Pitch 10 brands every morning and save my campground booking in a flood
The user's agent Dash pitches 10 brands each morning for his RV-life content business, and when a flood cancelled his campground, it found a new site so the trip survived.
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The user's agent Dash pitches 10 brands each morning for his RV-life content business, and when a flood cancelled his campground, it found a new site so the trip survived.
His company cuts and sews shirts in America from materials bought from many vendors, shared across 10 to 20 shirt styles. Working out the true cost of a finished shirt by hand was a mess. Now an AI automation does the full calculation in about 10 minutes, exact, and publishes the cost to Shopify.
A moving/junk-removal owner says three the AI run his marketing agency work: a Google Business Profile posts bot drafting daily posts in each client's voice, a review-replies bot generating three reply options per new review, and a GoHighLevel bot logging leads, creating call-back tasks and drafting follow-ups. His morning pass runs 6:30, 6:45 and 7:00 AM approving posts, picking replies and sending follow-ups, done by 7:05 with nothing left open; the bots are logged into Gmail, Quo, Stripe, Wix, GoHighLevel and Google Business Profile.
A user had the AI apply TurboQuant skills to optimise a Qwen3.5-9B model running locally via MLX on Apple Silicon. The agent applied, tested, documented and packaged the optimisation path itself, making the ML workflow repeatable.
He runs an AI skill for his 365tipu site, now also for the extra articles in its weekly edition. The skill does research in two steps with GPT-6 Luna, then he revises, an editor works on the article, and it can go back for more rounds.
A LaTeX user's copied table code did not fit his page size at all. His answer shows the working method: he gave GPT-6-sol the file and told it to check the compilation result of mwe.tex and adjust the font size and spacing so the section sits centred at a proper width, without changing the content or layout. The answer posts the adjusted code that came back.
He runs a small server with Postiz. The AI drafts posts from his commits and he approves them once a week.
Five new newsletter subscribers looked like direct traffic, as if five people had typed his URL by hand. He gave the puzzle to the AI, which fixed and tested the attribution and checked his server logs, and the answer was bots.
He released version 0.6.0 of his software, and his agent fleet built most of it. A pre-launch check caught a routing bug where one agent was being sent another agent's model id. Now every routing path runs as a canary before a release.
The AI goes through their shared work inbox, makes a list of every email, and sends three spreadsheets out to the departments with their tasks on them. The poster says it has basically changed their life at work.
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.