Case

We’re in a medium-sized tech services company. It is a quarterly review meeting. The management team is reviewing the delivery milestones as committed. When they get to the release calendar, the CEO asks why it’s the same. Indeed, a few months earlier, upon a perfect slide deck from the VP of Engineering and the product leaders, the CEO committed to another investment budget for AI. That deck was about AI adoption. The shared benefit highlighted was everyone using it, with an implicit delivery performance improvement as a consequence. There was no more precision, but everyone saw the need to go all in on AI. ...

A consultant cuts a number by 30%, presents the slides, and leaves. Three months later, the number is back where it started. I have watched that version many times, and I have been the consultant in it. I have also been the one whose fix was still running long after I was gone. The difference showed up in how the fix got built. The diagnosis: leadership was reading status, not time The team ran the path to production at a large enterprise. As usual, the process involved other specialized teams such as security, infrastructure, and cloud. One application took more than a year to get through it. Nobody inside the pipeline knew that, and everybody was doing their job. ...

One question has trailed the AI wave into every product conversation this year: why bother with customer discovery when you can build the thing in a weekend? The answer got clearer, and it points somewhere most teams are not looking. AI multiplied every team’s capacity to act. We get more code shipped, and more tickets closed. It added nothing to our capacity to know where to act. Over half of new features still fail to deliver the value teams expected. Mostly because they aim at the wrong problem, faster. ...

The number had just hit zero. For the first time in months, the number of release failures reaching production was zero. Three months of digging had gotten the team there. I could have written up the win that same afternoon and gone home. One month later, it was back up. I have watched this shape play out on enough teams to trust it. A team fixes the real thing, the number falls, everyone breathes out, and then it drifts back. Here is the story of one team that lived exactly that, and the part that finally held. ...