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
The default answer to “make the agent better” is a better model. But a growing pile of evidence says that
Two years into the coding-agent era, a plain Markdown file has quietly become standard infrastructure. AGENTS.md is the place where
Continue readingAGENTS.md: Teaching Coding Agents to Work in Your Repository
Three model releases in ten days have made one thing clear: the frontier story of late 2026 is not bigger
Reinforcement Learning with Verifiable Rewards (RLVR) has become the engine behind modern reasoning models. The recipe is straightforward: let 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
AI agents have gotten remarkably good at reasoning, perceiving, and acting. But ask one to remember what you told it
Continue readingMetis: The First Memory Foundation Model That Learns to Remember
Every Sunday, I scan the open source landscape for projects that are gaining real traction — not just stars, but
Continue reading5 Trending GitHub Repos: Multiplayer Agents, 2 GB LLMs, and AI Writing Discipline
The AI landscape moves fast. In the span of a few weeks, we’ve seen several notable model releases that push