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Multi-Agent Workflows with SLMs: Smarter, Faster, and More Efficient AI Systems

by Bernand Bernie
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Current price ₹2,347.00
Original price ₹2,690.00
Original price ₹2,690.00
Original price ₹2,690.00
(-13%)
₹2,347.00
Current price ₹2,347.00

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Book cover type: Paperback
  • ISBN13: 9798299481280
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 222
  • Original Price: GBP 20.69
  • Language: English
  • Edition: N/A
  • Item Weight: 395 grams
  • BISAC Subject(s): Programming / Algorithms

Artificial intelligence is evolving beyond giant, expensive models. The future lies in Small Language Models (SLMs) - efficient, adaptable systems that can run on modest hardware, deliver faster responses, and integrate seamlessly into production environments. But the real breakthrough comes when SLMs are orchestrated together into multi-agent workflows.

This book provides a comprehensive guide to building, scaling, and governing multi-agent systems with SLMs. Written for engineers, researchers, and applied AI practitioners, it explains how to design efficient workflows where multiple specialized agents collaborate, validate each other, and outperform a single large model.

Key areas include:

  • Why SLMs matter: cost and latency trade-offs vs. LLMs, and where they win in practice.

  • Agentic patterns: from ReAct and Reflexion to Graph-of-Thoughts, voting councils, and self-consistency.

  • Architectures: pipelines, hubs, and councils with robust hand-offs, retries, and deadlines.

  • Infrastructure: serving SLMs efficiently with quantization, batching, and optimized runtimes.

  • Memory and retrieval: vector databases, summarization strategies, and privacy-aware storage.

  • Frameworks in action: LangGraph, AutoGen, CrewAI, DSPy, LlamaIndex, smolagents.

  • Evaluation & observability: benchmarks, CI/CD test gates, dashboards, and regression alerts.

  • Governance & safety: guardrails, auditability, and policies for production systems.

  • Case studies & playbooks: real-world workflows in customer support, analytics, CI/CD, and enterprise RAG.

Unlike books that focus only on frameworks or introductions to small models, this work is practical and production-oriented. It bridges the gap between theory and deployment, offering actionable patterns, design strategies, and reliability practices that today's AI engineers demand.

Whether you are an AI engineer seeking efficiency, a researcher interested in orchestration, or a professional preparing for the shift from monolithic LLMs to collaborative SLM ecosystems, this book gives you the tools to build smarter, faster, and more efficient AI systems.

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