我不是反向半人马
作者一年前曾撰文表示，即使不考虑伦理和环境问题，大型语言模型（LLM）辅助编程对他而言也不适用。如今，他发现在开源项目中收到越来越多由 LLM 生成的贡献代码，这让他感到沮丧。Cory Doctorow 将这类人工审核机器产出代码的角色称为"反向半人马"——被冷酷无情的机器操控的脆弱人类。作者坚决拒绝成为这样的人，并分享了如何抵制这种趋势。
相关报道
The author, who once advised his sister to use code libraries without fully understanding them, now finds himself unable to commit AI-generated code he doesn't fully comprehend. He recounts spending 10 hours fixing code that an LLM produced in 12 minutes, and notes that while others trust AI code generators like a car engine, his need to understand every line negates any productivity gains.
The article argues that many single-page app developers misuse divs or buttons with onclick handlers instead of proper anchor tags for navigation, breaking browser history, accessibility, and native link features. The author urges using native `<a href>` elements or framework Link components.
The article argues that disallowing trailing (or leading) separators in languages like JSON, Haskell, and Prolog was a design mistake, as it makes adding or removing elements more complex. It highlights languages like Python, Go, and Alloy that permit trailing commas, and notes potential parsing ambiguities when trailing separators are used in control-flow contexts.
The article argues that Lucas Costa's concept of "backpressure" for systems handling code-generating AI is a misnomer. Backpressure signals upstream processes to slow down, while Costa's suggestions are about improving quality, not reducing quantity. The author proposes "lean manufacturing" as a more accurate analogy for managing unstable inputs from AI-generated code.
The article explains that the Windows thread pool is optimized for throughput rather than low latency, which can cause delays in task execution. It discusses the trade-offs between throughput and latency when scheduling work on thread pools.