Book-Reader-Assist/library/Context Engineering/book-structure.md

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

1. About the author
2. Map of the trilogy
3. How LLMs use context
4. Tokens and context windows
5. Memory and limits
6. The context cycle
7. Context rot: why large contexts degrade quality
8. Token economics: the real cost of bad context
9. Parametric calculation: cost of irrelevant context
10. Prompt engineering vs context engineering: why the prompt became a second-order variable
11. Specifications
12. Living documentation
13. ADRs
14. Conventions
15. Persistent context files
16. Project organization
17. Modularization
18. Context for brownfield projects
19. Context layers
20. Context packing
21. Context recovery
22. Context validation
23. Context compression
24. Context isolation
25. RAG vs direct context
26. MCP and tools as dynamic context
27. Context security and trust
28. Where to start
29. Development loops with AI
30. Measuring context: how to evaluate whether your context improves results
31. Principles applied: chat, IDE, terminal and CI
32. Teams: context as a repository asset
33. Preparing a project (from scratch and from a legacy system)
34. A complete AI-guided implementation
35. Post-mortem: where the context failed and how it was recovered
36. References

Source Text Index

Extracted from source-file.pdf by tools/split_book.py. Read these instead of the PDF.

Folder	Section	PDF pages	Pages without extractable text
Front-Matter	Front matter	1–11	1
Chapter-01-About-the-author	About the author	12–13	none
Chapter-02-Map-of-the-trilogy	Map of the trilogy	14–15	none
Chapter-03-How-LLMs-use-context	How LLMs use context	16–22	none
Chapter-04-Tokens-and-context-windows	Tokens and context windows	23–30	none
Chapter-05-Memory-and-limits	Memory and limits	31–36	none
Chapter-06-The-context-cycle	The context cycle	37–42	none
Chapter-07-Context-rot-why-large-contexts-degrade-quality	Context rot: why large contexts degrade quality	43–48	none
Chapter-08-Token-economics-the-real-cost-of-bad-context	Token economics: the real cost of bad context	49–52	none
Chapter-09-Parametric-calculation-cost-of-irrelevant-context	Parametric calculation: cost of irrelevant context	53–57	none
Chapter-10-Prompt-engineering-vs-context-engineering-why-the-prompt	Prompt engineering vs context engineering: why the prompt became a second-order variable	58–64	none
Chapter-11-Specifications	Specifications	65–73	none
Chapter-12-Living-documentation	Living documentation	74–81	none
Chapter-13-ADRs	ADRs	82–89	none
Chapter-14-Conventions	Conventions	90–98	none
Chapter-15-Persistent-context-files	Persistent context files	99–108	none
Chapter-16-Project-organization	Project organization	109–117	none
Chapter-17-Modularization	Modularization	118–129	none
Chapter-18-Context-for-brownfield-projects	Context for brownfield projects	130–139	none
Chapter-19-Context-layers	Context layers	140–150	144
Chapter-20-Context-packing	Context packing	151–162	none
Chapter-21-Context-recovery	Context recovery	163–176	none
Chapter-22-Context-validation	Context validation	177–189	none
Chapter-23-Context-compression	Context compression	190–203	none
Chapter-24-Context-isolation	Context isolation	204–216	none
Chapter-25-RAG-vs-direct-context	RAG vs direct context	217–232	none
Chapter-26-MCP-and-tools-as-dynamic-context	MCP and tools as dynamic context	233–245	none
Chapter-27-Context-security-and-trust	Context security and trust	246–254	none
Chapter-28-Where-to-start	Where to start	255–256	none
Chapter-29-Development-loops-with-AI	Development loops with AI	257–269	none
Chapter-30-Measuring-context-how-to-evaluate-whether-your-context	Measuring context: how to evaluate whether your context improves results	270–284	none
Chapter-31-Principles-applied-chat-IDE-terminal-and-CI	Principles applied: chat, IDE, terminal and CI	285–305	none
Chapter-32-Teams-context-as-a-repository-asset	Teams: context as a repository asset	306–316	none
Chapter-33-Preparing-a-project-from-scratch-and-from-a-legacy-system	Preparing a project (from scratch and from a legacy system)	317–333	none
Chapter-34-A-complete-AI-guided-implementation	A complete AI-guided implementation	334–353	none
Chapter-35-Post-mortem-where-the-context-failed-and-how-it-was	Post-mortem: where the context failed and how it was recovered	354–366	none
Chapter-36-References	References	367–371	none