Every request that hits an LLM server pays the same tax before the first generated token appears: the prompt must
Continue readingvLLM Prefix Caching: The Prefill Optimization You’re Already Running
Ask an LLM for JSON and you will usually get JSON. “Usually” is the word that ruins your week. One
Continue readingConstrained Decoding: How Structured LLM Output Actually Works
Large language model inference has an awkward performance profile: the GPU does enormous math, then waits. Every token requires a
Shipping an LLM-powered feature without an evaluation pipeline is like deploying a microservice without health checks — it might work
Continue readingBuilding LLM Evaluation Pipelines: Metrics, Frameworks, and CI Integration
Reinforcement learning has become the defining ingredient of modern LLM post-training. GRPO, PPO, and their variants drive the reasoning capabilities
The vLLM v0.23.0 release landed last week with 408 commits from 200 contributors, and it packs several changes that directly
The first version of any RAG pipeline usually looks the same: embed a query, search a vector store, stuff the
Continue readingBeyond Naive RAG: 4 Advanced Patterns That Actually Work in Production