Skip to content

Plaban Nayak

Summary

AI engineer and author who wrote an in-depth technical analysis of the LLM Wiki pattern, including a full Python implementation of the pipeline.

Contributions

"Beyond RAG: How Andrej Karpathy's LLM Wiki Pattern Builds Knowledge That Actually Compounds"

Published April 2026 on Level Up Coding (Medium). The article provides:

  • Detailed explanation of the three-layer architecture and compilation analogy
  • Full Python implementation with CLI pipeline (init, ingest, query, lint, status, prompts commands)
  • Analysis of advantages and disadvantages of the pattern
  • Discussion of implications for AI engineers (memory architecture for agents, MCP integration)
  • Working codebase with clear module boundaries

Python Implementation

Built a working llm_wiki package with: - Five-step ingest pipeline (Resolve → Route → Synthesize → Embed → Update) - Four-step query pipeline (Embed → Search → Assemble → Stream) - Health lint checks with --deep contradiction analysis and --fix embedding regeneration - 24 named query templates across 6 categories - Prompt caching for ~90% cost reduction on repeated operations

Repository: github.com/plaban1981/llm_wiki_rag_pipeline