cff-version: 1.2.0
title: "The Map Everyone's Missing: LLM Knowledge Engineering in 2026"
message: "If you reference this guide in research, blog posts, or talks, please cite it using the metadata below."
type: dataset
authors:
  - family-names: Law
    given-names: Kenneth
    alias: kennethlaw325
abstract: >-
  An opinionated, structured synthesis of how LLM knowledge engineering
  evolved between 2022 and 2026. Connects RAG, knowledge graphs, long
  context, MCP, skill routing, agent memory, and progressive disclosure
  into one coherent map across three generations: prompt engineering
  (2022-2024), context engineering (2025), and harness engineering
  (2026). Includes a curated 2022-2026 timeline of inclusion-criteria
  filtered events, a glossary, twelve in-depth chapters, and a real-world
  case study.
keywords:
  - LLM
  - large-language-models
  - retrieval-augmented-generation
  - context-engineering
  - harness-engineering
  - agent-memory
  - knowledge-graph
  - model-context-protocol
  - progressive-disclosure
  - skill-systems
  - agent-architectures
  - 2026
license: MIT
repository-code: "https://github.com/kennethlaw325/awesome-llm-knowledge-systems"
url: "https://github.com/kennethlaw325/awesome-llm-knowledge-systems"
date-released: 2026-05-06
