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Table Of Contents
30 Agents Every AI Engineer Must Build
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This chapter extended the perceptual architecture of intelligent agents across three domains. For Vision-Language agents, the foundational triad of visual encoder, alignment mechanism, and LLM determines whether an agent genuinely grounds its reasoning in pixel-level evidence or approximates visual understanding through degraded signals; COT prompting amplifies accuracy on complex queries by forcing step-by-step analysis before committing to an answer. For audio agents, the VAD model provides a continuous emotional representation that captures prosodic nuance beyond categorical labels, enabling systems to detect not just speech content but caller urgency and frustration. For Physical World Sensing agents, pattern-based event detection separates rule logic from agent code for hot-reloadable policies, while proportional control with deadbands prevents the short-cycling that degrades both hardware and energy efficiency. Across all three domains, the sense-model-plan-act loop...