Javelin is an agent-first machine learning framework developed by Ponder for building AI systems. Unlike traditional model-centric libraries, Javelin treats agents, not neural networks, as the primary abstraction. It includes a high-performance tensor engine with dynamic computation graphs, enabling full flexibility for research and production.