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AI ecosystem · Context engineering

Context engineering, curated and live

Five topics from the PDF outline (Context Engineering, pages 147–176) in the same reference deck as LLMs, Prompt engineering, Fine-tuning, and RAG—from the chapter divider through agent-facing context, a full workflow build, Claude Skills, and manual vs agentic context pipelines (TOC pages 147–176).

Topic 1

What is Context Engineering?

Chapter divider plus the opening section: orchestration vs clever wording, dynamic context building blocks, and the retrieval bottleneck (PDF 147–149).

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Topic 2

Context Engineering for Agents

Tools, memory, formats, six context types (including tool results)—through the full agent context stack.

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Topic 3

Build a Context Engineering workflow

Reference pipeline: ingest, memory, web and paper search, filter, kickoff, and Streamlit demo (PDF 159–168).

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Topic 4

Context Engineering in Claude Skills

Demo wrap-up, main vs appendix context, and Skills as packaged procedures (PDF 169–171).

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Topic 5

Manual RAG Pipeline vs Agentic Context Engineering

Worked query, layered retrieval, and how Airweave-style stacks operationalize the ideas (PDF 172–176).

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How to read this track: Topics match the PDF table of contents under Context Engineering (pages 147–176 in the file; chapter divider 147, then subsections at 148 / 150 / 159 / 169 / 172). Page 146 is the end of RAG → agent memory. AI Agents starts at page 177 in AI agents →. Footer numbers on slides may differ from the file page index by one.