JetBrains (@jetbrains)

Your IDE already knows your codebase. What happens when coding agents can use that knowledge too? We tested it with Netflix using Claude Code and Codex. One finding stood out: the strongest models gained the most from IntelliJ IDEA’s code intelligence.

Kirill Skrygan

@kskryganOct 15

We connected IntelliJ IDEA’s code intelligence to Claude Code and Codex, then tested the setup with Netflix. The first public results are out. Typical efficiency gains: 20–30%. Best code-navigation case: ~65%. These results come from two real codebases. The efficiency metric averages token savings and time savings. Correctness stayed stable or improved. Here’s what we actually built. The code engine behind IntelliJ IDEA ran headlessly, giving agents access to its capabilities through a CLI backed by a daemon. LSP alone wasn’t sufficient. Agents needed a convenient way to invoke the tools. The backend also needed to stay running and keep the project index warm between calls. The idea is straightforward. An IDE has already mapped the structure of your code and its dependencies — including what’s inside compiled libraries. An agent can use that knowledge instead of spending time and tokens reconstructing it. But the most interesting finding was which models benefited most. The strongest models saw the biggest gains. Especially at higher reasoning effort. In these experiments, more capable models were also better at taking advantage of code intelligence. My takeaway: better models and better tools aren’t competing bets. You don’t have to choose between investing in model intelligence and giving agents better access to your codebase. The two can reinforce each other. Huge thanks to @pbakker and the Netflix team for working with us on this!

121

19,318

JetBrains · Oct 20, 2026 · 1:30 PM UTC

@jetbrainsOct 20

An agent writes the code now. Do you still need an IDE? You do if you want to understand and verify what the agent did. 🎥 In our new video, we talk about the role of an IDE now that humans aren't the only ones working on the code. youtu.be/AHFGMkzrfwM

145

42,379

JetBrains · Oct 16, 2026 · 4:05 PM UTC

@jetbrainsOct 16

Junie Local now runs on @NVIDIARTXSpark from day one. Get a full-fledged coding agent on your PC. It reads your code, edits files, and runs tests. There are no tokens or quotas, and no code leaves the machine. Windows support is stable, too. All you need is a 24 GB Nvidia RTX card. Try it for free: junie.jetbrains.com/local

Image with a black background features text: "Your RTX Spark just got an agent. Junie Local runs on it from day one." The text is in white and green. The top corners display the logos for Junie and JetBrains. The bottom shows a green command line: "> /local".

ALT Image with a black background features text: "Your RTX Spark just got an agent. Junie Local runs on it from day one." The text is in white and green. The top corners display the logos for Junie and JetBrains. The bottom shows a green command line: "> /local".

8,140

JetBrains · Oct 16, 2026 · 11:05 AM UTC

@jetbrainsOct 16

Long-term AI adoption depends on driving down token costs. Mellum2.1 is our contribution to that shift – bringing an open-source 12B MoE model into local PyCharm workflows to deliver 140+ T/S without cloud overhead. Learn more and see it in action:

PyCharm, a JetBrains IDE

@pycharmOct 14

Meet Mellum2.1 – JetBrains' open-source 12B MoE model built for coding agents and local execution. 🚀 140+ T/S in local testing scenarios 🇪🇺 Ethically trained European open model 💻 Efficient worker model inside IDE agent workflows Try it locally: huggingface.co/collections/J…

8,798

JetBrains · Oct 15, 2026 · 2:16 PM UTC

Read the case study 👇 blog.jetbrains.com/ai/2026/1…

How Netflix Made AI Coding Agents More Efficient with JetBrains IDE Intelligence - The JetBrains...

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, depend...

blog.jetbrains.com

2,446

JetBrains · Oct 15, 2026 · 12:35 PM UTC

We're proud to see @junie_ai, the JetBrains AI coding agent, featured as an official partner in the @figma MCP Catalog! 🎉 Another step toward bridging the gap between design and code, making developers' workflows smoother and more connected. Excited to be part of this!

Figma

@figmaOct 15

Announcing 20 new MCP partners at Config India (!!) Amp, ClickUp, Dia, Junie by JetBrains, Linear, Meta Muse, Mistral, Notion, OpenCode, Sarvam Agents, Agentforce Vibes, Amazon Quick, Amplitude Wave, Cline, Delta, Dust, Glass, Gradial, Writer, Zed, Microsoft 365 Copilot

5,451

JetBrains · Oct 15, 2026 · 8:38 AM UTC

Try agentic coding with JetBrains Air and Junie Lite for free in PyCharm 2026.3 EAP 4 👇

PyCharm, a JetBrains IDE

@pycharmOct 8

Free, fast, and private agentic coding inside PyCharm? JetBrains Air is live in PyCharm 2026.3 EAP 4, and you can test it for free with Junie Lite – simply sign in with your JetBrains Account. No paid AI subscription required! 🤖 Powered by open-weights Qwen 3.6 27B + JetBrains code intelligence 🔒 Private by design – your code is never used for training ⚡ Perfect for routine tasks, boilerplate, and test generation in Air.

