but quietly carrying a bad assumption or architectural inconsistency that won’t surface until it’s expensive.

As agents take on more of the execution, the bottleneck shifts from producing change to understanding, verifying, and owning it. Code becomes cheaper to generate but more expensive to verify. Agent activity becomes easier to start but harder to coordinate, audit, and explain.

And while the work can be delegated, accountability cannot. An agent will not get the call at 3:00 am when something breaks. The responsibility for what ships still belongs to the people and organizations that ship it.

This is why control becomes harder, not easier, as AI improves. A more capable model may produce better output. It does not establish organizational policy, preserve provenance, provide cost visibility, or decide who accepts responsibility for the resulting change.

## ******The future is multi-vendor******

Multi-vendor support is a foundational design principle of JetBrains Air, shaping how the system is being built from the outset.

We don’t believe this market will consolidate any time soon. Models vary in what they’re good at, and rankings change every few months. Teams inside the same company already make different choices, and they are often right to do so. Standardizing on one AI vendor today means making a multi-year commitment in a market that won’t look the same next quarter.

Keeping the options open is the reasonable thing to do. The problem is what openness currently costs. Every new model, agent, or service an organization adds takes away a little more visibility into its own development work. Context doesn’t carry over between tools. Spend can’t be attributed. Policies have to be rebuilt for each service.

Organizations should not have to choose between using the best available tools and understanding what is happening inside their own engineering. That trade-off exists because nothing in the current stack was built to sit above several vendors at once.

This is the work JetBrains has taken on. We build our own agent, and we intend to make it excellent. But JetBrains Air does not require customers to use ours, and our strategy does not depend on which model provider leads the rankings this quarter. We have no reason to make the ecosystem smaller than it is.

What we can offer instead is one place to run, see, govern, and account for agentic development across every model, agent, and service – for the developer, the team, and the organization.

Supporting multiple models and agents is the floor, not the ceiling. The part that matters is what sits above them: shared context, one set of policies, a single cost view, and a record of what happened, regardless of which vendor produced the change.

## ****Why JetBrains?****

Multi-vendor choice solves only part of the problem. Agents also need reliable software intelligence.

JetBrains brings 26 years of engineering intelligence to the problem, helping developers understand the structure and behavior of complex software, not simply generate more of it. That deterministic code intelligence provides a foundation for making agentic work more reliable, efficient, and understandable across different models and agents. We are seeing promising results from giving AI agents access to deterministic code intelligence.

This is an economic advantage as well as a technical one. Agents spend time and money rediscovering information the codebase already contains. An agent that can retrieve that knowledge is cheaper and more accurate than one that has to reconstruct it. Because intelligence does not belong to one model, the benefit can extend across supported agents and services.

We are also going through the same transition as the organizations we build for, adopting agents internally, redesigning workflows, and learning where individual productivity gains translate into better software delivery and where they simply move work elsewhere.

## **What comes next**

JetBrains Air will develop through a rolling series of releases. We will be explicit about what customers can use now, what is entering preview, and what remains part of our longer-term direction.

Over time, JetBrains Air will extend further into mobile and remote experiences, allowing people to initiate, monitor, review, and continue agentic work as it moves between environments. The goal is not to reproduce the IDE on every surface. We are making the right context and controls available wherever decision
FinnLobsien75123
🟧 echo.blog ⭐JetBrains is bringing its agentic-development work together as Air, comprising IDE experiences, Air Teams, and Air Governance, with availablKirill Skrygan——
🟧 hnKilo for JetBrains is now a multi-agent control roomAireen585820

Interpretation history

Decision trace