行业71°

Jerry Liu主持AI晚宴,聊智能体循环与代码审查

We have an idea for dinner 2 already :) But what ideas are you all interested in? - technical top...

精选理由

Jerry Liu的AI圈饭局聊了智能体循环,说多数人不用Codex的/loop,还赌1-2年内没人review代码。想听一线真实观点的可以看。

AI 摘要

Jerry Liu与Devin Horthy共同主持了一场创始人晚宴,主题聚焦agent loops和loop engineering。与会者中大多数并未主动在Codex或Claude Code中使用/loop功能。多数人认为1-2年内将无人审查代码,但更关键的问题是否还需要审查任何内容。讨论还强调,AI输出质量仍取决于人的技能,人类需负责最大化输出并减少slop化。关于上下文,最少只需代码库加文档,研究或计划文件仅适合一次性任务。

原文 · Jerry Liu

We have an idea for dinner 2 already :) But what ideas are you all interested in? - technical top...

We have an idea for dinner 2 already :) But what ideas are you all interested in? - technical topics like rl envs, continual learning, cloud agents, world models - general startup / company building from plg, growth, GTM, talent, etc Jerry Liu @jerryjliu0 Yesterday I cohosted a dinner with @dexhorthy with a wonderful group of founders, to talk about agent loops and loop engineering. Some interesting insights: * Most of our group was *not* actively using /loop in Codex/Claude Code * You can build long-running autonomous agent loops through multi-agent handoffs, event triggers, or….just stacks of cron jobs (?) * Almost everyone believes that no one will be reviewing code in 1-2 years. * The more interesting question is whether we’d be reviewing *anything* in 1-2 years. * AI is still a bit of a skill issue. Humans are responsible for maximizing AI output and reducing slopification. * Will human intellect provide alpha as models get better, or will the playing field be leveled? Most people think it will be leveled a bit, but there is a need for humans to provide alignment, guardrails, judgment, creativity. * The minimum amount of context you need for AI could be just the codebase with some documentation. Any research/plan files are for one-off tasks and not meant to be maintained. Having a self-organizing wiki is nice but adds complexity. If you missed this one, we’ll be hosting more dinners like this on a regular cadence! If you have thoughts on what we should talk about, let us know :) (e.g. continual learning, RL envs, competitive differentiation vs. Anthropic, etc.) 🔗 View Quoted Tweet 💬 7 🔄 0 ❤️ 5 👀 1326 📊 7 ⚡