TLDR Tech / Data
We're Missing Data: The Other Half of AI Transformation
AI in data and engineering orgs is overfocused on tools and underinvested in the operating model needed to absorb them. Technical gains from coding agents, eval infra, and internal assistants are real, but without redesigning management, career ladders, team composition, trust mechanics, and communication norms, productivity typically rises for about 6 months and then plateaus. AI transformation is multiplicative, not additive: fund both the technical stack and the operating stack, or the investment will underdeliver.
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