A random mix from the whole library. Shuffle for a new set.
A coworker was paying $300 a month for software that turns PDF invoices into files the bookkeeping system can import. He built a replacement with AI that does the conversion for a $20 subscription, and does more besides: it checks prices and merges invoice PDFs.
A user ran a wide-research task with a detailed brief demanding context-rich, specific transcript passages; the AI delivered a generic extraction instead and consumed 10,000 credits. The AI admitted in writing that the output did not follow the requested standard, yet support refused to refund the credits.
Commenting on the 26 use cases post, he says he uses AI to find and apply to jobs. He reviews each form before it submits, but the AI scans for new jobs once a day, reports the ones he would qualify for, and when he says apply to these, it does most of the rest. It remembers his preferences, like salary range. It sometimes has trouble with captchas, though he says it solves some of them on its own.
Since July 2026 a Japanese creator has run a political clip channel with a pipeline the AI built: it watches source channels, fetches new videos, transcribes them locally, picks highlights from voice peaks and wording, fixes subtitle typos and names, makes thumbnails and titles, exports long videos and Shorts, uploads them unlisted, then collects view and retention data to feed the next round. In 3.5 months it shipped 319 videos for about 1.05 million total views and 1,080 subscribers, though the median long video reached only 268 views; he publishes the failures too, including the agent claiming 'fixed' when it was not.
He and the AI mapped published datasets and converted them into meshes for Moho depth, basin depth, and two sedimentary basin depths. The work pointed to a tight spot under the South Gate area of LA.
He wanted one place where people can find all the apps he is working on. The AI built the site, beardfm.app, in about 15 minutes.
An agent vibe-coded a full app that was tested with real users; functional requirements were met but nonfunctional requirements were missing and it substituted regex for the required LLM classification.
His bots on the AI hold a daily standup before he has had coffee. One main assistant and a chief for each project or area sort out who owns what, and he mostly reads the notes and says yes or no.
The same clinic director built his own phone switchboard where an AI voice answers patient calls first, transcribes them in real time and writes summaries and to-do lists. When two AI models disagree on how a call should be classified, the call lands on a grading screen where he taps number keys to mark the right answer.
Her business folder was a mess and file names did not show which files were still live on her site. The AI checked each file's fingerprint instead of its name, moved 288 files, and deleted none.
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.