Developer tools decision
JetBrains AI Pro
A single developer can implement a useful JetBrains IDE AI assistant plugin (core suggestion loop) in about a week, but reproducing JetBrains' full product polish, multi-IDE QA, support, and any proprietary integrations is not realistic for one person.
Visit website↗Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.
What a replacement has to do
- Provide inline AI coding suggestions in a JetBrains IDE by sending editor context to an LLM API and rendering suggestions as completions/quick-fixes.
What it still won’t have
- Official vendor support and branding
- Deep product polish, QA across all JetBrains IDEs and versions
- Any proprietary integrations JetBrains provides (if any)
- Potential bundled model access included by vendor
What remains hard
- Brand trust
JetBrains: Essential tools for software developers and teams
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 6 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build an IntelliJ Platform plugin in Kotlin that offers inline AI coding suggestions using an external LLM API. In scope: plugin project setup, editor context capture (file + selection + limited project files), request/response adapter to a configurable LLM endpoint with token-based auth and retry/backoff, UI to show suggestions as completions/quick-fixes and a side panel, user settings for model/token/prompt templates, basic telemetry and robust error handling, and unit/integration tests for core flows. Out of scope: training or hosting models, multi-IDE commercial packaging, enterprise SSO integrations, and large-scale telemetry pipelines.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 3 cited sources+3
- 3/3 assessment runs agreed+4
- Evidence score64
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time — so the same evidence always produces the same number.
How scoring works →Cited sources · 3
Every page the run actually retrieved.
- official productJetBrains homepage
- open sourcejulia-vscode/julia-vscode
- open sourceplatformio/platformio-vscode-ide
Integrity checks
What held up, and what did not.
