I moved this one up the pile until it became the book I’m actually reading. The premise alone rearranges how I think about building: most innovations fail not in the lab but at the checkout, because the team designs the product first and thinks about price last. Ramanujam and Tacke argue you should do it the other way round — design the product around the price, and around what people are actually willing to pay for it.

It comes out of Simon-Kucher, a firm that has run more than ten thousand pricing projects, so the advice isn’t theory. The book distils it into a nine-step approach and a set of blunt lessons: talk about willingness to pay early, before you’ve built anything; segment by value, not by demographics; understand that how you charge can matter more than how much. The failure taxonomy is the part that stings — the feature shocks, the minivations, the hidden gems nobody priced properly — because most of us have shipped at least one of them.

The reason it’s here, on the AI shelf of my reading in spirit if not in category, is that I spend my days building AI products and pricing is the part everyone gets to last and gets wrong. It’s easy to ship something clever and have no idea what it’s worth to the person using it. The whole field is discovering that the hard question isn’t “can the model do this” — it’s “will anyone pay for it, and how.” This book treats that question as the starting point rather than an afterthought.

I’m reading the Italian edition, and testing the willingness-to-pay conversations on something real while I go. I’ll rewrite this once I’ve finished and know which parts survived contact with an actual roadmap.