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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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Code-Generation agents represent the most mature application of agentic AI in software engineering. These agents go beyond simple autocompletion by implementing TDG, a methodology that transforms the probabilistic output of LLMs into deterministic, verified implementations. This section examines the TDG architecture and its three-phase workflow, demonstrates how multi-agent orchestration enables iterative refinement through structured feedback loops, and progresses from a single-function implementation to a complete full-stack development case study. The patterns established here form the foundation for the Compliance-Driven and Self-Improving agents that follow.
Code-Generation agents face a fundamental challenge: LLMs produce probabilistic outputs that can vary across runs and may not consistently align with design intent. Relying on these outputs without systematic validation is unsuitable for production environments...