Every Sunday night, someone somewhere is refreshing an LLM leaderboard. A new model edges out the old one on a coding benchmark. Another claims a fractional improvement in reasoning. Social media fills with grand declarations that everything has changed again. It usually hasn’t ! We’ve spent the last two years obsessing over who has theContinue reading “The Real AI Race Isn’t for Better Models. It’s for Pricing Power.”
Author Archives: Vijay Vijayasankar
The Loop Trap: Why Cheap Tokens Don’t Mean Cheap Tasks
In almost every enterprise AI conversation right now, someone eventually says the same thing: “Tokens are basically free.” I understand why people say it. If the expensive part of building with AI was inference, then cheaper tokens should unlock everything. But that assumption hides a bigger problem. The real cost of enterprise AI was neverContinue reading “The Loop Trap: Why Cheap Tokens Don’t Mean Cheap Tasks”
The Slowest-Scaling Constraint
One of the easiest mistakes in technology is assuming the most valuable asset is the most visible one. For the past three years, that asset looked like GPUs. Every headline tracked NVIDIA shipments. All funding rounds celebrated larger clusters. Every single discussion about AI infrastructure turned into a count of compute. But visibility is notContinue reading “The Slowest-Scaling Constraint”
And Vijay Says... 