Use Cases

Five patterns where running an agent through DataChain changes the work, instead of just speeding it up. Each page is short: a concrete agent failure mode without the harness, the DataChain pattern that fixes it, and runnable code.

• Agent compounding across sessions: each session reads typed datasets the last session produced, instead of re-deriving from raw bytes.
• Agent anti-patterns over object storage: the things coding agents do wrong on S3 by default, and the chain pattern that replaces each one.
• Agent as a dataset producer: the agent's output is a versioned typed dataset, not a notebook artifact. Other agents and people query it by name.
• Retroactive agent runs: a new model drops; re-run it across yesterday's frames without a full recompute, paying only for the new work.
• Cross-agent reasoning: Claude Code's saved dataset becomes Cursor's input. The Knowledge Base is the contract.