---
title: "How We Use AlphaEvolve to Make Complex IDE Algorithms Faster"
url: https://daily.dev/posts/how-we-use-alphaevolve-to-make-complex-ide-algorithms-faster-to4znwyrn
source_url: https://blog.jetbrains.com/ai/2026/05/how-we-use-alphaevolve-to-make-complex-ide-algorithms-faster
type: article
source: "JetBrains"
published: 2026-05-29T14:50:26.714Z
updated: 2026-05-29T15:32:21.580Z
tags: ["jetbrains"]
reading_time: 5
upvotes: 0
comments: 0
language: en
---

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# How We Use AlphaEvolve to Make Complex IDE Algorithms Faster

**[JetBrains](https://daily.dev/sources/jetbrains)** · 5 min read · 0 upvotes · 0 comments

## Summary

JetBrains experimented with Google DeepMind's AlphaEvolve to optimize the B-tree implementation at the core of IntelliJ-based IDE indexing. AlphaEvolve generated and ranked algorithm variants using a synthetic benchmark loop; sessions with 50+ iterations consistently achieved 15–20% synthetic score improvements. Two of five generated candidates were validated in full IDE integration tests using Kotlin Spring Petclinic on IntelliJ IDEA 2026.2 nightly builds. One candidate reduced end-to-end indexing time from 17.4 seconds to 16.6 seconds (~4.6% improvement). The key takeaway is that autonomous search expanded the optimization search space in a mature, heavily hand-tuned codebase, while engineers retained ownership of benchmarks, code review, and release decisions. Next steps include validating improvements against the internal 'Mega Index' user-experience KPI.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.jetbrains.com/ai/2026/05/how-we-use-alphaevolve-to-make-complex-ide-algorithms-faster>

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