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## llm-wiki.md

      
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              Created
              April 23, 2026 07:45
                — forked from rohitg00/llm-wiki.md
            
              
                LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory
              
          
    LLM Wiki v2

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.
What the original gets right

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.

  
## llm-wiki.md

      
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              Created
              April 23, 2026 04:42
                — forked from karpathy/llm-wiki.md
            
              
                llm-wiki
              
          
    LLM Wiki

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.
The core idea

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.

  
## latency.markdown

      
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                / latency.markdown
            
            
              Created
              December 19, 2019 08:49
                — forked from hellerbarde/latency.markdown
            
              
                Latency numbers every programmer should know
              
          
    Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

  
## latency.markdown

      
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                endlessc
                / latency.markdown
            
            
              Created
              December 19, 2019 08:49
                — forked from hellerbarde/latency.markdown
            
              
                Latency numbers every programmer should know
              
          
    Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

  
## .git-commit-blog.txt
# Type(<scope>): <subject>

# <body>

# <footer>

# type字段
# add 增加新博客/页面（add new post/page）
# correct 改错别字/语法（correct spelling/grammar ）
# update 更新内容（update content）

## .git-commit-template.txt
# Type(<scope>): <subject>

# <body>

# <footer>

# Type should be one of the following:
# * feat (new feature)
# * fix (bug fix)
# * docs (changes to documentation)
	# Type(<scope>): <subject>

	# <body>

	# <footer>

	# type字段
	# add 增加新博客/页面（add new post/page）
	# correct 改错别字/语法（correct spelling/grammar ）
	# update 更新内容（update content）