From Google Workspace to dbt™ Code: AI Workflows with DinoAI
Your specs live in Google Docs. Your mappings live in Sheets. Your dbt™ project knows none of it. DinoAI's new Google Workspace integrations fix that — read a spec, enforce a data contract, turn a Sheet into a tested seed, and ship a PR, all from a single prompt.
Fabio Di Leta
Feb 26, 2026
·
5
min read
Your dbt™ project's biggest problem isn't the SQL — it's the context that never makes it in. The spec doc in Drive. The "official" definitions in a Sheet. The data contract nobody remembers to enforce. DinoAI's new Google Workspace integrations pull that context directly into your development workflow, so you can stop translating and start shipping.
Three new tools: Google Docs, Google Drive Search, and Google Sheets. They're most useful when chained together with DinoAI's action tools (Terminal, File System, GitHub PR) inside a single Agent Mode workflow.
Workflow 1: Spec Doc → dbt™ Models and Tests
A product manager drops a Google Doc with requirements. Instead of reading it in one tab and building in another, point DinoAI at it directly.
DinoAI extracts the business logic, scaffolds the assets, and validates them. If dbt compile surfaces ref errors, it fixes them before returning results to you.
Workflow 2: Data Contract → Enforced Source Definitions
Contracts live in Drive. Models get built without them. DinoAI can close that loop.
The modification date filter ensures you're working from the current version, not a stale copy. The embedded URL in meta makes the source definition traceable back to the document that mandated it. When the contract updates, re-run the same prompt.
Workflow 3: Google Sheet → dbt™ Seed
Reference data living in Sheets — territory mappings, cost center codes, fiscal calendars — should be in your dbt™ project as tested, documented seeds. Now it can be, in one prompt.
DinoAI infers types, maps distinct values to accepted_values tests automatically, writes the seed, and runs a full validation cycle. For multi-tab workbooks, specify the sheet name or GID — it removes ambiguity.
Workflow 4: Drive Content → dbt™ Documentation
Most undocumented models aren't undocumented because the knowledge doesn't exist — it's because nobody has time to find it and write YAML. DinoAI can do that automatically.
The "match the language" instruction matters — it keeps descriptions grounded in your team's actual definitions rather than generic boilerplate. This scales: point DinoAI at a Drive folder and a models directory and let it run.
Workflow 5: Spec → Pull Request
The full loop — from Google Doc to committed, PR-ready code.
DinoAI chains Docs → File System → Terminal → GitHub PR in one workflow. The PR description includes a spec summary and a direct link to the source document — code and requirements stay connected.
Workflow 6: Multi-Sheet Dimensional Modeling
When business definitions are spread across multiple spreadsheets, DinoAI can read them all and reason across them.
Multi-source reconciliation that normally takes an afternoon happens in a single prompt.
A Few Things Worth Knowing
Filter Drive searches by date. Always include a modification date in Drive Search prompts when looking for contracts or specs. Stale docs produce wrong output.
Anchor to source URLs. Ask DinoAI to embed doc URLs in meta blocks and PR descriptions. Traceability from dbt™ asset back to source document is the point.
Let DinoAI handle the debug loop. When a workflow includes dbt build or dbt test, DinoAI reads error output and iterates. Don't interrupt it at the first failure.
Keep sheets clean. Headers in row 1, consistent column types. The Sheets Tool performs significantly better with well-structured data.
All three tools require a connected Google account in Paradime. Setup: Google Docs · Google Drive · Google Sheets
Full tool docs: Google Docs Tool · Google Drive Search Tool · Google Sheets Tool
