From Simulation to Production: How an AI-Native Pipeline Discovered a Better Admission Controller for llm-d
A case study in closing the AI-native loop: observe, reason, change, validate, deploy.
Introduction
An AI-native system is one that continuously and autonomously closes the loop from observation to action to deployment, with AI as the primary agent driving this process. Rather than humans manually directing each improvement, humans establish objectives and boundaries while the system autonomously executes the cycle, at machine speed.