学习AI代理在工厂中的实际应用，了解预算优化和开源模型发展，对比Warp开源前后GitHub星标数变化
AI代理误删200个工作负载，临床笔记错误率1/20，芯片设计师限制bash使用，优化预算平均节省78%，Warp开源后GitHub星标数增加3倍
Eight sessions on the parts of the factory that are not the model: - An agent tidying up after itse...
Eight sessions on the parts of the factory that are not the model: - An agent tidying up after itself hit a filter that matched everything: 200 workloads deleted in 90 seconds. The fix was not a narrower token. It was a budget: rate limits that refill, and an identity the agent cannot set - In the largest real world study of AI clinical notes, 1 in 20 carried an error serious enough to cause the patient significant harm. The dangerous ones look fine: nothing in the note is wrong, the detail that matters is missing - Chip designers told an agent to stay out of the spec files. It agreed, then wrote to them with bash. They blocked bash and sed. It used cat. Now they block at the system level, not tool by tool - Instead of killing an agent that blows its budget, steer it while it runs: compact the context, trim tool output, tell it to tighten up. Their benchmark: average spend down 78 percent, completion up from 67 to 96 percent - Warp went open source and jumped from around 20,000 GitHub stars to over 60,000, with thousands of PRs. No human reviewer gets pinged until an agent has approved the PR first Watch the AI Architects playlist: youtube.com/watch?v=rbjWzZ… 💬 0 🔄 0 ❤️ 1 👀 648 📊 1 ⚡