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An engineer on your team now ships in a day what used to take a sprint.
The gap between a good engineering team and a great one isn't really about talent or culture anymore. It's about how fast a team learns to work differently.
Teams pulling ahead right now are building two new disciplines on top of that foundation: treating AI fluency as a continuous core competency and orienting around step-function gains rather than incremental ones.
79% of senior tech leaders say they're pressured to overstate AI progress.
That's what our AI Execution Gap survey found, based on responses from 501 U.S. decision-makers running active AI initiatives at their companies.
Read together, the two findings describe a structural pattern.
83% of respondents plan to increase AI spending over the next 12 months, while the foundations underneath aren't keeping pace.
The friction doesn't go away when the reporting layer flattens it.
Procurement isn't underperforming because it lacks talent or headcount. It's saturated. Buried in low-leverage work that consumes the capacity that should be going to strategy.
That's the reframe our Fellow, Keith McFarlane, CTO at Globality, argues for in his new piece.
Some teams are getting 10x returns from AI coding tools. Most, though, are getting marginal gains or worse. What separates them is the state of the codebase that those tools are operating on.
After 27 years in software engineering, he argues that the investment leaders could never quite justify is now the highest-ROI move an engineering leader can make.