The factory
The AI Development Pipeline
From requirement to tested, reviewed SQL. In hours, not weeks.
Four stations. A person stands at the last one.
01
Spec
The request comes in and is sharpened into a spec that can only be read one way. Open questions go back to the requester, not into the code.
02
Impact
The pipeline maps what the change touches: which tables, which procedures, which reports downstream. Before the build, not after.
03
Test
Tests first, then the implementation. The AI writes SQL until every test passes. Without a test, the procedure does not exist.
04
Approval
The change reaches your people as a pull request. They read it, question it and decide. Nothing goes to production without their approval.
The route of a change
The AI works on a development server, never on production. What it builds reaches a reviewer as a pull request. Only after review and merge does the change go to production.
- 01dev server
- 02AI builds
- 03pull request
- 04review
- 05production
AI builds · a human signs off
What we do not bend on
Tested, always
Test-driven development is enforced, not recommended. Every procedure has tests that run again on every change.
A person decides
AI proposes. A reviewer approves and merges. There is no setting that turns this off.
Full audit trail
Who requested it, what was generated, who approved it and when it was merged. Recorded for every change.
Any platform
SQL Server, PostgreSQL or another database. The pipeline works with what you have.
Want to see it run on your own backlog?
In a thirty-minute demo we walk one change through, from request to approved pull request. After that you know whether this fits your warehouse.