Large language models (LLMs) now power everything from customer service bots to autonomous coding agents.
Agentic loops in production can be synonymous with high costs, especially when it comes to both LLM and external application usage via APIs, where billing
AI agents have evolved beyond passive chatbots.
Calling a large language model API at scale is expensive and slow.
You’ve probably written a decorator or two in your Python career.
The open-weights model ecosystem shifted recently with the release of the
Language models (LMs), at their core, are text-in and text-out systems.