30 Agents Every AI Engineer Must Build

From the author of 50 Algorithms Every Programmer Should Know. Learn to design and implement 30 intelligent agents that combine core architecture patterns with domain-specific solutions.Key FeaturesGet to grips with foundational agent principles including perception, memory, reasoning, and planningIntegrate advanced frameworks like LangChain and AutoGPT in your AI agent developmentDesign agents using advanced prompting, knowledge retrieval, and multi-agent orchestrationPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAs AI evolves from passive tools into proactive collaborators, intelligent agents lead this transformative shift. This guide equips you with critical knowledge on agent architectures, practical tools, and industry insights to develop robust, autonomous AI systems. You'll start by mastering foundational agent capabilities such as perception, memory, reasoning, planning, and learning. Gain insight into the cognitive loops essential for autonomous systems and build agent architectures using state-of-the-art frameworks like LangChain and LangGraph. Practical industry applications are explored across healthcare, finance, manufacturing, and education—illustrating how agents can optimize workflows, enhance advisory systems, automate quality control, and enable adaptive learning environments. Through numerous real-world examples, this book guides you in creating intelligent agents capable of contextual reasoning, effective tool utilization, real-time responsiveness, and seamless collaboration with humans. Additionally, you'll learn crucial strategies for the deployment, management, and ethical development of responsible AI systems. Whether you're developing your first intelligent agent or enhancing critical business operations, this book provides clear, actionable guidance for creating scalable and ethically robust AI solutions.What you will learnUse LangChain and LangGraph to construct autonomous agents with modular, scalable architecturesEstablish robust evaluation frameworks to measure agent performance, reliability, and alignmentDeploy production-ready agent systems that scale securely in enterprise environmentsImplement ethical guardrails and explainability features to ensure responsible AI deploymentNavigate ethical concerns around explainability, bias, and safe deploymentImplement ethical guardrails and explainability features to ensure responsible AI deploymentWho this book is forThis book is for AI engineers, software developers, ML researchers, and technical leads building intelligent systems. Ideal for those deploying LLM-powered applications or transitioning from traditional ML to agentic frameworks. Python experience and basic ML knowledge are recommended.

Imran Ahmad is the author of the 50 Algorithms every programmer should know. He has been a part of cutting edge research about algorithms and machine learning for many years. He completed his PhD in 2010, in which he proposed a new linear programming based algorithm that can be used to optimally assign resources in a large scale cloud computing environment. In 2017, Imran developed a real time analytics framework named StreamSensing. He has since authored multiple research papers that use StreamSensing to process multimedia data for various machine learning algorithms. Imran is currently working at Advanced Analytics Solution Center A2SC at the Canadian Federal Government as a data scientist. He is using machine learning algorithms for critical use cases. Imran is a visiting professor at Carleton University, Ottawa. He has also been teaching for Google and Learning Tree for the last few years.