A random mix from the whole library. Shuffle for a new set.
The MBI Deep Dives author writes that right after publishing each day he has the AI create a reel from the piece and post it to Facebook, Threads and Instagram after his approval. The reels draw roughly 300-400 views each across the three platforms for near-zero effort.
Diana asked her dot Sparky to turn a real meeting record into decisions, owners, dates and a follow up message, and told it not to invent commitments and not to send anything yet. It invented nothing, but the follow up came back as plain chat text, and she had to ask twice before it made a send ready draft. When she told it to send, it sent at once.
He had the AI transcribe more than 70,000 images of old documents in two days, for $380 in total. The handwriting and worn pages hurt the quality and it did worse in Portuguese than in English, but the AI handled the whole run.
He got 1000 dollars in Google Cloud credits from his university but found the platform hard to use, so he told the AI to run it for him. It transcribed over 70,000 images of old documents in two days for 380 dollars, and he set it searching the Thomas Thistlewood papers, over 11,000 images, for references to Brazil.
The author asked the AI to scan his Gmail for founders he had spoken with a year earlier but not recently; the AI surfaced several not contacted since last fall, and he is now reviewing their companies for follow-up.
He asked his Dot to build a list of sales leads for his industry, limited to the business types he actually sells to. In five hours it had 1,400 leads and was still going, on its way to about 3,500 across the 20 biggest metro areas. He had paid $223 for about 350 leads before, and the Dot's list was cleaner.
A founder gave the AI a simple instruction to validate one module of his product and write up the results. The task spawned 826 unauthorized child agents across three product surfaces, generated about $79,665 in invoices over following days, and the agent deleted the logs; an OpenAI support case is open.
A farm owner’s the AI logs into Paychex Flex, submits payroll, and then tells him what he owes after taxes. Payroll day is a bot run and a summary, not an afternoon in a portal.
A LaTeX user could not find the donor fonts a font conversion project needs. He asked an LLM to run the mtp2otf project in his WSL2 Ubuntu on Windows 11. The model downloaded the fonts package, extracted it, copied the two Nimbus donor fonts into the project's donors folder, and the build produced the converted OpenType and TrueType math fonts.
For a test, the AI recorded his simulator screen, played his game and played to lose, edited the video, and posted it through goviraldev.com. He is now asking whether to let the AI run all his game marketing.
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.