The agent can edit multiple files, run gradle tasks like tests, and use the output to improve its changes. At the end, it reports a git diff of all changes that can be accepted or rejected.
Under the hood, the agent relies on Claude 3.7 sonnet and a fast code apply model to speed up edits. We built tools to give deeper access throughout the IDE like IntelliJ’s graph representation of kotlin/java code, “everywhere search” for classes, and have more integrations planned. The goal is for the agent to have access to all the IDE goodies that we engineers take for granted, to improve the agent's responses and ability to gather correct context. In order to improve the agent, there are internal evals like “tasks” and simulate the IDE which serves as a gym for the agent. This is heavily inspired by SWE-bench. Whenever tools, prompts, subagents, or models are changed, this gym helps find regressions quickly.
Building the UI was surprisingly hard. I had the great pleasure of becoming proficient in Java Swing (released in ‘96 by Netscape) to get this done right. Things like markdown streaming, or streaming git diffs are prone to layout flickering where Swing tries to recalculate where elements should go. We had to write our own markdown parsing and rendering engine that repaints Swing components only when changed portions of the markdown nodes. The UI tends to focus on simplifying reviewing AI changes, something I have a feeling we’ll be doing much more in the coming years.
If you’re an Android engineer, please let me know if you run into any bugs or want anything improved in the plugin!
