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:
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All ASR models share the same audio pipeline: 16kHz mono WAV → 80-bin Mel spectrogram → FastConformer encoder.，推荐阅读同城约会获取更多信息
另一层更致命的是责任漂移。模型输出参与决策、代理系统参与执行，过失主体更容易在供应链里移动，从部署方漂到集成商，再漂到平台与模型提供者。巴伦指出什么算AI、什么算AI使用在司法与理赔中仍存在解释空间，这会拉长争议、抬高准备金不确定性，也迫使承保条件更前置。，更多细节参见搜狗输入法2026
賴嘉敏對BBC中文解釋說，只要寵物犬進入了食環署圖則紀錄中的餐廳範圍，便已違反禁狗法律。
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