Better Context Will Always Beat a Better Model

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Context quality matters more than model capability for enterprise AI success. Engineering leaders emphasize that feeding AI systems with precise, filtered data beats using larger models with noisy inputs. Key challenges include context poisoning from irrelevant data, governance gaps from AI-generated code, and token waste from

8m read time From thenewstack.io
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Table of contents
The Rise of ‘White Coding’ and the Governance GapThe Fallacy of ‘More is Better’Fighting ‘Context Poisoning’ With StructureContext Caching and ‘The Notebook’Cognition for Humans and AIFiltering as the Competitive Advantage

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