Chunked Prefill: Solving the Noisy Neighbor Problem in Inference
When a massive prompt stalls your entire inference server, you have a noisy neighbor problem. The solution requires rethinking how we process context with Chunked Prefill.
From the Front Lines of Tech
Sharing strategic insights and lessons from over 20 years of building scalable systems, leading high-performing teams, and navigating complex technology shifts.
Agent FinOps: Architecting Economic Constraints into LLM Routing
We built autonomous agents that can think, reason, and execute. Now we need to stop them from bankrupting us. Here is how to build economic constraints directly into your LangGraph loops.
Rack-Scale AI Design: The End of Component Scaling
We have hit the physical limits of what a single chip can do. The new unit of compute for AI infrastructure isn't the GPU; it's the fully integrated rack.
TTFT (Time To First Token): Measuring Inference Correctly
TTFT reveals the real bottleneck in LLM inference. Learn why Time To First Token matters more than average latency, and how to separate prefill vs decode.
· StrategyThe P&L Mandate: Transitioning the CAIO from Pilots to Profitability
Boards demand hard financial ROI over soft metrics like 'hours saved'. This is the framework to shift your AI strategy toward measurable margin and revenue impact.
RadixAttention in SGLang: Prefix Caching Documentation
SGLang's RadixAttention uses radix trees for KV cache optimization. How it outperforms vLLM PagedAttention for multi-turn conversations and agent workflows.