Autonomy at the Speed of the Mission

This post introduces the concept of an 'AI Factory' for autonomy, which is a governed production system that transforms operational data and mission intent into deployable capabilities. It emphasizes a shift from traditional engineering cycles to a model where operators refine autonomy through intent, conversation, and examples without direct code modification. The post details how foundation and multimodal models augment classical autonomy, enabling systems to reason through unforeseen conditions. It highlights the importance of running models on the aircraft for reduced latency and operational resilience, with concise task, state, and semantic updates exchanged over limited bandwidth to support one-to-many supervision. The system retains predefined mission logic and approved contingency behaviors if operator connectivity is lost, and prioritizes high-value data segments from the edge for learning. Assurance is integrated throughout development and release, with evaluation against performance standards, traceable evidence, simulation, integration testing, and runtime oversight. The AI Factory makes repeatable deployment possible by preserving knowledge and evidence, and increasingly uses AI to improve its own workflows.