In the rapidly advancing field of agentic AI, selecting the right resources is crucial for developers. This list of five essential books provides in-depth insights for creating effective production systems.
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AI Engineering by Chip Huyen – Offers practical guidance on LLM applications, focusing on robust evaluation frameworks and engineering tradeoffs.
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LLM Engineer’s Handbook by Paul Iusztin and Maxime Labonne – A comprehensive guide for LLMOps, emphasizing modular workflows and observability for reliable systems under load.
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Hands-On Large Language Models by Jay Alammar and Maarten Grootendorst – Visual explanations help build foundational knowledge, critical for designing reasoning agents.
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Building LLM-Powered Applications by Valentina Alto – Provides hands-on advice on agent memory and tool integration, ideal for teams prototyping agentic features.
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Prompt Engineering for Generative AI by James Phoenix and Mike Taylor – Delves into chain-of-thought reasoning and systematic prompt debugging, enhancing agent performance.
These resources are indispensable for engineers aiming to deploy robust AI systems.
