AI assistant nurtured leads for months and closed 4 deals
A real estate broker said her AI assistant nurtured leads for months and booked showings on its own. She closed 4 deals with buyers she never spoke to until the showing.
A random mix from the whole library. Shuffle for a new set.
A real estate broker said her AI assistant nurtured leads for months and booked showings on its own. She closed 4 deals with buyers she never spoke to until the showing.
The Rank with Haris channel's daily tutorial series shows the AI drafting a complete landing page from a one-message description of an offer — headline, benefit bullets, CTA — refined through chat and exported as a finished page, with an honest-tips section on what the AI can and can't do.
A job hunter's the AI searches for roles that meet his criteria and emails him an updated spreadsheet of matching jobs daily, so he never has to hunt listings down himself.
Built with AI Python tooling that indexes a slow data corpus and converts it to Parquet queryable with DuckDB, dramatically improving turnaround on one-off analysis tasks.
He had an email with stage times and used AI to tidy it into a Stage, Day, Time, Artist list. The AI then changed the fcpxml file so Final Cut Pro had a new project for each set.
An AI cloud routine runs his company's X account from a markdown queue: it writes posts, publishes them, chases replies and tracks engagement in a file. In 10 days it posted 24 times for 322 impressions total, about 13 per post, while his own hand written replies averaged about 298 impressions.
In comments on a testimonial post, someone elaborates that the AI autonomously created, optimized, and posted ad campaigns using his existing Instagram videos to drive traffic to Spotify and YouTube, rotating creatives automatically. Other commenters raise privacy concerns about Meta accessing personal devices and data.
A Business Insider Japan writer set up six AI bots besides his main one and has run them for about a week. One checks his to-do list and pushes him to reschedule, one picks out mail that needs a reply and drafts it, one pulls expense items from mail into a spreadsheet, and one looks up missed call numbers in his mail and contacts and sums up who called.
Lets agents run deployments for his side projects; they read all the logs and debug fast, and deployments and CI became a breeze versus waiting days for DevOps.
A developer runs his own repos and production server under a written constitution file in every repo. Automated runs check production logs daily and file bug reports. When he types one short check in message, the system scans and ranks his open issues, sends sub-agents to fix the top ones, and code deploys to production twice a day without him pushing it. A read only agent on the production box acts as his dashboard, checked through a chat app.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.