The Foundation for Transparent Tracking in MtO Projects W. Edwards Deming once stated: “In God we trust. All others must bring data.” In most distressed projects I have worked with, the problem is not that Read…
In a distressed MtO project, the feature burndown shows whether the team is closing scope gaps. But there is a second dimension that the burndown does not capture: product quality. Features can be declared “done” while carrying unresolved defects that compound across releases and eventually lead to ugly customer escalations—or worse: field failures. That can result in shipping broken products—not because the team hasn’t worked hard on developing new features, but because product quality hasn’t been managed early on. Read…
Made-to-Order (MtO) projects are fundamentally different from R&D. A customer defines the requirements. The scope is contractually fixed. The lifecycle follows a V-model (at least in regulatory-relevant projects) with formal verification at every level of Read…
Last week, Anthropic CEO Dario Amodei said we might be “6–12 months away from models doing all of what software engineers do end-to-end.” Read…
Last year, as music is my hobby, I spent an evening creating professional-sounding songs with Suno. They sounded great, and I felt really good about myself—until I realized that tens of thousands of people are Read…
Large Language Models (LLMs) such as ChatGPT 5 and Grok 4 are becoming more capable and versatile. The real question is whether they can be used for serious work in automotive parts development. LLMs can Read…
Last weekend, Sam Altman did something that should make every AI hype merchant pause. He hired Peter Steinberger. Not the company. Not the tech. The guy. The one-man band who, in a few weeks in Read…
Could Volkswagen face a decline similar to the “Detroit Big Three”?
Could VW become another GM, a company that filed for bankruptcy in 2009?
It appears highly unlikely, but in theory, it’s possible. Read…
As AI reshapes the way expert teams collaborate, the days of large, layered management structures may be coming to an end. With AI as a powerful multiplier, small, specialized teams are the future of innovation. Read…
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