Agent Engineering
Build agents you can understand, test, and improve! This practical four-chapter ebook shows you how to choose the right level of autonomy, connect agents to useful tools, break complex processes into manageable parts, and catch weak spots with evaluation and feedback. By the end, you’ll have a solid foundation for creating more reliable agent systems and the technical judgment to take on more advanced agent development.
Download the Agent Engineering ebook for free!
What's inside:
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Combining an LLM, tools, and an agent loop to support autonomous action
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Building tool-based agents with LangGraph, including state management and conditional routing
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Breaking complex agent processes into focused, testable, and reusable units
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Applying benchmarks, rubrics, critic agents, grounding agents, and guardrails to evaluate behavior
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Using tracing, experiments, session tracking, and feedback to identify weaknesses and improve agents
Get all 4 ebooks for $99.99 here!
Build an AI Agent (From Scratch)
Build an AI Agent (From Scratch) is a fascinating step-by-step journey through design, development, and deployment of a system of autonomous AI agents. Authors Jungjun Hur and Younghee Song guide you concept by concept as you build a sophisticated research agent in Python, designed to solve complex, multi-step tasks from the rigorous GAIA (General AI Assistants) benchmark. By seeing the construction of the system end to end, you’ll understand how the underlying mechanics are unobstructed by any existing blackbox libraries and frameworks.
AI Agents and Applications
AI Agents and Applications is your hands-on guide to creating real, production-ready language model solutions. With LangChain and LangGraph, you’ll orchestrate powerful agentic workflows and build dynamic tool-based agents that can search, summarize, reason, and act. You’ll move from essential prompt engineering to advanced Retrieval Augmented Generation (RAG), and finally to deploying multi-agent systems using modern integration standards like the Model Context Protocol (MCP).
Agent Design Patterns
AI agents are showing up everywhere—and most of them are being built by trial and error. Agent Design Patterns distills the experience of a growing community of agent builders into 20+ composable, reusable patterns for building AI agents that are reliable, efficient, controllable, and easy to reason about. In this uniquely valuable book, author and NVIDIA Research scientist Peter Belcak gives you a durable engineering vocabulary and design intuition that outlasts any new model release.
AI Agents in Action, Second Edition
AI Agents in Action, Second Edition is a substantial revision and update of the first edition. It is a practical and comprehensive guide to building AI agents—not just understanding what they are, but designing, implementing, evaluating, and deploying them. Its strength is in the way it combines conceptual clarity with working code examples, so readers build progressively rather than absorb isolated ideas. The examples form a continuous learning path, moving from a minimal agent to more capable, tool-using, multi-agent, and deployable systems. Each step adds a new skill while reinforcing what came before.
