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Are our teams actually getting better?
It’s a simple question, and not enough technology leaders are asking it. Some assume the answer is yes. Others are too buried in day-to-day delivery to step back and check. But every leader should be asking it, and that’s more true today than it was even a few y...
When transformation isn’t producing results, the first instinct is to look at delivery. Teams aren’t shipping fast enough. The backlog is bloated. The release cadence is inconsistent. The organization reaches for the familiar remedies: new frameworks, better ceremonies, more alignment meetings. Sometimes this helps at the margin. Th...
I’ve spent the last 25 years trying to answer one question: how do you actually get a large, complex organization to deliver software predictably? The question hasn’t changed. The technology has changed. The buzzwords have changed. The funding model has changed. But the underlying problem has been the same one the whole time, and right now it’s wearing a new...
In my last article, Why Most App Modernizations Fail, I made the case that organizations know they need to modernize but are lacking a framework that remo...
Most Fortune 100 companies aren’t struggling with AI because they lack the right tools or models. They’re struggling because AI fails at the organizational level: fragmented data, misaligned incentives, no clear ownership of outcomes, and legacy systems that weren’t designed to feed production AI. It’s these issues that stop promising pilots from scaling int...