The core of successful AI products lies not in the underlying model, but in the surrounding 'harness' engineered by developers. This harness encompasses prompt scaffolding, tool integration, context management, retrieval systems, error handling, and evaluation loops. While models provide raw capability, the harness transforms this into a usable product that can withstand real-world user interaction and deliver consistent value. AI
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IMPACT Highlights that the engineering effort around AI models, rather than the models themselves, is key to shipping successful products.
RANK_REASON This is an opinion piece discussing the engineering approach to building AI products.
