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:
Gartner研究总监Ranjit Atwal发出警示:“最终结果是你在市场上失去了选择。我们面临的是一个相当独特的情况。通常当内存价格飙升时,是因为生产问题限制供应。在这里,是来自超大规模数据中心的需求端压力推高了PC和智能手机的内存成本。”与内存行业早期的繁荣—萧条周期不同,这种短缺可能是长期的,并可能延续到2027年底。
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It's funny to consider, then, how cash is in fact quite amenable to automation.
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