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A notebook is a named list of SQL cells stored in Nightshift. It’s the natural home for analysis you want to keep: the agent writes the queries, runs them, and the results are snapshotted so you (or anyone on your team) can review the work later without re-running anything. Notebooks are the middle ground between a one-off query and a full App:

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Creating a notebook

Just ask. A prompt like:
“Explore last month’s orders and save your working queries as a notebook called Monthly Revenue”
will have Claude create the notebook and fill it with SQL cells as it works. A few things worth knowing about how this behaves:
  • Cells don’t run on creation. Adding a cell just saves the SQL. A cell only executes when it’s explicitly run — so a notebook can be drafted end-to-end before anything touches your data.
  • Running a cell snapshots the result. When a cell runs, its result (columns, rows, row count, and when it ran) is saved onto the cell. That snapshot is what renders in chat and in the console.
  • Stale results are flagged. If a cell’s SQL is edited after its last run, the saved result is marked as “query edited since, run to refresh” — you’ll never mistake an old answer for a current one.

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Running notebooks from chat

When Claude shows you a notebook in chat, it’s not a screenshot — it’s live. Each cell has a Run button, and there’s a Run all for the whole notebook. Clicking Run executes that cell’s SQL through your Nightshift identity, so the same policies that govern the agent govern the button: if you can’t read a table, neither can the cell. This makes notebooks a nice handoff artifact. The agent does the analysis, you press Run a week later to refresh the numbers.

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Notebooks in the console

Every notebook is visible in the console, with its cells, saved results, and run timestamps. Since results are snapshots, the console shows you exactly what the agent saw when it ran the query — which makes notebooks a lightweight audit trail for how a conclusion was reached.

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Tips

  • One question per cell. Cells are the unit of re-running and reviewing. A notebook of focused cells is easier to audit than one giant query.
  • Promote reusable transforms to views. If several cells share the same cleanup SQL, ask Claude to create a view and query that instead. Notebooks are for analysis, views are for shared shape.
  • Name notebooks for the question they answer. “Churn by signup cohort” beats “analysis-2”. Future-you is the audience.