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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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This chapter explored two complementary approaches to building agents that teach, learn, and transfer knowledge.
The Education Intelligence agent combined knowledge graph curricula, BKT, and adaptive techniques grounded in cognitive science to create a personalized learning system. The programming tutor case study showed these components in production: a two-stage misconception detector, context-aware feedback, and spaced repetition scheduling delivered a 34% improvement in assessment scores and pushed course completion from 71% to 89%.
The Collective Intelligence agent extended multi-agent collaboration into consensus-driven problem solving. Weighted voting with expertise calibration, adversarial critics for groupthink prevention, and cross-pollination for emergent insight produced synthesized designs that consistently outperformed single-agent outputs. The most valuable results came from synergistic interactions between agents with complementary expertise. In the...