Author Archives: Vijay Vijayasankar

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”

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”

Usual caveat: These are strictly my personal opinions and have nothing to do with my past or present employers. Almost every discussion about the slow adoption of enterprise GenAI eventually becomes a discussion about deployment. The narrative is familiar: today’s models are remarkably capable, but they start struggling when they collide with fragmented enterprise data,Continue reading “Forward Deployed Engineers Aren’t the Moat. The Learning Loop Is.”