Ground the agent before you build
Start sessions with a look around:“What data do I have in Nightshift? Describe the tables I’d need for revenue analysis.”An agent that has listed your objects and read your schemas writes correct SQL on the first try far more often than one working from your description of the data. This costs one prompt and pays for itself immediately.
Build durable shape, not piles of copies
The order of preference for making data useful:- Views first. They’re free, always current, and they turn “the query Claude figured out last Tuesday” into a named object every future conversation can build on.
- Tables when you mean it — materialize when the transform is expensive or you need a stable snapshot to work against.
- Avoid one-off copies.
sales_final_v2_newis how warehouses rot. If an agent session produced clutter, say so — cleanup is one prompt, and rollback has your back.
daily_pageviews, active_customers), not for when
they were made. The names become the vocabulary you and the agent share.
Put work where it lives longest
- A question → just ask; a query in chat is fine.
- A read on the data right now → ask for a dashboard in chat.
- Analysis you’ll rerun or hand off → have Claude save it as a notebook.
- Something the team opens every week → have Claude publish an app.
Let the agent act as you — scope tokens for automation
For interactive work, connecting Claude through the standard flow (acting as you) is the right default: full visibility, full attribution in the audit log, zero setup. Reach for a scoped token when:- something runs unattended (scheduled jobs, CI, a server),
- you’re handing access to a narrower context and want a smaller blast radius,
- an app or integration needs its own standing identity.
Review like it’s cheap — because it is
Don’t pre-approve every step of an agent’s work; review it afterward instead. The platform is built for exactly this:- The Audit log shows every change from the session as snapshots.
- Notebook cells keep the queries and their results.
- Restore undoes anything, without losing history.
Bring data in the front door
External data enters through Add Data (or your connectors) — not through SQL. Queries can’t read files, URLs, or credentials by design, so don’t ask the agent toCOPY from a
bucket; ask it to load the data through a connector instead. Credentials live in Add
Data’s managed configuration, never in SQL text.

