If you use IntelliJ, PyCharm, WebStorm, GoLand, or Rider, you’ve already passed through JetBrains. Don’t code? Their tools still shape the software you use every day.
JetBrains brings OpenAI models into the workflow
JetBrains isn’t just a set of editors. It’s behind tools used by about 15 million engineers and 88 of the Fortune 100 companies. They also created Kotlin, the official language for Android. Now they’re bringing OpenAI models into how software gets built—not to replace people, but to amplify them.
"Developers don’t just write code. They review, reason, and design systems. AI can help with the parts that go beyond typing."
JetBrains’ bet is practical: protect the developer’s flow, remove repetitive work, and let engineers focus on design, architecture, and judgment. Sound familiar? It’s what many of us feel when a repetitive task pulls us out of productive flow.
What they use inside JetBrains
- ChatGPT
- GPT-5
- Codex
Externally, customers can choose GPT-5 inside Junie, JetBrains’ code agent, and in AI Assistant for chat help. It’s not a single magic model, but choosing the right tool for each task.
What tasks do they delegate to AI right now?
They start with what creates the most human friction: documentation, tests, reviews, and context handoffs. Teams are already delegating real tasks to agents and getting results. Kris Kang, Head of Product at JetBrains, says he assigns increasingly complex tasks to an agent backed by GPT-5 and many complete successfully.
That doesn’t mean writing code without looking. JetBrains’ criterion is clear: not just speed, but sustained excellence. Code must be safe, readable, and maintainable—not just clever and fragile.
How it changes your day-to-day as a developer
- Less boilerplate and fewer context switches, which protects deep work time.
- AI that generates drafts: you design, AI suggests, you review.
- Better quality: tests and documentation more complete from the start.
- Agents that finish repetitive tasks and leave humans with higher-impact work.
Think about asking an agent to write unit tests, document an API, or do a first-pass review. It’s not less work; it’s different work—more focused on architecture and judgment.
One strategy: hybrid, not replacement
JetBrains promotes hybrid flows: AI drafts and assists; humans design, review, and set boundaries. That makes the advantage not instant and fleeting, but compound: those who experiment well with AI will gain cumulative benefits.
"Chat gives you a boost. Agents give you a change in scale."
The metric isn’t just delivery speed, but the ability to iterate efficiently and keep quality over the long term.
For teams and technical leaders
Start with obvious frictions: documentation, tests, reviews. Protect deep time and document intentions and architecture. If you define intention well, AI multiplies the effect.
Small practical experiment: pick a repetitive task on your team, try Junie with GPT-5 for that task, collect simple metrics (time, number of reviews, bugs) and decide based on data. Efficient iteration wins over instant solutions.
For product and engineering leaders, the message is clear: it’s not about removing developers, but raising the level of human work. Design better systems, guide and put guardrails on agents, and review more effectively—that’s where the value is.
In the end, JetBrains’ promise with OpenAI isn’t futuristic: it’s practical. It lets engineers do higher-impact work, with less friction and more confidence when shipping code to production.