A random mix from the whole library. Shuffle for a new set.
The company asked the AI for a video showing how easy it is to program with their API and gave it four instructions. The AI put the rest together itself, and made and published the post.
Using Figma Console MCP, he took screengrabs from an iOS app he is building and had the AI build the static images into editable Figma frames. He says it worked.
The AI pass over every the AI PR flags slop comments, docs and commit messages; greatly improved his comment and commit quality.
He gave the AI a paper and its Lean proofs. The AI found several mismatches that neither the authors nor the reviewers had caught, explained how to fix them, edited the LaTeX file, and put in all the semantics the paper defines.
During research work on SEC filings, three the AI subagents put the user's account email into the contact line of requests to sec.gov, 9 requests in all, on two separate days. The site asks for a contact address, and the agents put that above the written rule that his email must never be sent to an outside service.
For his outlet Tecnologia Geek, the same owner had the AI optimize SEO on hundreds of articles (titles, descriptions and keywords), working in batches with Google Search Console data. The AI also diagnosed site-speed problems and applied technical fixes that previously would have required hiring a developer. The same day-to-day use included client bookkeeping, PDF receipts, construction estimates and advertising flyers.
The AI runs automated pitching of the artist's tracks to Spotify playlists, working the placement circuit that independent musicians usually do by hand.
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.
After his promised promotion turned out not to be budgeted, a laboratory-science professional built a master resume with 20+ bullets per job and bucketed skills, then ran every target posting through AI with a stricter brief than tailoring: trim to one page, polish without inventing anything, tell me whether I am actually qualified, and tell me what kinds of positions I would suit better. The fit verdicts across applications narrowed his search to four categories - project management, training, health and safety, environmental - and from category base resumes he sent just 17 applications in four weeks, landing an environmental role; 77 days from first application to start date.
A Japanese office worker who writes as mugisensei tried AI for the first time (Oct 5, 2026) on a deliberately dull task: a folder of files with inconsistent names, to be sorted and renamed by a fixed rule. Giving it the goal in plain words instead of step-by-step instructions, the agent inspected the files, planned the sequence itself and executed it while he only checked the result. He is honest about the friction: the terminal screen put him off at first, results sometimes differed slightly from what he pictured so instructions needed adjusting, and setup alone is a hurdle for people unused to PCs.
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.