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Engineering DSPy: The Practitioner's Guide to Compiling Robust, Self-Optimizing AI Agents
Paperback
Publisher: Independently Published
Published: Dec 15 2025
Pages: 142
Weight: 0.57
Height: 0.30 Width: 7.00 Depth: 10.00
Language: English
In Engineering DSPy: The Practitioner's Guide to Compiling Robust, Self-Optimizing AI Agents, you'll learn how to build reliable, production-grade LLM applications-from advanced RAG systems and multi-tool agents to self-correcting pipelines-without endless manual prompt tweaking.
Key topics include:
- Overcoming prompt brittleness with programmatic compilation
- Designing retrieval-augmented generation (RAG) that learns signal from noise
- Creating agentic workflows with ReAct, tools, and hallucination reduction
- Enforcing constraints with assertions and backtracking
- Distilling GPT-4-level performance into smaller, quantized models
- Tracing, caching, versioning, and FastAPI deployment
Move beyond prompt engineering-start programming language models that improve themselves. Ideal for anyone building scalable AI agents with DSPy.
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