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发布时间:2026-07-26 | 浏览:2
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A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
Manage Packages and Dependencies See Installed Packages See Dependency Tree Remove Hanging Dependencies Remove All Packages
See Installed Packages
See Dependency Tree
Remove Hanging Dependencies
Remove All Packages
Manage Files Installation Paths
Installation Paths
Build your own content team with Claude Code, Codex, or Cursor. Give each job to the best model, and make them argue before anything ships.
This is the full recipe from the ClickMinded "Little Guys Strike Back" webinar. It's not one magic prompt. It's a small editorial team you run from a single agent: strategy, research, writing, editing, images, and distribution, each handled by the best model for the job, checking each other's work.
Copy this whole document into your agent (Claude Code, Codex, or Cursor) and work through it top to bottom. Every step has a prompt you can paste and adapt.