本系列教程介绍如何从零搭建一个前端CI服务器,以及如何优化其性能。
本系列教程均基于Gitlab CI,其它系统的酌情参考。
| // Use Gists to store code you would like to remember later on | |
| console.log(window); // log the "window" object to the console |
A pattern for building personal knowledge bases using LLMs. Extended with lessons from building agentmemory, a persistent memory engine for AI coding agents.
This builds on Andrej Karpathy's original LLM Wiki idea file. Everything in the original still applies. This document adds what we learned running the pattern in production: what breaks at scale, what's missing, and what separates a wiki that stays useful from one that rots.
The core insight is correct: stop re-deriving, start compiling. RAG retrieves and forgets. A wiki accumulates and compounds. The three-layer architecture (raw sources, wiki, schema) works. The operations (ingest, query, lint) cover the basics. If you haven't read the original, start there.