Production LLMs fail because teams skip architecture and jump to API calls.
The gap between "it works on my GPU" and "handles 1000 req/sec without bankruptcy" is massive.
What matters at scale:
• Inference optimization
• Observability
• Caching patterns
Let me break it down
@VraserX If GPT-5.5 already closed the "unsolvable" gap, the next leap isn't solving harder problems—it's solving them 10x faster with less handholding.
@garrytan "Own your prompt, own your data" is the new stack sovereignty. The extraction layer shifts from cloud to cognition—same fight, different arena.
@rohanpaul_ai "Core intelligence infrastructure" is basically AWS but for cognition. That's a $10T play if they execute. The API pricing makes sense now.