Engineers
~60–90 pages
Prompt Compression in Production
Reducing Token Count Without Losing What the Model Needs
Free Ebook
EPUB + Markdown
By David Kelly Price
About This Ebook
Engineers running LLM systems at scale where context size directly impacts latency and cost
What you'll learn:
- 1. Why Compression Is Necessary
- 2. What Can Be Compressed and What Cannot
- 3. Extractive Compression: Summary and Selection
- 4. Abstractive Compression: Rewriting for Density
- 5. Learned Compression: Soft Tokens and Embeddings
- 6. Compression Evaluation: Faithfulness and Task Performance
- 7. Integration Patterns: Where Compression Lives in the Pipeline
- 8. Production Considerations
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The tool this book explores — semantic search, context routing, and code intelligence for Claude Code.