# Cursor Chat: ai-agent-book

## Metadata
- **Project**: ai-agent-book
- **Path**: `/Users/boj`
- **Date**: 2025-09-22 07:52:46
- **Session ID**: `287c3319-9baf-4c06-a0f8-fa65b51baca9`

## Conversation

### 👤 You

在 chapter3.md 中的开头部分，需要增加来自 @http://www.incompleteideas.net/IncIdeas/BitterLesson.html the bitter lesson 的思考，特别是：

The second general point to be learned from the bitter lesson is that the actual contents of minds are tremendously, irredeemably complex; we should stop trying to find simple ways to think about the contents of minds, such as simple ways to think about space, objects, multiple agents, or symmetries. All these are part of the arbitrary, intrinsically-complex, outside world. They are not what should be built in, as their complexity is endless; instead we should build in only the meta-methods that can find and capture this arbitrary complexity. Essential to these methods is that they can find good approximations, but the search for them should be by our methods, not by us. We want AI agents that can discover like we can, not which contain what we have discovered. Building in our discoveries only makes it harder to see how the discovering process can be done.

然后据此，引入两种核心机制，一是从现有知识库中学习现有人类知识，二是通过自主探索学习，对应本章的二三部分。本章第一部分 RAG 基础是学习现有人类知识和通过自主探索学习共同的基础。

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### 🤖 Cursor Assistant

Okay, I will begin by reading the file `book/chapter3.md` to understand its current structure.

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### 🤖 Cursor Assistant

好的，我明白了。我将根据您的要求，在 `chapter3.md` 的开头部分，增加一段源于 "The Bitter Lesson" 的思考，并以此为引，介绍本章将要探讨的两种核心学习机制——从现有知识库学习和通过自主探索学习，同时点明 RAG 是这两者的共同基础。

我将首先阅读 `chapter3.md` 文件以了解当前结构，然后为您撰写新的引言并更新文件。

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