JetBrains AI

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. …

Air now puts multiple projects in one window, renders Markdown files as formatted documents, and fixes IME input on Windows.

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.

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…

Air now supports GitHub Copilot, OpenCode, Pi, Cline, and other ACP agents, adds Java and Kotlin IDE intelligence, and runs Windows tasks in Docker.

Today, we’re launching JetBrains Context, a new repository intelligence layer that helps coding agents work more efficiently and produce higher-quality results on complex codebases. As part of the JetBrains AI for Teams and Organizations rollout, JetBrains Context is now available in early access at…

Does "rtk" reduce Claude Code token usage? Part 2 of a series where we take public “token saving” 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%). TL;DR: rtk advertised saving: 60–90%. Measured…

We’re releasing an open benchmark for evaluating AI coding agents on real-world Kotlin tasks. Compare agents, inspect the methodology, and see the results on the leaderboard.

We’re about to start rolling out a new set of AI capabilities that provide shared context, reusable agentic workflows, organization-level governance, and cost control for software production. Developers use different AI tools depending on the task – from JetBrains IDEs to terminal-based agents su…

A paired A/B benchmark of the token-compression skill Caveman on Claude Code, run on SkillsBench: does it actually save tokens, and does it degrade AI agent output quality? Advertised saving: 65%. Measured saving: 8.5%. Output-token saving on real agentic tasks, with the skill forcibly activat…

Born out of a deep partnership between JetBrains and GitHub, this integration makes Copilot native in the agent picker and delivers a more stable agent experience directly in the IDE you already use every day. From ACP Registry to native experience Copilot was previously accessible via the…

JetBrains Air is now available for Windows. Try it today!