Tutorials

Each tutorial starts with one prompt and ends with something you can inspect. Your agent handles the MCP calls, local files and CLI commands. Start with the quick-start instructions and select a separate tutorial project. The connection guide explains how to verify access. Select your project when the agent shows the available choices. It carries that context through the conversation.

Lesson	You ask for	You will inspect
Train a decision model	Prepare data, train a model and benchmark it	A trained model, baseline comparison and example mistakes
Fine-tune a language model	Prepare examples, fine-tune and benchmark text responses	Base-model and fine-tuned outputs, scores and example mistakes
Record a trace	Write and run one local tracing example	One trace with a tool call and its result
Run an evaluation	Check recorded fraud labels	Valid answers and a deliberate vocabulary failure

Both model-training tutorials and the evaluation tutorial use the same fraud example dataset. The trace lesson uses a local function and needs no external data. You can take it independently. Both model-training tutorials include training and benchmark inference. The trace example application makes no model calls, but enabled platform scoring may; the label-format evaluation does not train a model, although the platform may generate explanations for low scores. Your coding agent uses its own provider. Each tutorial states the work it starts.

Start here

How-to guides

Reference

Explanation

Tutorials