{"id":3604,"date":"2026-03-11T21:43:05","date_gmt":"2026-03-11T21:43:05","guid":{"rendered":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/2026\/03\/11\/jetbrains-launches-air-and-junie-cli-to-blend-traditional-ide-with-ai-agents\/"},"modified":"2026-03-11T21:43:05","modified_gmt":"2026-03-11T21:43:05","slug":"jetbrains-launches-air-and-junie-cli-to-blend-traditional-ide-with-ai-agents","status":"publish","type":"post","link":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/2026\/03\/11\/jetbrains-launches-air-and-junie-cli-to-blend-traditional-ide-with-ai-agents\/","title":{"rendered":"JetBrains Launches Air and Junie CLI to Blend Traditional IDE with AI Agents"},"content":{"rendered":"
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JetBrains has launched a new \u201cagentic\u201d tooling stack that pairs a multi\u2011agent development environment, Air, with a standalone, LLM\u2011agnostic coding agent, Junie CLI.<\/span><\/p>\n

If you know <\/span>JetBrains<\/span><\/a>, you probably know it for <\/span>Kotlin<\/span><\/a>, the statically typed Java Virtual Machine (JVM) language used mostly for Android development, or for its well-known integrated development environments (IDEs), such as IntelliJ IDEA for Java, PyCharm for Python, and WebStorm for JavaScript. Going forward, JetBrains hopes you\u2019ll also know it for its AI tools, <\/span>JetBrains Air<\/span><\/a> and <\/span>Junie CLI<\/span><\/a>.<\/span><\/p>\n

The first, Air, is pitched as an \u201cagentic development environment\u201d that lets developers delegate coding tasks to multiple AI agents running concurrently. Rather than bolting chat boxes onto editors, Air \u201cbuilds tools around the agent,\u201d bundling terminals, Git, previews, and code navigation into a single workspace designed to guide and correct agents rather than just prompt them. JetBrains says it\u2019s using its 26 years of IDE experience to focus Air on orchestrating agents, while leaving day\u2011to\u2011day editing and broader workflows to traditional IDEs such as IntelliJ IDEA. It\u2019s a best-of-both-worlds: an old-school IDE and a brand-new AI-agentic approach.<\/span><\/p>\n

Out of the box, Air supports Codex, Claude Agent, Gemini CLI, and <\/span>JetBrains\u2019 own Junie<\/span><\/a>. These agents are treated as a normal workflow step rather than a migration. The platform uses JetBrains and the <\/span>Zed<\/span><\/a>\u2018s <\/span>Agent Client Protocol (ACP)<\/span><\/a> to bridge the gap between coding editors and AI agents. Tasks can run locally by default or inside Docker containers and Git worktrees. This enables you to run sandboxed, parallel work while Air manages the process of bringing changes back into the main codebase.<\/span><\/p>\n

It works, according to <\/span>Nik Tkachev<\/span><\/a>, Air ADE\u2019s Head of Product, by helping \u201cyou navigate your codebase. You can mention a specific line, commit, class, method, or other symbol when defining a task. As a result, the agent gets precise context instead of a blob of pasted text. And when the task is done, your review doesn\u2019t stop at the code diff. Air lets you see the changes in the context of your entire codebase, and you\u2019ll have essential tools like a terminal, Git client, and built-in preview right in front of you.\u201d\u00a0<\/span><\/p>\n

To combat \u201cagent sprawl,\u201d a tangle of windows and terminals per task, Air shows one task (one agent session) at a time and notifies developers when another task needs attention. The macOS preview is available to holders of <\/span>JetBrains AI Pro<\/span><\/a> or AI Ultimate.<\/span><\/p>\n

The company also supports a bring-your-own model, where you provide your own Anthropic, OpenAI, or Google keys. These are billed first before falling back to JetBrains\u2019 subscription. JetBrains is also testing cloud execution, where agents run in isolated remote sandboxes, and says an enterprise\u2011focused offering is on the way.<\/span><\/p>\n

At the same time, JetBrains announced Junie CLI. This is a standalone version of Junie\u2019s coding agent that can run directly from the terminal, in any IDE, in CI\/CD pipelines, and on GitHub or GitLab. The company describes Junie CLI as LLM\u2011agnostic, supporting \u201ctop\u2011performing models\u201d from OpenAI, Anthropic, Google, and Grok, and plans to integrate new models as they arrive. To seed adoption, JetBrains is offering a week of free access to Google\u2019s Gemini 3 Flash, enabled by default for new Junie CLI users before standard pricing kicks in.<\/span><\/p>\n

Junie CLI is designed to support all major developer workflows with minimal friction. It includes one\u2011click migration from other agents such as Claude Code and Codex. Junie also exposes extensive customization via guidelines, custom agents and skills, commands, the <\/span>Model Context Protocol (MCP<\/span><\/a>), and other configuration methods. You can also plug in your own model keys without paying an additional platform markup. JetBrains pitches this as a more transparent pricing structure meant to fit existing governance, compliance, and cost\u2011management policies inside organizations.<\/span><\/p>\n

Technically, Junie leans on JetBrains\u2019 project intelligence to combine LLM output with the company\u2019s deep understanding of code structure and workflow state. The agent is intended to handle complex problems, remain context\u2011aware by default, and operate under \u201crequired safeguards\u201d for reliability and security, while maintaining strong benchmark performance even on relatively low\u2011cost models like Gemini Flash 3. Features such as real\u2011time prompting let you adjust instructions while a task is running. Junie\u2019s codebase intelligence is meant to move it beyond \u201cAI in a terminal\u201d toward a fully autonomous task executor.<\/span><\/p>\n

Both approaches underscore JetBrains\u2019 broader strategy to treat AI agents as first\u2011class development tools rather than add\u2011on assistants. Air targets the fragmentation that comes from running different agents in different tools across different contexts, with little structural understanding of the code. By allowing multiple agents to work in parallel under a unified interface, JetBrains hopes to normalize agent orchestration as part of everyday development, not an experiment at the margins.<\/span><\/p>\n

JetBrains has not yet detailed an exact timeline for Windows and Linux versions of Air, only saying they are \u201ccoming soon.\u201d The company is also preparing dedicated enterprise offerings for both Air and Junie. But with Air\u2019s public preview and Junie CLI\u2019s beta now available, the company is clearly betting that professional developers are ready for a new layer of tooling built explicitly around AI agents, rather than simply embedding AI into existing tools.<\/span><\/p>\n

Read More<\/a><\/p>\n

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JetBrains has launched a new \u201cagentic\u201d tooling stack that pairs a multi\u2011agent development environment, Air, with a standalone, LLM\u2011agnostic coding […]<\/p>\n","protected":false},"author":1,"featured_media":3605,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[5],"tags":[],"class_list":["post-3604","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-devops"],"_links":{"self":[{"href":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/wp-json\/wp\/v2\/posts\/3604","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/wp-json\/wp\/v2\/comments?post=3604"}],"version-history":[{"count":0,"href":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/wp-json\/wp\/v2\/posts\/3604\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/wp-json\/wp\/v2\/media\/3605"}],"wp:attachment":[{"href":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/wp-json\/wp\/v2\/media?parent=3604"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/wp-json\/wp\/v2\/categories?post=3604"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rssfeedtelegrambot.bnaya.co.il\/index.php\/wp-json\/wp\/v2\/tags?post=3604"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}