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Working from home
3k followers · 54 following

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@coderabbitai

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Achievement: Pull Sharkx4Achievement: Pair Extraordinairex3Achievement: Starstruckx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor

Achievements

Achievement: Pull Sharkx4Achievement: Pair Extraordinairex3Achievement: Starstruckx4Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor

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rohitg00/README.md

Hi, I'm Rohit

Twitter LinkedIn Medium

London, UK. CNCF Ambassador. Docker Captain. Google Developer Expert (Cloud).

I build AI agent infrastructure and developer tools. 15K+ GitHub stars across 270+ repos. 100K+ member DevOps community.

Python TypeScript Rust Kubernetes MCP

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  1. agentmemory agentmemory Public

    #1 Persistent memory for AI coding agents based on real-world benchmarks

    TypeScript 15.8k 1.3k

  2. ai-engineering-from-scratch ai-engineering-from-scratch Public

    Learn it. Build it. Ship it for others.

    Python 10.7k 2.1k

  3. pro-workflow pro-workflow Public

    Claude Code learns from your corrections: self-correcting memory that compounds over 50+ sessions. Context engineering, parallel worktrees, agent teams, and 17 battle-tested skills.

    JavaScript 2.2k 205

  4. kubectl-mcp-server kubectl-mcp-server Public

    Published in CNCF Landscape: A MCP server for Kubernetes.

    Python 890 171

  5. awesome-claude-code-toolkit awesome-claude-code-toolkit Public

    The most comprehensive toolkit for Claude Code -- 135 agents, 35 curated skills (+400,000 via SkillKit), 42 commands, 176+ plugins, 20 hooks, 15 rules, 7 templates, 14 MCP configs, 26 companion app…

    JavaScript 1.8k 554

  6. LLM Wiki v2 — extending Karpathy's L... LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory
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    # LLM Wiki v2
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    A pattern for building personal knowledge bases using LLMs. Extended with lessons from building [agentmemory](https://github.com/rohitg00/agentmemory) 10K Stars ⭐️, a persistent memory engine for AI coding agents.
    
              
    
              
    
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    This builds on [Andrej Karpathy's original LLM Wiki idea file](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f). 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.
    
              
    
          
    
    
    
  
    

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