Versions:

3.5.38
3.5.37
3.5.34
3.5.32
3.5.30
3.5.28
3.5.25
3.5.23
3.5.21
3.5.20
3.5.17
3.5.11
3.5.9
3.4.3
3.3.2
3.2.2
3.2.1
3.2.0
3.1.2
3.0.3
3.0.2
3.0.1
3.0.0
2.11.1
2.11.0
2.10.1
2.10.0
2.9.4
2.9.2
2.9.1
2.8.4
2.8.2
2.7.4
2.7.3
2.7.1
2.7.0
2.6.2
2.6.0
2.5.1
2.5.0
2.4.5
2.4.2
2.3.0
2.2.3
2.2.1
2.1.2
2.1.1
2.0.13
2.0.12
2.0.11
2.0.9
2.0.8
2.0.5
2.0.4
2.0.2
1.100.3
1.98.2
1.97.2
1.96.4
CN

Trae 3.5.38, published by SPRING (SG) PTE. LTD, is an adaptive AI IDE positioned in the Developer Tools / IDE category that rewrites the traditional coding workflow by embedding a cooperative AI pair-programmer directly inside the editor. Instead of passive suggestions, Trae converses with the author through an AI Q&A panel, predicts and completes whole code blocks in real time, and can switch into an autonomous agent mode to carry out multi-step programming tasks on request. The result is a single environment where human intent and machine execution iterate continuously, shortening the path from idea to running software. Typical use cases include scaffolding new projects, refactoring legacy codebases, writing unit tests, debugging unfamiliar libraries, and onboarding junior developers who learn by observing the AI’s reasoning. Because the model adapts to the active repository’s style and dependencies, recommendations stay contextually accurate across Python, JavaScript, TypeScript, Java, C#, Go, and other mainstream languages. Sixty incremental versions have appeared since the first public build, indicating rapid cadence of improvement; release 3.5.38 refines completion latency and expands the agent’s capacity to resolve cross-file symbol references. The installer bundles the IDE core, language runtimes, Git integration, and a private local proxy so that no separate AI service subscription is required to start coding. Trae is available for free on get.nero.com, where downloads are provided through trusted Windows package sources such as winget, always delivering the latest build and supporting batch installation alongside other applications.

Tags:

ai 159

code 84

coding 70

develop 103

development 136

editing 48

editor 205

large-language-model 75

llm 93

programming 110