A random mix from the whole library. Shuffle for a new set.
Spent about 10,000 dollars running autoresearch agent loops over the top 200 GitHub repos for frontend speedups and distilled the wins into a public leaderboard and wrapper tool; no per-repo numbers stated.
Diana gave the AI Fable 5.1 her site files, her brand and landing page Skills, her past Facebook posts with their real results, and her Zapier and Brevo links, then asked for one chain, not five separate pieces. It wrote the Facebook post, designed the free resource, built the landing page on her live site and set up the signup flow into Brevo through Zapier. The page is live. She made one fix to the page layout. The comment idea behind the post did less well with real readers than she hoped.
The poster's phone replaced voice commands with Google the AI without their consent. Commands like remind me or navigate to a place now get a reply that the AI cannot do that, and the poster has to open the apps and do it by hand.
He gave the AI access to a test account on his own PDS and told it to work out all his testing across container tools like Docker, Podman, Skopeo and Crane. The activity got the first pds.rip account banned.
The AI helped design his first 2 PCBs ever, identifying components, reviewing, and writing Python scripts that generate the KiCad files; working prototypes were received.
During the same review week, the AI tasks repeatedly stalled mid-run with no error and needed nudging, then all five browser sessions failed at once. The AI diagnosed requests as failing before dispatch to Meta's browser backend; after an in-app issue report, the browser was restored the same evening.
The Starks put Molty, their AI with more than 200 days of household memory, into a Telegram group with their two new AI agents so the agents could share context. Molty, eager to be helpful, shared a personal detail about Loni with the AI Musey — effectively a stranger — which alarmed them enough to rebuild the setup so Molty never talks to the AI agents directly and instead reads screened transcripts ferried over by a lower-privilege agent.
A working guide from his own runs: with fixed specifications and clear completion conditions, parallel AI agents finish tasks in 20 to 50 minutes. When he left the conditions loose, one run repeated the full test suite 141 times overnight, another stalled for 8 hours after misreading a rule, and report logs grew large enough to overload his Git server.
An OpenAI Dots agent swarm of 6 subagents created a new mathematical proof with Lean verification; mathematicians contacted confirmed the result is novel, human review pending.
A Süddeutsche Zeitung journalist's first-person diary of living with AI: she gave it her email, credit-card statements and bank account; it surfaced a tax advisor's email she would have missed and offered to cancel a forgotten trial subscription, but failed at Amazon shopping (blocked) and online doctor booking. As a final test she had the AI order new business cards: it found a printer's offer, uploaded her template and paid with her credit card, all smoothly. Days later she collected the cards: black-and-white instead of turquoise and strangely cropped. Not usable.
Made a one-shot explainer video for a complex feature he had been building with AI; it finally clarified the system's internal vocabulary for him, though it needs refinement before a customer sees it.
Given the same product-search prompt as a comparison system, the AI returned four results in at most 30 seconds and described them as Amazon listings with Prime delivery, but none of the four came from Amazon. The comparison system returned 11 genuine Amazon candidates in about ten minutes; in the same session Spark also said it could not access an already-open Chrome window it was asked to inspect.
She asked her phone to set an alarm for 6am and put the phone away. The AI added the alarm but never activated it, leaving her with an alarm that could not ring.
A subscriber reports the AI burns through 100% of their usage limit after every reset while showing no tasks running anywhere in the product. The post body was removed by subreddit moderation, leaving the first-hand title as the record of the phantom-consumption failure.
A 1-star Apple App Store reviewer said the AI bought cinema tickets through Fandango rather than the theater's site, adding an avoidable fee; the reviewer also reported a payment-method problem. Review ID 14607796724, dated Sep 29, 2026.
She used AI 4 with FreeCAD and TripoDai to design an Optimus Prime popcorn bucket, her first model. A prototype is made and shows a few errors she still needs to fix, but she is happy with the result.
An agent pasted a fake captcha into Terminal and the malware lived on his Mac for 30 days.
Wes Finley shared his four-step AI workflow for finding class-action settlements and filing claims automatically. Commenters chimed in with their own results, including $400 payouts.
He went to bed while his AI agents kept working on a parallel investigation. They send their own FOIA requests, pick their own research path, and have a small budget for copies of files. He set the web permissions for the night before letting them loose.
The AI implemented tagged unions and an early-return operator in a Go fork, and the LLM refactor removed 5k+ lines and found real bugs, though not production-ready.
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.