A Make.com pipeline takes a keyword, generates AI content, sends it for email approval, and logs it to Google Sheets.
A Make.com pipeline takes a keyword, generates AI content, sends it for email approval, and logs it to Google Sheets.
The setup was a no-code Make.com workflow using OpenAI, Gmail, and Google Sheets. A person entered one keyword, ChatGPT generated both the Instagram caption and image, Make.com emailed that content to a reviewer, and the reviewer chose approve or reject before the content, image, and decision were logged to Sheets.
The poster says it worked well and highlights the human approval step as the main safeguard against off-brand auto-posting. No performance metrics, posting volume, or time-saved numbers were given.
The main catch is that it stops for manual approval by email, so a person still has to review every post before it is logged.
Build a scenario that takes a keyword from [Google Sheet or form] and uses AI to write an Instagram caption and image idea for [my brand and tone]. Email the draft to [my email] for approval, and log each keyword, draft and approval status in Google Sheets. Don't publish anything to Instagram until I approve, and show me the first draft to review.
Reviewers use Make workflows with Gemini to generate ideas, create and title a daily YouTube video, and route Google Form responses into a CRM with follow-ups.
An agent runs overnight, collects the author's AI newsletter subscriptions and produces a daily podcast to listen to on walks.
An hour before each discovery call, get a one-page brief on the account, the attendee and recent news, saved to Salesforce.