# The Map Everyone's Missing

LLM Knowledge Engineering Ecosystem -- 2026
2022 -- 2024
Prompt Engineering
"Craft the perfect prompt"
-->
2025
Context Engineering
Karpathy
"Construct the dynamic context window"
-->
2026
Harness Engineering
Fowler, OpenAI
"Orchestrate the entire system around the model"
KNOWLEDGE SOURCES

### RAG Pipelines Ch02

- Self-RAG, Corrective RAG
- Adaptive RAG, Agentic RAG
- 1,250x cheaper than long context
- 71% of enterprises use RAG

### Knowledge Graphs Ch02

- Microsoft GraphRAG
- Entity-relationship reasoning
- Multi-hop query resolution

### Long Context Windows Ch02

- 1M+ token windows (Claude, Gemini)
- Best for static, bounded docs
- "Lost in the middle" degradation

feeds into
CONTEXT ENGINEERING

### Dynamic Context Assembly Ch03

- 6-layer context model (Anthropic)
- KV-cache hit rate = key metric
- 100:1 input-to-output ratio

### System Prompts + Instructions Ch03

- Rules, constraints, persona
- Routing tables for skill dispatch

### Tool Definitions + Schemas Ch07

- MCP protocol standard
- 97M+ monthly SDK downloads
- Meta-tool pattern for efficiency

### Conversation + Memory Ch06

- Episodic / Semantic / Procedural
- Cross-session persistence
- Zettelkasten-inspired (A-MEM)

shapes
HARNESS ENGINEERING

### Skill Systems + Routing Ch05

- 700K+ community skills
- Skill Graphs (arscontexta)
- Progressive disclosure routing
- 85-95% token reduction

### Agent Architecture Ch04

- Planner / Generator / Evaluator
- Sprint contracts for QA
- 6x performance gap (Meta-Harness)

### Safety + Control Ch04

- Guides (feedforward) vs Sensors (feedback)
- Computational vs Inferential controls
- Multi-layer content guards

### MCP / Tool Layer Ch07

- Universal protocol standard
- Linux Foundation governance
- Auth, sandboxing, audit trails

The model is the CPU. Context is RAM. The harness is the OS.
Each generation contains the last. Harness engineering includes context engineering, which includes prompt engineering.
awesome-llm-knowledge-systems -- The first unified guide connecting every piece of the AI knowledge ecosystem.