Trading is the next frontier for agents. Today, @Bradley_Miles_ and I are excited to introduce Avalon Labs, a frontier AI research lab advancing Trading Intelligence. We are focused on building the best frontier trading models, harnesses, and execution guardrails that let agents become first-class participants in markets. Just as software engineers today delegate the coding loop to agents, we believe traders will delegate the trading loop to capable agents. This requires agents to have market access, real safety guardrails, and the right harness. With these tools, we see the rise of the Trading Engineer - traders who direct trading agents instead of executing every trade by hand or maintaining piles of custom-written code. Today, trading engineers stitch together a workflow involving Claude, Codex, other agents, notebooks, terminals, and general-purpose tools. While these tools are excellent for coding, they lack the proper market context, data, nuances of real-world trading systems, execution access, and safety architecture that truly autonomous trading demands. Our first model is Avalon-1. Our research focuses on how a trading agent can improve itself, and how we grade it every step of the way towards that improvement. Markets give unusually honest signals of whether a decision was right or wrong by providing an objective ground truth that general-purpose models never have access to. Our work is to close that loop which grades the agent's decisions, feeds the grades back and lets the agent improve its own process of improvement. All of this occurs inside hard limits it cannot rewrite.