The AI wrote his logic project and the thousands of tests that prove it
The AI produced the code plus thousands of unit tests and validation and fuzzing scripts for his tedious conditional-logic side project; it works and is shipping.
A random mix from the whole library. Shuffle for a new set.
The AI produced the code plus thousands of unit tests and validation and fuzzing scripts for his tedious conditional-logic side project; it works and is shipping.
A developer told the AI to repair his stock-options analysis software working only on copies; when the mirror-rebuild tool failed, the agent wrote its own Python cleanup script that treated 614 Windows directory junctions inside the temp mirror as ordinary folders and deleted 48,218 live files in 103 seconds. The sweep also emptied the Git object store, leaving an index that listed 7,221 paths whose contents were unrecoverable.
A solo founder in Germany moved his whole company into a folder of plain text files four months ago and lets the AI operate it: rules in one file, decisions in their own folder, an inbox that fills when he says keep this. Last week the folder produced a three day expansion of his app covering close to 3,000 points of interest, each with an article in three languages and its own audio; the same job took him four weeks by hand in January. A weekly caretaker run tidies the folder and proposes at most one change, which he approves.
He uploaded a PDF of a credit card statement and asked the AI to spot the subscription charges for each cardholder. The AI linked the charges to the right people, summed them up, and pointed out the same vendors showing up on more than one card.
The AI via Blender MCP made add-on plugins and a Geometry Nodes asset-library workflow distributed on an internal network, useful chairs and tables on first try.
His role was cut on Tuesday morning. By Wednesday breakfast he had built a 16-bit co-op game about the job hunt with AI and put it online for anyone to play.
A business owner set a Dot to watch his Facebook groups for lead posts in his specialization; the Dot opens the groups in its cloud browser but the checks keep getting stuck or missing relevant posts entirely. The AI, connected directly to his Facebook account, did the same monitoring reliably, leaving him stuck mid-migration to Dots.
A shop owner set the AI up to work out how many socks to order so the shop does not run out. It sends the order by email, reacts to replies, creates the order, stocks the goods, and books the invoice when it lands in the inbox.
The user's the AI came up with the idea itself: it built websites and the user made the calls, closing two sales out of roughly 50 outreach attempts to local businesses.
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.
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.