Show HN: An experiment in automated long-horizon builds with AMQP 0.9.1
My cofounders and I are in the process of spinning up an AI integration lab, and over the last year we've consumed billions of tokens across multiple American, European, and Chinese models as a force multiplier for building out our products. However, despite our extensive technical expertise, we've still discovered there are long-term ramifications to heavy agentic AI usage. So I decided to run an experiment for us: given a specification, can an LLM fully, concretely, and correctly implement an
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points · 1 votes
2026-11-03 12:00:07.772Z
cumulative since publication
研究分析
项目记录
仓库：siennathesane/switchboard。 来源描述：My cofounders and I are in the process of spinning up an AI integration lab, and over the last year we've consumed billions of tokens across multiple American, European, and Chinese models as a force multiplier for building out our products. However, despite our extensive technical expertise, we've still discovered there are long-term ramifications to heavy agentic AI usage. So I decided to run an experiment for us: given a specification, can an LLM fully, concretely, and correctly implement an
采用记录与比较对象
来源票数: 1 votes (2026年11月3日 UTC; cumulative since publication)；前次同口径记录为 1（2026年11月3日 UTC），两个观测值不等于需求增长。 可供比较的近期同类记录：“google/skills” (GitHub Trending, 2026年11月5日)；“mattpocock/skills” (GitHub Trending, 2026年11月5日)。主题相近仅用于导航，未核验其是否属于同一需求或独立证据。
采用判断
应与它要替代的工具或人工流程比较。现有记录支持发现项目，尚不能确认可靠性、运行成本优势或商业采用。
尚未核验的门槛
尚未核验：许可证权限、硬件要求、安装步骤、维护状态，以及包含失败样例的代表性任务。
下一步试验
选择一个真实任务和现有替代方案，记录 commit、环境、输入、输出、耗时与失败行为；保留结果后再给出采用建议。