Performance and telemetry analysis of Trae IDE, ByteDance's VSCode fork (github.com)

Article summary

The article analyzes the performance and telemetry of Trae IDE, a fork of Visual Studio Code developed by ByteDance. The investigation reveals that Trae continues to transmit a broad set of data even with telemetry opt-out enabled, including hardware and usage metadata. The article also discusses the team's efforts towards transparency and their plans to release a dedicated Privacy Mode. The author notes that while the team has made improvements, Trae still consumes more resources than a standard VSCode setup.

Main themes

• Telemetry and privacy
• IDE performance
• Transparency and accountability
• AI-generated content
• Language barriers and translation

What commenters say

• Using AI to generate content can make it seem less credible and less worth reading, even if the conclusions are sound.
• The use of AI-generated content can be seen as a tradeoff between clarity and authenticity, with some preferring to read 'broken English' over potentially misleading AI-generated text.
• The provenance of a report, including whether it was written with AI assistance, is relevant to its credibility and trustworthiness.
• Some argue that AI-generated content is often low-signal and high-effort, making it not worth reading, while others see it as a useful tool for non-native English speakers.
• The tone and structure of AI-generated content can be altered, making it seem disingenuous or insincere, and potentially excluding readers who prefer authentic human writing.
• Disabling telemetry may be seen as a signal that a user has something to hide, leading to increased surveillance, and some argue that client-side telemetry should be avoided altogether.