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"item_title" : "DSPy Agentic Systems",
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"item_description" : "using Stanford's DSPy framework. In this in-depth exploration, Alex Ming introduces you to a declarative approach to AI one where agents are not just coded but taught to reason, evaluate, and improve.You'll discover how to: Build modular, reusable agent pipelines that integrate multiple reasoning componentsImplement contextual memory systems for persistent understandingIntegrate LLMs to enhance logic, retrieval, and decision-makingCreate feedback and evaluation loops for continual learningDeploy multi-agent collaboration systems that share goals and information dynamicallyWith its focus on clarity and engineering rigor, this book equips you to move beyond static prompts into the era of self-improving, context-driven AI. Whether you're building assistants, copilots, or research agents, DSPy Agentic Systems provides the tools and design thinking to craft intelligent systems that truly evolve over time.",
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DSPy Agentic Systems : Designing Adaptive AI Agents with Declarative Reasoning and Memory in Python
by Alex Ming
Overview
using Stanford's DSPy framework. In this in-depth exploration, Alex Ming introduces you to a declarative approach to AI one where agents are not just coded but taught to reason, evaluate, and improve.
You'll discover how to:
- Build modular, reusable agent pipelines that integrate multiple reasoning components
- Implement contextual memory systems for persistent understanding
- Integrate LLMs to enhance logic, retrieval, and decision-making
- Create feedback and evaluation loops for continual learning
- Deploy multi-agent collaboration systems that share goals and information dynamically
This item is Non-Returnable
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Details
- ISBN-13: 9798274350594
- ISBN-10: 9798274350594
- Publisher: Independently Published
- Publish Date: November 2025
- Dimensions: 10 x 7 x 0.47 inches
- Shipping Weight: 0.87 pounds
- Page Count: 222
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