7,444

JetBrains · Oct 14, 2026 · 1:38 PM UTC

@jetbrainsOct 14

A few AI power users don’t automatically make a whole team more productive. At @WorldSummitAI, Ciara Byrne of JetBrains shared how teams can make AI agents useful beyond a handful of power users: build skills across the team, agree on shared practices, and automate repetitive work. See how JetBrains Air can help your team: jb.gg/s9nrn4

5,249

JetBrains · Oct 13, 2026 · 9:02 PM UTC

@jetbrainsOct 13

Gemini 4 Argon is officially live! @kristel_tech tasked two agents with building a web-swinging delivery game in a hyper-realistic night city: • Gemini 4 Argon: $54.41 | 23 mins • Opus 5.5: $56.97 | 2h 20 mins Compare their performance yourself in JetBrains Air or Junie.

141

20,253

JetBrains · Oct 13, 2026 · 11:48 AM UTC

@jetbrainsOct 13

Companies are measuring lines of code again. With flawed productivity metrics and spiraling AI spend, many leaders still don’t know what agentic development is actually costing them. Meri Williams (@Geek_Manager) calls metrics that look healthy while masking problems underneath “watermelon metrics”: green on the outside, red on the inside. That lack of visibility is one reason we made Air Governance, the organizational layer of JetBrains Air, our agentic development platform for engineering teams. Get Meri’s full take on October 14, 4:00 pm UTC: jb.gg/lmrt3j

Certainly! Here's a suitable alt text:

"Webinar announcement by Blueprint. Title: 'Beyond Watermelon Metrics: The Actual Costs of Agentic AI and Paths to Productivity.' Featuring Ciara Byrne and Meri Williams.

ALT Certainly! Here's a suitable alt text: "Webinar announcement by Blueprint. Title: 'Beyond Watermelon Metrics: The Actual Costs of Agentic AI and Paths to Productivity.' Featuring Ciara Byrne and Meri Williams.

5,550

JetBrains · Oct 12, 2026 · 1:27 PM UTC

@jetbrainsOct 12

Better yet, try it yourself. Fastest way: download the 26.3 IDEs EAP and press ⌘2 (Ctrl+2), or look for the Air icon. Using JetBrains at work? Air Teams and Air Governance have early access links in the thread. 👇

Kirill Skrygan

@kskryganOct 12

Holy moly, we’ve seen a lot of interest in JetBrains Air since the announcement! -Air in IDEs: for developers -Air Teams: for team leads & engineering managers -Air Governance: for CTOs & engineering directors Here’s how to try these things: Links below 🧵

8,822

JetBrains · Oct 9, 2026 · 1:13 PM UTC

@jetbrainsOct 9

Financial institutions want agentic AI. Their reality is COBOL, legacy systems, and strict regulation. Daniel Wolff and Aaron Wanjala discuss how to innovate without losing control – part of the wider industry shift reflected in @getsome_air. Watch: jb.gg/8e9su0

ALT An online webinar banner titled "Adopting AI in Financial Services and Legacy Systems." The banner features two speakers. On the left is a person affiliated with Capgemini, and on the right is a person affiliated with Google Cloud Platform. The Blueprint logo is at the top left corner.

5,511

JetBrains · Oct 8, 2026 · 7:34 PM UTC

Air in JetBrains IDEs, in action. Run your agent. Test the result. Verify the changes. All without leaving the IDE. youtu.be/yODck3N_lyU

JetBrains Air in IDEs – From Installation to Verified Agent Task in...

New to JetBrains Air? This is everything you need to know to go fro...

youtube.com

16,117

JetBrains · Oct 8, 2026 · 7:35 PM UTC

Try it with Junie Lite for free. plugins.jetbrains.com/plugin…

Air - IntelliJ IDEs Plugin | Marketplace

Air is a workspace for agentic development inside your JetBrains IDE. Delegate coding tasks to Codex, Claude, Junie, OpenCode, and other supported agents, and keep...

plugins.jetbrains.com

2,482

JetBrains · Oct 8, 2026 · 2:24 PM UTC

Live from @WorldSummitAI 👇

Nick Frolov

@v1becoderOct 8

Replying to @kskrygan

@kskrygan presents JetBrains Air at @WorldSummitAI JetBrains Air is new system for building software with agents

6,183

JetBrains · Oct 8, 2026 · 7:06 AM UTC

"Just because you can build 100 things doesn't mean you should." Engineering teams shared with Gleb Malkov, AI Solutions Architect at JetBrains, what they're learning about building with AI agents. Dive into the 3 key challenges: jb.gg/midcid

Two people kneel while working on a blue Formula 1 race car. Text above them reads, "3 things engineering teams tell us about working with AI agents.

ALT Two people kneel while working on a blue Formula 1 race car. Text above them reads, "3 things engineering teams tell us about working with AI agents.

ALT An illustration of hands holding a blue robot head. Below, text reads: "Automating the boring work creates a new operational burden.

Two people interact near a blue Red Bull Racing vehicle. One is leaning toward the seated person, who appears to be in the vehicle. The text on the image reads, "Implementation got cheap. Review didn't.

ALT Two people interact near a blue Red Bull Racing vehicle. One is leaning toward the seated person, who appears to be in the vehicle. The text on the image reads, "Implementation got cheap. Review didn't.

A person adjusts a blue, complex mechanical device against a plain backdrop. The image contains text that reads, “Check out the third most frequently mentioned scenario in our blog post.” The person is wearing bright blue pants.

ALT A person adjusts a blue, complex mechanical device against a plain backdrop. The image contains text that reads, “Check out the third most frequently mentioned scenario in our blog post.” The person is wearing bright blue pants.

6,657

JetBrains · Oct 7, 2026 · 5:30 PM UTC