I personally sold at least $50M of SAP HANA contracted value between 2012 and 2015. The pitch was simple: workloads that took hours could now run in minutes with this new database. Sometimes 100x faster because of beautiful columnar storage rather than row-based. But the business process rarely became 10x faster. The bottleneck moved. I first learned this idea in chemistry through the limiting reactant. A chemical reaction is constrained by the ingredient that runs out first. Adding more of everything else does not increase output. I was speaking to a startup founder recently where the same question came up with AI coding. Their engineers were getting dramatically faster. If engineering becomes 3x faster, engineering may simply stop being the constraint. Now the bottleneck could be product judgment. QA. Distribution. Customer validation. That is why I would be careful with AI metrics such as percentage of code written by AI or hours saved. As a CEO, I would rather track: How fast does an idea reach a customer? or How many experiments can we run? or How quickly do we learn? AI can make a function much faster without making the company much faster. SAP HANA taught me that more than a decade ago. AI is teaching companies the same lesson again.