Create LLM-powered autonomous agents and intelligent assistants that can adapt to your specific business and personal needs.
Each job you take on or decision you make requires some of your precious time. AI Agents in Action teaches you to develop and deliver LLM-based assistants and agents that can independently process information, make decisions, and learn from interactions. These powerful autonomous AI agents and interactive assistants handle routine tasks behind the scenes so you can focus on other things.
In AI Agents in Action, author Micheal Lanham combines cutting-edge academic research with practical experience to help you:
From script-free customer service chatbots to fully independent agents operating out of sight, AI-powered assistants are a groundbreaking advance in machine intelligence. In AI Agents in Action you'll learn a reliable, tested framework for developing working agents for a variety of practical business and personal tasks.
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Micheal Lanham is a proven software and tech innovator with over 20 years of experience. He has developed a broad range of software applications in areas such as games, graphics, web, desktop, engineering, artificial intelligence, GIS, and machine learning applications for a variety of industries. At the turn of the millennium, Micheal began working with neural networks and evolutionary algorithms in game development.
From the back cover:
AI Agents in Action teaches developers how to create and deploy agents and assistants built on large language models such as OpenAI's GPT-4, Anthropic Claude, and Groq Labs Mixtral. You'll learn to use prompt engineering to create agents with their own personas and profiles, set up multi-agent collaborations that can succeed in unpredictable environments, and build the kind of AI you can trust to handle high-stakes negotiations.
Along the way, you'll discover a toolbox of AI development tools, including the OpenAI Assistants API, GPT Nexus, LangChain, Prompt Flow, AutoGen, and CrewAI. You'll appreciate the numerous Python-based examples and patterns of how AI agents can be used in a business environment to drive innovation and reduce human labor.
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