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Practical DSPy for AI Agents: Structured Design, Optimization Cycles, and Real-World Deployment.

by Leo Brooks
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₹1,777.00
Original price ₹1,777.00
Original price ₹1,777.00
₹1,777.00
Current price ₹1,777.00

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Book cover type: Paperback
  • ISBN13: 9798273881716
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 178
  • Original Price: USD 17.0
  • Language: English
  • Edition: N/A
  • Item Weight: 318 grams
  • BISAC Subject(s): Artificial Intelligence / Natural Language Processing


Are you ready to move beyond brittle prompts and build AI agents that are predictable, modular, and production-ready?
Practical DSPy for AI Agents is a hands-on guide for AI engineers, Python developers, and ML practitioners who want to design structured, optimized, and reliable agent workflows using DSPy's declarative programming model.
Unlike traditional prompt-based AI, DSPy allows you to define exact agent behaviors, optimization cycles, and modular workflows in Python, giving you control, reliability, and scalability in real-world applications.
What You'll Learn

  • How to design predictable DSPy agents with declarative input-output modeling
  • Building modular, reusable components for structured workflows
  • Implementing optimization cycles like BootstrapFewShot, MIPRO, and self-improving pipelines
  • Integrating RAG workflows, tools, APIs, and multi-agent systems
  • Designing multimodal pipelines for text, audio, and visual data
  • Deploying agents in production with MLflow, Redis, and fault-tolerant architectures
  • Monitoring performance, ensuring reliability, and controlling cost in real-world environments
Who This Book Is For
  • AI engineers building reliable agent systems
  • Python developers transitioning from prompts to structured AI workflows
  • ML practitioners and technical teams deploying scalable AI solutions
  • Technical leaders architecting enterprise-grade AI pipelines
Whether you are creating autonomous research agents, document processing pipelines, or multi-agent orchestration systems, this book equips you with the practical skills, architecture patterns, and optimization techniques to build DSPy agents that work-and keep improving over time.
Stop guessing with prompts. Start engineering AI agents that deliver predictable, real-world results.

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