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Last day to exhibit your breakthrough to 10,000+ tech leaders at Disrupt is on Oct 2. Book Exhibit Table Now. Disrupt doors open Oct. 13. Get your pass and bring someone with you at 50% off. REGISTER NOW. There’s an old saw in management: What you measure matters. And, typically, you get more of whatever you’re measuring. Software engineers have debated productivity metrics for decades, starting with lines of code. But as the new generation of AI coding agents delivers more code than ever, what their managers ought to be measuring is less clear. Enormous token budgets — essentially, the amount of AI processing power a developer is authorized to consume — have become a badge of honor among Silicon Valley developers, but that’s a very weird way to think about productivity. Measuring an input to the process makes little sense when you presumably care more about the output. It might make sense if you’re trying to encourage more AI adoption (or selling tokens), but not if you’re trying to become more efficient. Consider the evidence from a new class of companies operating in the “developer productivity insight” space. They’re finding that developers using tools like Claude Code, Cursor,

Apr 18, 2026
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