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Pierre Pureur, Kurt Bittner, and Todd Miller present five practical ways to use AI coding agents to document legacy services, identify architectural flaws, conduct security audits, build application foundations, and test scalable architectures. The article emphasizes that the speed of code generation does not replace defining architectural quality requirements and reviewing results manually.
Mallika Rao explains that the success of adaptive recommendation systems depends on designing the entire system, not on model accuracy alone. Priorities include real-time feedback loops, retrieval freshness, stage coordination, and controlling latency, cost, and observability.