文章摘要
Y Combinator CEO Garry Tan宣称其AI编码代理每天部署3.7万行代码,引发争议。一名波兰资深开发者检查其AI博客后,批评这些代码是“AI垃圾代码”,并指出实际生产中存在大量问题。
文章总结
Y Combinator CEO加里·谭近日在社交媒体上自夸,称其与AI编码代理每天在五个项目中部署37000行代码,并已连续72天保持这一节奏。然而,一位波兰游戏开发者兼高级软件工程师Gregorein深入检查了谭的AI博客网站代码后,发现实际情况远非如此。Gregorein指出,该网站存在大量臃肿和低效问题:用户访问时浏览器需发起169次服务器请求,总数据量达6.42兆字节,而对比Y Combinator旗下的极简网站Hacker News仅需7次请求、12千字节;网站直接向用户浏览器发送28个测试文件,共300千字节的开发者脚手架代码;加载78个JavaScript控制器,涵盖AI图像生成、语音提取等功能,但首页并未使用;网站标志是一只熊,却以八种格式下载,包括一个0字节的空文件;使用未压缩的老式PNG图片,单张近2兆字节,而现代格式仅需300千字节;此外还有重复页面内容、空CSS文件、只读页面加载大型富文本编辑器、缺失图像描述,以及故意绕过广告拦截器的分析代码。Gregorein强调,这仅是前端代码的问题,后端和数据库尚未审查。他总结道,AI编码工具虽能快速生成大量代码,但质量才是关键,数量不等于质量。谭的案例表明,若缺乏严格审查和测试,AI生成的代码会导致功能故障、安全漏洞和后续修复难题。Gregorein认为,当前AI让代码生成速度远超人类审查能力,而谭的回应似乎是“停止审查”,这类似于Facebook“快速行动,打破常规”的旧策略,但历史证明其效果不佳。
评论总结
根据评论内容,主要围绕Garry Tan使用AI工具每日生成37k行代码所引发的争议,核心观点如下:
1. 代码质量与效率的冲突(多数评论支持)
- 评论指出网站存在严重臃肿:169次服务器请求、6.42MB资源、28个测试文件、78个JavaScript控制器、8种格式的logo(含空文件)、未压缩的PNG等。
- 关键引用:
"The website ships 28 actual test files... 300 kilobytes of pure developer scaffolding that users never asked for."
"The site downloads the logo in eight different formats, including a completely empty 0-byte file."
2. 对“数量即质量”的批判(多数评论支持)
- 评论认为以代码行数(LoC)衡量成功是错误导向,AI工具导致代码膨胀而非优化。
- 关键引用:
"Measuring success in LoC is so wrong… It's like bragging that you took 10,000 steps to reach the store by walking in circles."
"How can anyone in their right mind think that growing a codebase by 200K LOC every week could possibly be a good thing?"
3. 对AI工具与专业判断的反思(部分评论支持)
- 评论指出AI工具缺乏专业判断,导致“能产出但不知好坏”的困境。
- 关键引用:
"This is what happens when you give people tools that let them achieve an outcome, without necessarily giving them the judgement or expertise to know whether the outcome is any good."
"You can make decent code with AI assistance... However, I’ve seen no evidence to suggest that you can do both."
4. 对“先发布后优化”策略的辩护(少数评论支持)
- 部分评论认为Tan的“先发布后优化”策略可行,尤其对于初创阶段。
- 关键引用:
"Garry Tan's point still stands: he never pretended to be building nice software. But his point was that he can now build AT ALL!"
"This may be what Tan does as well: first profitable, then correct."
5. 对行业普遍问题的批评(部分评论支持)
- 评论指出臃肿代码并非AI独有,而是行业长期问题,但AI加剧了此趋势。
- 关键引用:
"Bloat is not 'since generative AI coding' new. We always had it."
"Ironically the fastcompany page hosting the article... seems to do 300+ requests, with 29.4mb of resources."
6. 对AI工具价值的质疑(部分评论支持)
- 评论质疑AI工具的实际产出,认为其更多是“卖铲子”而非创造价值。
- 关键引用:
"Where are all the new businesses and tools? I only see more shovels being sold."
"What I really want from the people who have effectively unlimited tokens to spend, is to use that finding ways for the rest of us to produce higher quality output at lower costs."
总结:评论普遍认为Tan的AI驱动开发模式存在严重代码质量问题,但对其“先发布后优化”策略存在争议。多数评论强调质量优先于数量,并批评行业对AI工具的盲目追捧。