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While developing a website or an app, you’ll encounter loads of technical challenges that need to be solved – from how to code the functionality to how to host it. Delivering even a simple to-do app requires a hefty technology stack, a team of professionals, and hours of testing and maintenance. Thi…

JetBrains AI Assistant just got a major upgrade, giving you smarter completions, better project understanding, and more control over how AI works in your IDE.

This summer, we're making Mellum, our code completion model, easier for developers to use locally, and we’re introducing support for more languages than ever.

AI agents are already in your tools—now it’s time to understand them. Learn to build and work with them responsibly in this free course by JetBrains and Nebius.

I was testing my agent built on Koog, JetBrains' open-source framework for building AI agents in Kotlin. I fed it a task from SWE-bench-Verified, a real-world GitHub issue that tests whether AI can actually write code. For the first 100 messages, everything looked promising. The agent methodicall…

At AI Summit London 2025, Kris Kang, Head of Product for AI at JetBrains, gave a talk that questioned a common belief in AI development: that bigger means better.

AI is no longer a distant idea. It’s already here and changing how we build software. As it advances, new questions emerge about its impact.?

We’ve just released Koog 0.3.0, which comes with many updates that make building, running, and managing intelligent agents easier. This version focuses on durability, speed, observability, and smoother integration with real-world systems. If you’ve been exploring how to develop your own intellige…

In May, 145 JetBrains employees from across teams and time zones paused their regular work to participate in a 48-hour AI hackathon.?With support from Google Cloud, the participants built a total of 41 prototypes from scratch. Some were practical, others experimental, but all explored how AI could change how developers work.

As AI tools continue to advance and become bigger parts of our lives, it is important to think critically about AI interactions. At JetBrains, some of our research teams study this, with a particular interest in enhancing these interactions in code-related tasks. In this post we will look at how our teams applied insights from a leading theory on motivation, Self-Determination Theory, to empirical results, and identified areas for actionable improvement.

JetBrains Mellum – our open, focused LLM specialized on code completion – is now available to run as a containerized microservice on NVIDIA AI Factories.

In AI-enabled IDEs, code completion quality heavily depends on how well the IDE understands the surrounding code – the context. That context is everything, and we want your help to find the best way to collect it.