console but it’s more of a way for humans to audit the work done by an Agent.
We’ve designed Nightshift to fit into the “auto” workflow as much as possible which is what we describe (rather informally) as:
- Prompt Claude (or any other agent) to research across a bunch of structured or unstructured data
- process data like running aggregations, groups, cleaning operations, etc.
- create stateful catalogs, tables, and views
- integrate these data objects into dashboards or live applications
Apps
Hosted data applications, built by your agent
Notebooks
Saved, re-runnable SQL analysis
Policies
How access works — for people, tokens, and agents
Audits
Every change recorded, every change reversible
Sharing
Give teammates access to apps, notebooks, and data
General Best Practices
Habits that make agent-driven data work go well

