Oh I see, that looks like marketing BS indeed. Not cool that he agreed with this job title. But to be fair, these days you also see a lot of 'data scientists' w

Oh I see, that looks like marketing BS indeed. Not cool that he agreed with this job title. But to be fair, these days you also see a lot of 'data scientists' whose 'scientific' work consists in putting some statistics together and plot them with Python. Anyway what I was saying was based on reading his books, which again I think have real-world value for some areas of software development. As I said in another comment to me his work consists in collecting and documenting existing practices. I don't think he pretends to teach magic recipes. Each technique is usually presented with potential drawbacks and context where it might apply. That's why I was telling you to use your judgement because these techniques are not supposed to be one-size-fit-all silver bullets. The point is more to identify and describe recurring patterns so that we can communicate more clearly, hence my light-hearted joke about how it helps writing your commit messages. I agree that it would be great to have strong scientific studies showing that such practice works better than such other practice and I bet Fowler would agree too. In fact I watched a talk recently where he advertised a book called "Accelerate" (not by himself) where apparently the authors attempted to evaluate the impact of practices associated with DevOps based on statistical data. The thing is it's much easier to demonstrate or measure the performance of an algorithm than the impact of a code change on the whole life-cycle of a software project. So we resort to experience and intuition not because we don't value the scientific method, but because the scientific method is too difficult to apply in this context.