Build and evaluate trading agents.

Learn how trading agents work, how models and tools work together, and what to check before connecting an agent to an API.

Choose where to start

Understand what an AI trading agent does, what its parts are, and where its limits begin.

Compare model providers and other parts of an AI trading stack before you commit to a design.

Work through API connections, authentication, test environments, and the limits of a public endpoint check.

Plan the model, tools, controls, and testing around an agent before it reaches an execution API.

Examine trading hypotheses, their inputs, and the records needed to test them without treating them as live signals.

See how models, tools, and execution APIs fit into one application, and why they are not interchangeable.

Start with a harmless public API check, then separate connectivity from authentication, permissions, and access.

Compare the documented API, tool, caching, batch, rate-limit, and lifecycle choices behind an agent build.

Compare two trading-system hypotheses, the records each needs, and the failure cases they cannot settle.