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Artículo: AMZ-B0G6PT1Z2N
AGNO Unleashed: Multi-Domain Multi-Agent Systems: Design, build, and deploy production-ready multi-agent systems with modern LLMs
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Kindle
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0.20 kg
0.20 kg
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Amazon
Amazon
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USA
USA
Sobre este producto
- AGNO Unleashed: Multi-Domain Multi-Agent SystemsAGNO Unleashed is a practical guide to designing, building, and deploying production-ready multi-agent systems using modern large language models.This book goes beyond prompt engineering and isolated agent demos. It focuses on real architectures, agent collaboration, tools, workflows, and deployment strategies that work in real-world environments.If you want to move from experimental agents to scalable, reliable AI systems in production, this book is for you. What You’ll LearnWhen to use single agents vs. multi-agent systemsHow to design agents with clear responsibilities and memoryHow to orchestrate teams of agents for parallel and collaborative executionHow to integrate tools using structured outputs and tool callingHow to build complex workflows for multi-step processesHow to use the Model Context Protocol (MCP) to connect agents to external systemsHow to configure and optimize LLMs from multiple providersHow to handle streaming, error recovery, retries, and fallbacksHow to deploy and monitor agentic systems in production Who This Book Is ForThis book is written for software engineers, backend developers, AI/ML engineers, and architects who want to build robust and maintainable agentic systems.A basic understanding of Python and general software development concepts is recommended. What Makes This Book DifferentUnlike many books that focus only on prompts or toy examples, AGNO Unleashed takes a systems-level, engineering-driven approach to multi-agent systems.It emphasizes real-world concerns such as scalability, cost control, observability, and long-term maintainability — making it suitable for both individual developers and production teams. About the AuthorAlexandre Evangelista de Souza is a software engineer with extensive experience in backend systems, distributed architectures, and AI-powered applications. His work focuses on bridging the gap between cutting-edge AI capabilities and real-world production needs.
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