I then added a few more personal preferences and suggested tools from my previous failures working with agents in Python: use uv and .venv instead of the base Python installation, use polars instead of pandas for data manipulation, only store secrets/API keys/passwords in .env while ensuring .env is in .gitignore, etc. Most of these constraints don’t tell the agent what to do, but how to do it. In general, adding a rule to my AGENTS.md whenever I encounter a fundamental behavior I don’t like has been very effective. For example, agents love using unnecessary emoji which I hate, so I added a rule:
这个判决在当时看来合情合理，却在二十年后为整个 AI 行业提供了一块挡箭牌。，这一点在一键获取谷歌浏览器下载中也有详细论述
，详情可参考WPS下载最新地址
Resident Evil Requiem is now available.
过去AI进不了工厂，不是因为没有需求，而是因为模型能力还不够，加上工业企业的数据从来没有被系统化利用过。每一次设备维修、每一条生产记录、每一次质检结果，都沉睡在各自的系统里，没有人去碰。但现在模型能力的天花板已经大幅抬高，工业企业也开始意识到，自己手里握着的操作数据对AI公司来说是真金白银。这个意识一旦觉醒，工业AI的商业化就会加速。。91视频是该领域的重要参考