There is a pricing shift happening underneath the AI capability headlines that most enterprise teams are not tracking closely enough, and Perplexity's numbers from March 2026 just made it impossible to ignore. Annualised recurring revenue jumping from $305 million to $450 million in a single month. A 50% revenue increase in 30 days. More than 100 million monthly active users. And a business model that has quietly pivoted from being an AI-powered search engine to being a platform for building businesses, with a $1 million competition to prove it. The Perplexity story is being covered as a growth story. It is actually a pricing architecture story. And the implications for how enterprises budget, procure, and govern AI spend over the next 24 months are more significant than the headline numbers suggest. We need to spend time on both sides of this. The capability and growth story is interesting. The business model transformation underneath it is the part that will land on enterpris...

Seven models. Simultaneously. On a single supercomputer cluster. One of them with 10 trillion parameters, a scale that would make it among the largest AI systems ever trained. When Elon Musk revealed that xAI is running all of this in parallel on Colossus 2, the coverage focused almost entirely on the raw numbers. The parameter counts. The infrastructure scale. The competitive positioning against OpenAI and Anthropic. That is the wrong frame for understanding what this moment actually signals, and what it means for every enterprise team currently making AI platform decisions. The number that matters most is not 10 trillion. It is seven. Seven simultaneous training runs does not say "we have found the answer and we are scaling it." It says "we do not yet know which architectural approach will work and we are running multiple bets in parallel to find out faster." That is a fundamentally different signal from what most AI infrastructure announcements communicate, and...