Introducing Ornith 1.0 - Agentic Coding LLMs

Sam Witteveen explores this new family of self-scaffolding models designed to generate their own task-specific harnesses alongside solutions. By utilizing a two-stage reinforcement learning process, these models aim to optimize both the coding environment and agentic trajectories, offering a versatile approach for handling complex local coding tasks without requiring human-authored scaffolds.