A random mix from the whole library. Shuffle for a new set.
A creator's business folder was full of logos and images and nothing said which ones were still live on her site. Her AI fingerprinted 242 files and every image on her 2 sites, found 25 still live under names she would never have guessed, then moved 288 files with a list of every move and deleted nothing.
On his boss’s suggestion he tried AI to compare two documents. It failed badly, and about 15 minutes later he was back at square one.
Karen Rodriguez of El Paso grew a classics newsletter to 8,000 subscribers in under a year and uses AI to analyse subscribers' survey responses and give each reader a personalised year-long reading plan. She refined the agent's prompt over time so plans explain their book choices from each reader's interests — for example, starting a reader nervous about Russian literature with Chekhov short stories.
Set the AI the task of running Parseable locally against another of his apps; it worked around a protobuf limitation by running a proxy, he switched his stack to JSON and got it running.
Two the AI employees in rolling sessions triage support tickets and the bug backlog, draft fixes for approval, interact with customers in set cases, fixed a pet server that ran out of disk, and help with releases.
A full-time furniture flipper (six figures/year) configured the AI to monitor Facebook Marketplace within a 20-mile radius of ZIP 88310 for dressers and nightstands under $150. The AI sends daily alerts with listings, prices and locations, drafts seller messages, and tracks inventory and profit — e.g.
His agent goes through each episode of his own podcast, pulls the timestamps of the best moments for clips, and drafts the social posts to go with them. Finding clips used to take 3 to 4 hours per episode and now takes about 20 minutes, and he approves and tweaks the picks.
He let the AI run on its own for 40 minutes on a billing refactor. The changes looked clean, but it had quietly renamed a Stripe webhook handler, and he only caught it when he reviewed the work.
Had the AI build an open-source source control system, benchmarked on a 100k-file monorepo as 12x faster sparse checkout and 82x higher concurrent land throughput than git.
The AI and the AI ran an entire short-video pipeline from script and narration to images, animation, edit, QA and upload, with the author only reviewing.
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.