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30 Agents Every AI Engineer Must Build

30 Agents Every AI Engineer Must Build

By : Imran Ahmad
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30 Agents Every AI Engineer Must Build

30 Agents Every AI Engineer Must Build

5 (1)
By: Imran Ahmad

Overview of this book

As 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.
Table of Contents (3 chapters)
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Summary

This chapter has established the foundational concepts that underpin modern agent engineering. We've explored how AI agents have evolved from simple reactive systems to sophisticated autonomous entities capable of perception, reasoning, planning, action, and learning. Through our examination of agent architecture, we've seen how modular components work together to create systems that can effectively navigate and respond to complex environments.The agent development lifecycle we presented offers a structured approach to design, implementation, and continuous improvement, while our exploration of agent capabilities has illustrated the cognitive functions that enable goal-directed behavior. We introduced frameworks for classifying agents based on their level of interaction and developmental maturity, providing a roadmap for understanding and advancing agent technology.By examining design patterns, machine teaching approaches, and real-world business applications...

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30 Agents Every AI Engineer Must Build
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