A 3-阶段 智能路由 架构 for My Own AI 智能体✎ Edit

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A 3-阶段 智能路由 架构 for My Own AI 智能体

时间 I first joined this OpenClaw group, members actively shared experiments, technical experiences and projects.

然后 came spam and scammers, followed by competing product promotions. And now, memes have practically taken over the group.

That drift is part of why I went the other direction and built my own lightweight AI 智能体 to replace OpenClaw - no unnecessary complexity, no bloated function surface I never asked for.

My 3-阶段 智能路由 架构:

  1. Redis & MySQL Cache – 再利用 existing data and results so I'm not paying to recompute what I already have.
  2. Frequent Scripts – Handle the repetitive work deterministically, with zero unnecessary LLM calls in the path.
  3. Intelligent 模型 路由 – Hit the lowest-cost capable model first and only escalate up the chain when the task actually demands it.

Tech 技术栈: Web-命令行, Redis, MySQL and Telegram as my on-the-go interface.

运行中 my own AI 智能体, I've shipped 100+ standalone web applications, along with a lot of server and infrastructure work underneath them:

  • Linux server provisioning and VM management
  • PostgreSQL and MySQL
  • Redis caching
  • Docker and container management
  • Nginx and reverse proxy
  • Gitea and Git version control
  • Timeshift, snapshots and backup management
  • 服务器 monitoring and deployment automation

The interesting part? 总计 AI model costs stay below USD 40/月, and that includes running my own distilled model.

应用 development, server operations and infrastructure management - all driven through my own AI 智能体.

Less overhead. Smarter routing. More engineering.

How about everyone else? What have you been building, experimenting with or improving lately?

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Apa pendapat anda?

Komen disemak sebelum diterbitkan. 电子邮件 diperlukan untuk moderasi dan tidak dipaparkan kepada pembaca.

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Suda Thailand

看第二遍才注意到server and infras 100的细节。

Miguel Philippines

文章对时间 I first joined提供了很好的起点,值得继续跟进。

Liza Philippines

如果有更多frequent scripts – handle的数据和结果会更完整。

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