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Agentic Programming with AI Agents: A Practical Software Engineering Guide to Tool-Calling Agents, Planning Systems, Memory, Evaluation, Security, and Production Deployment - Softcover

McLucas, Cameron

 
9798185848661: Agentic Programming with AI Agents: A Practical Software Engineering Guide to Tool-Calling Agents, Planning Systems, Memory, Evaluation, Security, and Production Deployment

Inhaltsangabe

Agentic Programming with AI Agents: A Practical Software Engineering Guide to Tool-Calling Agents, Planning Systems, Memory, Evaluation, Security, and Production Deployment

AI agents are no longer experimental demos. Developers, engineers, and technical teams now need agents that can call tools, follow plans, manage context, remember useful information, evaluate outputs, handle failures, and run safely in production.

But building reliable AI agents is not as simple as connecting an LLM to an API.

Are your prototypes impressive but fragile? Do your agents break when workflows get longer, tools multiply, or users expect dependable results? The real challenge is moving from clever prompts to engineered agentic systems that are testable, secure, observable, and ready for real software environments.

Solutions

Agentic Programming with AI Agents gives you a practical software engineering guide to building tool-calling agents, planning systems, memory layers, evaluation workflows, security controls, and production deployment patterns.

Inside, you will learn how to design agent architectures, connect tools safely, structure planning logic, manage state and memory, evaluate agent behavior, reduce failure modes, and prepare systems for real-world use.

This book focuses on practical implementation, clear workflows, and engineering discipline rather than hype. It connects AI agent design with the habits serious developers already value: clean architecture, testing, reliability, security, monitoring, and maintainable production code.

Proof

You will gain a clear framework for building production-ready AI agents, including:

  • Tool-calling and workflow orchestration

  • Planning, memory, and context management

  • RAG-ready agent patterns

  • Evaluation and reliability checks

  • Security, guardrails, and deployment practices

Written for software developers, AI engineers, technical founders, and advanced learners, this guide helps you turn agentic AI ideas into structured systems that can support real applications.

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