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Context Engineering: Engineering Information for AI Systems
- Author: J.C. Ködel
- Format: PDF
- Length: 371 pages
- Source File: /library/Context Engineering/source-file.pdf
- Top-Level Sections: 36
- Note: Sections 1–2 are orientation/front matter; the main technical argument begins in Section 3.
Contents
- About the author
- Map of the trilogy
- How LLMs use context
- Tokens and context windows
- Memory and limits
- The context cycle
- Context rot: why large contexts degrade quality
- Token economics: the real cost of bad context
- Parametric calculation: cost of irrelevant context
- Prompt engineering vs context engineering: why the prompt became a second-order variable
- Specifications
- Living documentation
- ADRs
- Conventions
- Persistent context files
- Project organization
- Modularization
- Context for brownfield projects
- Context layers
- Context packing
- Context recovery
- Context validation
- Context compression
- Context isolation
- RAG vs direct context
- MCP and tools as dynamic context
- Context security and trust
- Where to start
- Development loops with AI
- Measuring context: how to evaluate whether your context improves results
- Principles applied: chat, IDE, terminal and CI
- Teams: context as a repository asset
- Preparing a project (from scratch and from a legacy system)
- A complete AI-guided implementation
- Post-mortem: where the context failed and how it was recovered
- References