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Book Overview & Buying
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Table Of Contents
30 Agents Every AI Engineer Must Build
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The development of autonomous agents follows a structured, iterative lifecycle that serves as a roadmap—but one that fundamentally diverges from traditional software engineering practices. Unlike procedural systems that rely on static logic and predefined behavior, intelligent agents must operate within dynamic, uncertain environments. They interpret ambiguous inputs, make decisions under uncertainty, invoke external tools, and continuously refine their behavior through feedback. These evolving, goal-directed behaviors require a lifecycle model that is not just iterative, but also deeply adaptive—supporting reasoning, learning, memory, and orchestration. The Agent Development Lifecycle (ADL) was designed to meet this need, providing a flexible framework that mirrors the operational complexity of modern agent-based systems.This section outlines the ADL—a practical framework that spans from early conceptualization to post...
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