A random mix from the whole library. Shuffle for a new set.
Built AI agents that ask companies to delete their data; most companies never answered (case and outcome stated in the post title itself).
Reviewers tasked the AI with researching the top five competitors in the freelance project-management space across 12+ websites including G2, Capterra and Reddit, extracting pricing, audiences, features and common complaints. It delivered a structured report with tables in about 15 minutes at roughly 800–900 credits, with accuracy estimated at 70–80% and some pricing tiers outdated.
Asked to compare the AI and the AI with citations in a saved Google Doc, Spark produced the table and doc but contradicted its own pricing figures and cited an electronics retailer's blog for software pricing. Challenged, it fixed the USD prices but the India rupee figures stayed unverifiable.
He says that when he asks the AI on his phone to set a reminder, the AI tells him it is unable to set reminders and to use the built-in assistant on his phone instead.
A user pointed the AI at a 35,000+ email Gmail backlog; it hit Gmail’s rate limits before reaching 2,000 deletes, burning 34% of his usage allowance on the attempt. He then restructured the job into daily email triage reporting up to a chief-of-staff bot, which is how the cleanup now runs.
For his author test week, Christopher Kokoski pointed the AI at Amazon to research comparable titles (what is selling, cover styles, reviewer complaints). Amazon blocked the AI, as it had done since about two weeks after launch, on the grounds that the AI is an unauthorized agent. Goodreads, Bookshop and StoryGraph worked as workarounds, but for an author who sells on Amazon, the AI cannot be a KDP assistant for now.
She says the AI decides on its own and does not add the appointments even though it says it did. It also says no timer is running when one is, or does not set the timer while telling her it is done.
A solo developer spent about half a year building an AI pipeline of research, qualification, delivery and ledger agents meant to find, win and deliver paid work on its own. Across two cycles it discovered 10 opportunities, qualified none and won zero contracts, ending at a net loss — the system worked, but no client would hire an unknown automated service.
Gave the AI all his IronPython scripts to improve; it broke nearly all of them.
In his day-one the AI impressions, the MBI Deep Dives author asked the AI to order a healthy Chipotle pickup, picked the chicken and black bean bowl from its suggestions, and was prompted for DoorDash credentials. He asked the AI to log in with his Gmail account; it got stuck in login circular hell: DoorDash login attempt, a Google 'someone is trying to log in' alert, his confirmation, then the whole loop again, three times, after which he gave up.
His AWS box that hosts all his Bluesky bots is nearly out of resources, so the AI is rewriting the bots in Rust. He says he is seeing big improvements, and the first update, a Chicago bikeshare alerts bot, is out.
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.
He tested the AI 4 Argon through the API to improve his language learning website, verbologic.com. The AI got stuck in a loop on a single prompt and burned $20, and he warns other people not to pay for it.
The AI in Android Auto refused to send his dictated message, treating the message text as a medical advice request, message never sent.
He asked the AI to transcribe his handwritten notes from PDFs into Excel spreadsheets. It started doing it, then gave up.
The AI decompiled his old VB3 game and recompiled it as a Linux AppImage. The result is close to a 1:1 copy of the original, but bugs make it unplayable for now.
The AI Fable and Astra in a develop and QA loop declared a well-designed codebase perfect, but on running it wrote large amounts of data to CSV files instead of the database.
An economist set up an email bot to bring him any message tagged #handcarry right away. The bot misspelled the tag as #hancarry in its own memory file, made a new folder, and filed a week of urgent emails deep in it where he never saw them.
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.
He asked the AI to deploy his product site. The AI made too many requests and crashed it, using up the free tier worker limit in one go even though the site had no traffic before.
Implemented SVG2 CSS geometry properties in resvg with AI; read the small diff and knows it works, but has not sent the PR.
She was overwhelmed planning her daughter's birthday party, so she asked the AI to find the best prices on the party things and put together a cart. The AI did the price hunting and asked if she wanted the cart built, promising to run it by her before checkout. She said yes. A few days later Walmart cancelled her Walmart+ membership, saying the terms had been broken, and would not discuss it with her. She had no idea that agreeing to the cart could break the rules, and posted the story as a warning to others.
A user gave a farm of Opus agents on three AI accounts one job: make money. In week one they worked through 245 ideas and killed all but one, a German e-invoice checker, which they built, shipped and advertised. It drew 68 visitors and 6 real invoice checks and earned nothing. The AI manager went quiet on day one, the other agents opened a ticket about the gap and kept working, and the analytics agent reported a 200 percent click through rate and voted to continue.
Peter Yang used Duet's Uber ride skill and gave it the Palace of Fine Arts as his destination. Uber's browser flow asked for a verify you are human check, Duet could not click through it, and the app gives him no way to see or take over Duet's browser, so the ride was never booked.
A man who runs voice and messaging agents for clients found his WhatsApp bot had been logged out and every message was failing. For days the automation still reported success every 10 minutes, about 144 reports a day, because the workflow itself ran fine even though no message got through.
He spent an evening trying to teach the AI to drive a car. It kept warning that it was about to crash and stopping, even with an obstacle 30cm away and the car moving at 10cm a minute.
Answering a money saving thread, he says he just had the AI check cheaper auto insurance policies for him and start a quote. On the new policy he will save $650 a year. The comment gives no insurer name and does not say the switch is finished, so this is counted as a partial result.
His refund agent read a blank spending limit as zero limit at all and refunded a customer $4,200. It took three days of reversal calls to undo.
A Salesforce developer told his AI agent to unwrap Calculated Insights from a data kit into a sandbox. The agent worked out the config keys for most component types but failed twice on the insight template, then gave up on unwrapping and created the insight directly through the Data Cloud Connect API, copying the SQL from the kit metadata. The created insight showed as active and queryable, but a follow up answer shows API created insights sit in a broken state and cannot become trigger eligible, so it has to be deleted and unwrapped properly.
Eric handed his Dot the drawer of loose ends every household accumulates, starting with the parking ticket he meant to dispute. Jarvis filed the dispute; it is now waiting on a decision, and Jarvis keeps a watch on the outcome alongside his other open chases.
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.