Junie Review 2026: JetBrains' AI Coding Agent Tested

This is the whole thesis. Junie queries the same index IntelliJ uses for Go to Definition and Find Usages, so when a task touches an interface with four implementations, it knows which one is wired up in the Spring context rather than guessing from names. In our multi-module test project, a task to change a repository method signature updated the interface, the implementation, three call sites, and the test doubles — the exact set, no strays. Text-based agents attempting the same task missed the test doubles twice out of three attempts.

You describe a task, Junie drafts a plan and executes it: edits, build, tests, read failures, fix, repeat. Completion was strong on bounded work — add validation to a service and cover it with tests, migrate a deprecated API across modules, wire a new endpoint following the existing pattern. It is noticeably slower per iteration than lightweight agents, largely because it runs real Gradle builds rather than pretending compilation is free. On a slow monorepo, that honesty costs minutes but avoids diffs that never compiled.

Junie runs the project's real test configuration and reads the failures the way you would — stack trace first, then the offending assertion. It fixed genuine bugs in its own output during our runs rather than deleting the failing test, which is the failure mode worth watching for in every agent. Where it struggles is flaky suites: an intermittent failure sends it chasing a phantom, and it will happily rewrite correct code to satisfy a test that was going to fail anyway. Stabilize flaky tests before delegating.

Changes are staged into the standard JetBrains diff viewer, which is a bigger deal than it sounds: you review agent output with the same tool, keyboard shortcuts, and partial-staging workflow you already use for your own commits. There's no separate chat pane holding the source of truth and no copy-paste step. Accepting some hunks and rejecting others is normal, and that granularity is exactly what agent output needs.

Java and Kotlin are clearly first-class — annotation processing, generics, and framework conventions are handled with a confidence that shows in the diffs. Python in PyCharm was strong too, especially on typed codebases. TypeScript and Go were competent but unremarkable; nothing here beats what Cursor does in the same languages. Judge Junie by your primary stack, not by the breadth of the IDE lineup it ships with.