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Title: JetBrains AI - The JetBrains Blog

Open Graph Title: JetBrains AI - The JetBrains Blog

X Title: JetBrains AI - The JetBrains Blog

Description: JetBrains AI Archive - The JetBrains Blog

Open Graph Description: JetBrains AI Archive - The JetBrains Blog

X Description: JetBrains AI Archive - The JetBrains Blog

Opengraph URL: https://blog.jetbrains.com/ai/

X: @jetbrains

Generator: WPML ver:4.9.3 stt:59,9,1,4,3,28,29,42,45,2,53;

direct link

Domain: blog.jetbrains.com


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Promo image https://blog.jetbrains.com/ai/2026/11/livestream-scaling-agentic-development-with-air-governance/
Webinarshttps://blog.jetbrains.com/ai/tag/webinars/
Livestream: Scaling Agentic Development With Air Governancehttps://blog.jetbrains.com/ai/2026/11/livestream-scaling-agentic-development-with-air-governance/
Read articlehttps://blog.jetbrains.com/ai/2026/11/livestream-scaling-agentic-development-with-air-governance/
Getting Started with Air in JetBrains IDEs – Part 1 Setting coding agents up to handle several tasks while you continue working is easy. The harder part is knowing where each task stands, what each agent has changed, and what still needs your attention. Recently, we introduced Air in JetBrains IDEs. It brings coding agents into the environment whe… Tanu Tams https://blog.jetbrains.com/ai/2026/10/getting-started-with-air-part1/
The Terminal in JetBrains IDEs Now Runs on libghostty More and more of your terminal work now runs through tools that push the terminal harder than a shell prompt ever did: AI coding agents like Claude Code and Codex, full-screen apps like Neovim and tmux, system monitors and dashboards. These tools lean on modern terminal protocols, the kind today’s b… Ekaterina Valeeva https://blog.jetbrains.com/platform/2026/10/jetbrains-terminal-now-uses-ghostty/
Air Governance: Manage AI Agents, Access, and Spend Throughout Your Organization Air Governance is the organization layer of JetBrains Air, a system of products for agentic development. It gives you one place to manage which AI agents, models, and providers your teams use, set spending limits, and see what that usage costs and delivers. Viktor Kiselev https://blog.jetbrains.com/blog/2026/10/22/air-governance-manage-ai-agents-access-and-spend-throughout-your-organization/
Can you bake Maven into a neural network? We tried, and it builds. We compiled the decision-making part of a Maven-style build tool into a fixed weight matrix and used it to build a real Java library. The output matches Apache Maven's byte for byte. A clean build with tests took 1.49× as long as the same logic written in Python (95% in… Denis Shiryaev https://blog.jetbrains.com/ai/2026/10/can-you-bake-maven-into-a-neural-network/
How Netflix Made AI Coding Agents More Efficient with JetBrains IDE Intelligence Across every model, agent, and task type tested, JetBrains IDE intelligence made coding agents more efficient overall – typically 20–30% more efficient, and up to about 65% in the best case, depending on the specific model, agent, and task. Anastasia Kazakova https://blog.jetbrains.com/ai/2026/10/how-netflix-made-ai-coding-agents-more-efficient/
Mellum2.1 Gets to Work: A Fast Open Model for Coding Agents Trained with reinforcement learning in real environments, Mellum2.1 is built for coding agents and fast sub-agents that run on your own hardware. Bulat Salimzianov https://blog.jetbrains.com/ai/2026/10/mellum2-1-gets-to-work-a-fast-open-model-for-coding-agents/
A New Agentic Experience: JetBrains Air in IDEs – EAP Now Open Last week, we shared our point of view on where we think agentic development is headed and introduced JetBrains' answer to it: JetBrains Air, an open system of products for agentic development. Today, we're launching the Early Access Program for Air in JetBrains IDEs. It's available now as a plug… Dominique Rolink https://blog.jetbrains.com/ai/2026/10/air-in-ides-eap/
Building a RAG Pipeline for Semantic Code Search: A Developer Diary and Field Notes Part 1: Parsing, chunking, and vectorization  Some time ago, we set out to build the best semantic code search platform we could: a RAG pipeline that gives LLM agents precise, citable evidence from real repositories instead of whatever grep happens to surface. The eventual solution was Air Context. … Adam Malek https://blog.jetbrains.com/ai/2026/09/building-a-rag-pipeline-for-semantic-code-search-a-developer-diary-and-field-notes/
New in Air: Multiproject View, a New Markdown Editor, and IME on Windows Air now puts multiple projects in one window, renders Markdown files as formatted documents, and fixes IME input on Windows. Vladimir Gromozdin https://blog.jetbrains.com/air/2026/08/new-in-air-multiproject-view-and-improved-markdown/
Our First Moves to Get AI Spend Under Control Over the past six months at JetBrains, our AI development expenses have increased roughly 10x. When the costs started rising, of course we noticed – and realized that we simply didn't know how to control them systematically. Viktor Kiselev https://blog.jetbrains.com/ai/2026/08/our-first-moves-to-get-ai-spend-under-control/
Ponytail Skill for Claude Code: Does It Really Cut Agent Code by 54%? Part 3 of a series where we take public "token saver" add-ons for coding agents and run the same paired A/B benchmark against each of them. Part 1 was the caveman skill (advertised −65%, measured −8.5%). Part 2 was rtk (advertised −60–90%, measured +7.6%). We ran 80 paired tasks to test the pony… Denis Shiryaev https://blog.jetbrains.com/ai/2026/07/ponytail-skill-claude-tested/
What’s new: Air gets more agents, local models, and Java/Kotlin code intelligence Air now supports GitHub Copilot, OpenCode, Pi, Cline, and other ACP agents, adds Java and Kotlin IDE intelligence, and runs Windows tasks in Docker. Vladimir Gromozdin https://blog.jetbrains.com/air/2026/07/what-s-new-air-gets-more-agents-local-models-and-java-kotlin-code-intelligence/
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