VIEWER RESOURCE — PROMPT SHOWN IN THE LESSON

Reconstructed from the on-screen prompt. Replace the business description with your own. This text is a resource for viewers, not an instruction that has been executed against your accounts. Start in a separate demo project with fictional data, review generated SQL, and confirm the intended project before applying changes.

I own a residential plumbing company in Houston, TX. We do water heater installs and repairs, drain cleaning, repipes, faucet and fixture repair, and sewer line inspections. Customers reach us by phone, text, and a website form. A job goes: first contact, quoted, scheduled, done, invoiced, paid.

Build me a simple database that an AI assistant can read and write to. Give me exactly four tables:
• customers (who they are and how to reach them)
• jobs (what we did, when, which tech, for how much)
• invoices (amount, due date, paid or not)
• ai_action_log (every text, email, or call the AI makes, with the result)

For each table:
(1) Explain the columns in plain English, one line each.
(2) Give the exact SQL to create the table in Neon (Postgres) with sensible rules, like a date column that only accepts dates and a status column limited to scheduled, in_progress, done, or cancelled.
(3) Give me 8 rows of realistic fake Houston customers and matching jobs, invoices, and log entries as INSERT statements, with at least two unpaid invoices.

Then give me three questions I can ask the database this week as SQL:
• Who owes me money and how late are they?
• Who has not been serviced in over a year?
• What did the AI send out this week?

Keep every explanation at a 5th-grade reading level.

BEFORE USING THE RESULT
Check how customers, jobs, invoices and actions are linked. Have the assistant explain which validations it actually implemented. Creating an action-log table does not itself log events: the workflow must write those events. Database creation also does not automatically configure messaging, CRM synchronization or customer follow-ups.