Deploying a prototype is easy. Deploying a system that handles 100,000 requests per minute with consistent sub-second latency is where the real engineering happens.
The Bottlenecks
Enterprise AI scaling faces three primary bottlenecks: Rate limits, Token costs, and Semantic drift.
Optimization Strategies
- Prompt Caching: Reducing costs by 40% through intelligent caching of systemic instructions.
- Dynamic Routing: Automatically switching between models based on task complexity.
- Vector Database Sharding: Ensuring retrieval-augmented generation (RAG) remains fast as datasets grow to the petabyte scale.