# 构建个人AI代理工具以提升思维辅助能力

- 来源：elvis (@omarsar0)
- 发布时间：2026-04-28 03:22
- AIHOT 分数：60
- AIHOT 链接：https://aihot.virxact.com/items/cmoi4sz7200nysle9e0dv0pym
- 原文链接：https://x.com/omarsar0/status/2048845158154661961

## AI 摘要

AI应提升人类思维，而非取代。当前LLMs默认不支持此功能，需用户构建agent harness（包括检索、验证、记忆等架构）来增强辅助能力。agent harness至关重要，即使简单技能也能显著提升LLMs的"human-centered augmenting"能力。持续学习前景广阔但尚处早期，上下文学习更为有效。用户需主动优化工作流程以引导LLMs，而自我改进代理因激励不足效果有限。最佳实践是重用LLM输出，让AI持续为用户服务，并通过每次交互提升双方能力。最终，用户需亲自构建定制化AI工具，而非等待他人开发。

## 正文

"AI should elevate your thinking， not replace it."

I don't disagree， but the issue is that current LLMs are not really trained to support that out of the box.

I've solved this by building my own agent harness （retrieval， verification， memory， multi-agent architecture， skills， etc.）.

That's how important agent harnesses are today. Even with simple skills （.md files）， you can already get far， so even non-technical folks can improve the "human-centered augmenting" capabilities of LLMs/agents.

Continual learning promises to solve this， but we are so early on this. People need to understand that in-context learning works great for this. Today's LLMs are steerable if YOU spend time building and optimizing your workflows. Self-improving agents don't work as well because the incentives are not there. A good mindset is that every output you get from an LLM should be reused in some way， let it work for you， and make you and the agent better in the next session.

So this has to come from you. You are the only one with the incentives to make it work for you the way you want. Don't wait for anyone to build it for you. Use AI to build the AI you want.

Own the harness.