想让你家智能体越用越聪明？这个线程给了三个可落地的改进方向，尤其是从用户操作中学习那块，不少人都忽略了。
Santiago Valdarrama 分享智能体自我改进的三个途径：模型层（仅适用于代码和数学，由大实验室负责）、执行框架层（步骤、工具和安全检查，容易控制且回报大）、上下文层（纯文本记录学习内容，最易入手）。他还强调从用户纠正智能体决策的每个实例中学习，真实反馈无可替代。文章提供了明确的优先级和实操建议。
How to build an agent that gets better over time: …
How to build an agent that gets better over time:
There are 3 areas an agent can learn from:
1. The model: Only works for code and math, where a computer can score right vs. wrong. Leave this to the big labs.
2. The harness: These are the steps, tools, and safety checks you build around the model. This is easy to control and will give you a huge payoff now.
3. The context: This is a plain-text representation of what the agent has learned. Probably the simplest place to start.
But there's something else that most people miss:
Your agent should learn from its users.
You want to learn from every time a user fixes the agent's decision. Nothing can replace feedback from real usage.