Building Agentic and Autonomous AI Agents: Design Intelligent LLM Agents with Tools, Memory, Reasoning, Planning, Multi-Agent Workflows

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Bol AI is moving beyond systems that simply generate text. The next generation of intelligent applications can interpret goals, reason about tasks, use tools, maintain context, make decisions, and execute multi-step workflows.But building reliable AI agents requires more than connecting an LLM to a prompt. Building Agentic and Autonomous AI Agents provides a practical engineering guide to designing, developing, evaluating, securing, and deploying modern agentic AI systems. It takes you from the foundations of AI agents to autonomous workflows, tool use, memory, reasoning, planning, orchestration, and multi-agent architectures.You will learn how to: - Understand the architecture and core principles behind agentic AI- Design LLM-powered agents that can reason and make decisions- Build agents that use tools, APIs, databases, files, and external services- Implement short-term, long-term, and persistent agent memory- Design task decomposition, planning, reflection, and adaptive reasoning loops- Build sequential, conditional, iterative, event-driven, and human-in-the-loop workflows- Move from predefined workflows toward controlled autonomous execution- Design multi-agent systems with specialized roles, delegation, coordination, and supervision- Connect retrieval-augmented generation to AI agents- Test agent decisions, tool usage, reliability, and task completion- Protect agents against prompt injection, unauthorized actions, and unsafe tool use- Monitor, evaluate, optimize, deploy, and scale production-ready agentic applications- Understand advanced architectures such as ReAct-style, planning-based, reflection-based, memory-augmented, and multi-agent systemsRather than treating AI agents as mysterious autonomous systems, this book approaches them as engineered software systems with models, state, tools, memory, control loops, policies, and measurable outcomes.Whether you are a developer exploring LLM agents, an AI engineer building production systems, or a technical professional seeking to understand autonomous AI architectures, this book provides a structured path from LLM applications to intelligent, tool-using, reasoning, and autonomous systems.This is Book 1 of The Agentic AI and GraphRAG Engineering Series.It establishes the foundations you will need before moving into the knowledge-aware architectures explored in Book 2, Building Intelligent AI with GraphRAG.

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AI is moving beyond systems that simply generate text. The next generation of intelligent applications can interpret goals, reason about tasks, use tools, maintain context, make decisions, and execute multi-step workflows.But building reliable AI agents requires more than connecting an LLM to a prompt. Building Agentic and Autonomous AI Agents provides a practical engineering guide to designing, developing, evaluating, securing, and deploying modern agentic AI systems. It takes you from the foundations of AI agents to autonomous workflows, tool use, memory, reasoning, planning, orchestration, and multi-agent architectures.You will learn how to: - Understand the architecture and core principles behind agentic AI- Design LLM-powered agents that can reason and make decisions- Build agents that use tools, APIs, databases, files, and external services- Implement short-term, long-term, and persistent agent memory- Design task decomposition, planning, reflection, and adaptive reasoning loops- Build sequential, conditional, iterative, event-driven, and human-in-the-loop workflows- Move from predefined workflows toward controlled autonomous execution- Design multi-agent systems with specialized roles, delegation, coordination, and supervision- Connect retrieval-augmented generation to AI agents- Test agent decisions, tool usage, reliability, and task completion- Protect agents against prompt injection, unauthorized actions, and unsafe tool use- Monitor, evaluate, optimize, deploy, and scale production-ready agentic applications- Understand advanced architectures such as ReAct-style, planning-based, reflection-based, memory-augmented, and multi-agent systemsRather than treating AI agents as mysterious autonomous systems, this book approaches them as engineered software systems with models, state, tools, memory, control loops, policies, and measurable outcomes.Whether you are a developer exploring LLM agents, an AI engineer building production systems, or a technical professional seeking to understand autonomous AI architectures, this book provides a structured path from LLM applications to intelligent, tool-using, reasoning, and autonomous systems.This is Book 1 of The Agentic AI and GraphRAG Engineering Series.It establishes the foundations you will need before moving into the knowledge-aware architectures explored in Book 2, Building Intelligent AI with GraphRAG.


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Merk Independently Published
EAN
  • 9798192280355
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