Uploaded May 2026 | Updated September 2026, 2 hours ago

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Chapters:
0:00 Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise.
03:22 Why "More Tokens" Means Worse Results
04:52 "Lost in the Middle" Explained
05:36 The Cost & Complexity of Attention (N²)
07:34 1. Deterministic Trimming (Sliding Window)
08:18 2. Source-Level Filtering (Highest Impact)
09:21 3. Mechanical Compaction
10:06 4. Terminal Sequence Collapse
10:50 5. Semantic Summarization (Map Reduce vs. Stuffing)
12:10 6. Retrieval-Based Compaction & Contextual RAG
13:39 7. Knowledge Graphs & Graph RAG
14:40 8. Learned Prompt Compression (LLMLingua)
15:47 9. Multi-Tier Memory (MemGPT)
16:43 10. Agentic Context Engineering (ACE)
17:40 Bonus: Output Optimization Tricks
19:48 Best Practices: When (and When Not) to Compact
21:35 Multi-Agent & Model Routing Strategies
23:44 Actionable: Order of Operations for AI Engineers

#aiengineering #contextengineering #compaction