Should I stick with content repurposing or switch to AI automation, what’s the biggest mistake beginners make when selling their first automation, and how do I set up invoice reminders and track overdue invoices?
The invoice reminder is sent from your own business email—the same one you use for regular communication—so customers recognize your domain (e.g., nickleclick.ai) and assume legitimacy. To pull overdue invoices you can use Stripe, QuickBooks, Zero, or any major invoicing tool to retrieve all invoices sent up to a point (e.g., the last 100) and apply the same logic: filter for unpaid, calculate overdue amounts, and send reminders.
I use Stripe for everything. My guiding principle is always ‘keep it simple, stupid’—I want as few platforms as possible, and the automation I build on those platforms should also be simple. Stripe gives me AI-powered features and API endpoints for every need, so I don’t have to resort to hacky workarounds. It handles recurring billing, late‑payment reminders, and integrates smoothly with the rest of my stack, making it the best all‑in‑one solution for my automation agency.
The automation works by using a Google Sheet as a simple database of invoices you’ve sent. For each invoice you record the date, then calculate how many days have passed. Based on the age you trigger follow‑up emails: after 7 days send follow‑up A, after 14 days send B, and so on (7, 14, 21, 28, 35, 42 days). The sheet can be built in any system you prefer—Google Sheets, a CRM, Stripe, QuickBooks, etc.—as long as you can pull the invoice date and payment status. A second automation watches for incoming payments (e.g., via Stripe) and marks the invoice as paid, so only unpaid invoices continue to receive follow‑ups. The email templates are simple reminder messages that reference the invoice and ask if the client needs anything to expedite payment. This low‑cost setup automates the entire follow‑up process without manual effort.
He describes using a Google Sheet to track invoices, checking the date sent to find overdue ones, pulling data into make.com, calculating days overdue, and routing follow‑up emails based on age; for attachments, add a column with the invoice file ID (or link) and use a Google Drive download module so make.com automatically attaches the file when iterating over overdue invoices; you can host invoices anywhere (Google Drive, etc.) and just store the file ID; the same follow‑up logic works for any pipeline, not just invoices; built‑in platform follow‑ups (Stripe, PandaDoc) are poor because they sound robotic, whereas a friendly, assumptive tone preserves relationships and improves response.
The main problem with automating finance is the risk of costly mistakes. If an automation glitches and adds extra zeros to an invoice or payroll, you can instantly create a huge loss—think turning a $1,000 payroll into $10,000, which dwarfs the modest time savings. The marginal benefits of automation in finance are small, while the potential downsides are massive, especially when the automation interacts with bank accounts. For example, automating payroll for ten staff might save only 40 minutes a month, which translates to about $15 in savings—hardly worth the risk of a $99,000 error. Instead of fully automating, I recommend doing the heavy‑lifting manually, then using a simple queue to batch payments (e.g., calculate amounts, then push transactions through Wise once or twice a month). You can also leverage AI for tasks like parsing financial statements, generating cheap analysis packages, or automating bookkeeping, but keep the core financial actions under human control because the juice is often not worth the squeeze.