The neural API ecosystem
Different interfaces.
Connected possibilities.
Six focused tracks for understanding where models meet applications. Choose by the task you are trying to solve—not by the label that sounds most advanced.
Choose your learning track.
Language models
Explore text generation, structured outputs, embeddings, and the contracts that connect models to applications.
Agentic systems
Understand tool calling, task planning, and permission checks without confusing a model proposal with authority.
Chat agents
Design chat experiences with purposeful memory, evidence-based retrieval, and a clear path back to a human.
Robotics
Study the boundary between model-generated plans and physical control, starting with supervised simulation.
Brain & biosignals
Explore brain-signal data interfaces through channel metadata, timing, research consent, and reproducible processing.
Trading research
Explore AI-assisted market research with point-in-time data, reproducible experiments, and no live order execution.
Prompts connect every track.
Clear tasks, evidence boundaries, and testable templates belong in every model workflow.
Choose the consequence before the capability.
A text answer, a record update, a physical task, a biosignal interpretation, and a research conclusion need different checks. Start with the consequence of a mistake. Define the input, the output, who may act, and what a safe stop looks like. Then follow the guide that matches that boundary. Our examples are educational reference patterns, not a single interchangeable endpoint for every field.
Plan your first integration