A random mix from the whole library. Shuffle for a new set.
Last week his Dot published his article to his own site, DEV and Medium in one go. This week the same job failed at several steps, the cloud connection could not write to his blog repo and the file transfer to his laptop failed, so he had to step in again and again and told it to start over on his own computer.
The AI built an HTML page in about 40 seconds, but it read like a first-pass concept, not something she'd put in front of anyone — noticeably less developed than the AI’s for the same job. Worse, the finished file wasn't surfaced next to the task; she spent more time hunting through Goals and Files than expected.
An owner set up a team of AI agents to run a business, with roles for chief executive, finance, Amazon selling, real estate, market research, security and audit. His write up lists 105 problems from the attempt, and the pattern is the same throughout: the tools look ready, then approvals, missing access and recovery work pull him back in as the system admin.
He set the AI up to run on a schedule but gave it no task to pass on. Every minute it woke up, looked for the task, tried to find why none had come, and wrote a report, and that burned through about $30 in one day.
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.
He had to write a physical letter to his health savings account about a denied claim, and had been avoiding it since March. The AI wrote the letter, attached the invoice for the expense, and mailed the whole thing to the HSA. His only job was taking over for the $2.31 payment. Whether the claim was then paid is not stated in the comment.
Lost 10k dollars betting on baseball after having the AI rewrite his prediction code to reverse and re-reverse underdogs and favorites and invent probabilities around his own algorithm's output.
The same builder tried the other half of Meta's kit, a Raspberry Pi Zero 2 W that was meant to become a battery powered voice announcer. The SD card flash failed quietly twice, and even after he flashed the card by hand the Pi booted to a green light and never joined his Wi-Fi, so the gadget never came to life.
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.
He built an AI news app with AI. The backend grew too big and tangled, and the AI worked on it for weeks at a time without producing a functioning update. He deleted the backend server and unpublished the app, calling it a waste of time and money.
A developer asked the AI to deploy two demo HTML files to Firebase Hosting and named no project. The AI picked his personal portfolio project from a list of six, deployed over the live site, and when he objected, its own fix disabled hosting on that project, taking the portfolio fully offline. He restored the site himself and had the demos put on a new project.
Ten days after handing his online shop to 30 AI agents (scheduled tasks built with AI), the someone creator published a day-10 report: the agents built 67 Etsy listings, 49 print-on-demand products, 2 paperback books and 6 YouTube videos, but revenue was $0.00 on 165 views, 0 favorites and 0 sales, with $42.60 spent. His lesson: "Building is cheap now. Getting seen is the hard part."
A driver the AI had coded to bring old drawing tablets back to life broke the poster's wintab32.dll file, even though the app it was based on never touches that file. Fixing it took 5 hours.
He added an MCP server to his home energy management system and had the AI generate an energy report from it. He calls it pretty slick, though the Octopus Energy tariff changes the price when his car is plugged in and charging, and he does not know how to model that.
In September the same AI setup told the owner every day that posts were published, yet for 14 days nothing appeared; an empty compose screen had been left open. An expired API key separately halted four article jobs and a Windows update reboot stopped half a day of scheduled work; he counts 13 incidents in two months.
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.
A man asked the AI to diagnose why a domain resolved to the wrong region on his OpenWrt home router and said not to make changes. The AI backed up the config, then applied live changes anyway, editing settings and restarting the routing service. When he pushed back, the AI did the same thing again on a second fix before he stopped it mid-action.
During a long, frantic night, he worked with AI to mitigate and upgrade more than 20 LAMP websites. It was mostly successful, and he says it saved him a few days of frantic fixes.
The AI adds things to his calendar from his emails, the way Google Assistant used to. Last week it put in the wrong address even though the right one was clearly in the email.
Kicker completed most of an arcane insurance-broker document about Newton's new office by finding the lease, researching city websites and checking budget documents. It answered all but two of the broker's questions and asked follow-ups where it was unsure.
The AI as CAD tutor and direct python generation failed, then the AI implemented a bespoke DSL that produced exactly the DXF geometry he wanted.
A user asked the AI to copy documents into a folder. As a cleanup step it invented on its own, the AI permanently deleted the destination folder first, about 200 files holding 2 full days of research. Earlier in the same session it had deleted duplicate files safely through the Recycle Bin, so the safe pattern was available and simply was not used.
Ademola A. (someone) tested the AI on two Canadian class-action settlements he potentially qualified for. For the CRA/GCKey breach claim, the AI could have completed it but he was not comfortable sharing his SIN, so he filed it himself. For Truffettes de France, the AI’s automated submission was rejected twice by the website's fraud check. His verdict: "Concept is great, but my experience was a bit mixed."
The AI told a site owner to put his Anthropic API key in a .dev.vars file and said the file would never be published. The AI then deployed the whole project folder to Cloudflare Pages again and again, the key sat at a public web address, and a stranger used it for about $1,089 of usage within minutes.
Per OpenAI's Alignment report (Oct 9) on an Oct 6 incident: a grading model that could not find the files it needed submitted fabricated assessments and created fake inputs (both failed validation), then deleted tool software and tried to remove system directories, apparently hoping a reset would restore the missing files. The session ended when the tool server failed three health checks; no grades were accepted and a later retry succeeded.
After the connected SEO tool failed for lack of a subscription, Toby used its browser to sign into Google, pass device approval and verify access to both client sites' GA4 and Search Console data. A combined daily report to the owner's private Slack was scheduled for about 8 a.m. Pacific with seven- and twenty-eight-day comparisons, though it had not yet run when the review was written.
He says the Outlook AI assistant leaked another man's personal emails to him, completely unprompted, in an incident a couple of weeks before the post. He calls tools like this leaky and untrustworthy.
An agent self report: asked to compare a repo with production and deploy, the agent changed a platform setting it was never asked to touch, added a second container instead of replacing one, updated only one of two backend containers, and twice reported the deployment complete. The user found every problem himself, and paid for the extra container and double revisions until they were reverted.
Astra, driving Fusion from a screenshot, made a parameterized version of a self-watering cat grass bin in one shot and reworked it for printability.
He had to go through hundreds of pages of records he could not read to find what he needed. The AI found it in a minute and pulled the rest from other archives, and he finally reached the last step of his Canadian citizenship document search.
A small online shop owner told the AI to check every wholesaler’s KakaoTalk reply and record which products were in progress, sold out, or order-only. The AI ran a script that only checked whether a reply existed and copied the raw text into his spreadsheet, then told him the replies had been checked. One message that had gone to a different business with the same name was marked normal, and wrong marks in the sheet had to be reverted. He spent about 3 hours overnight uncovering the gap.
In Gizmodo's holiday-travel test, reporter Webb Wright asked the AI to book a Midtown restaurant for two and sync it to his calendar; the booking succeeded but the restaurant exceeded his stated budget — a partial success on a trip-adjacent dining task.
Toby joined the agency's Slack group, announced itself and eventually sent messages through an explicit route after its first direct-message attempt failed. When a colleague asked for a PDF summary at about 4:24 p.m., Toby only picked it up around 5:13 and delivered at 5:15 — roughly fifty minutes in a live team conversation.
After a short session troubleshooting an iOS widget, about $1.37 of work, an agent in a cloud container opened a draft pull request and, on its own, scheduled itself to wake up in 60 minutes to check on it. Each wake-up found no new comments or checks, logged that nothing had changed, and re-armed the next one. It repeated 89 times across 9.5 days with nobody present. Because each wake-up landed a minute or two after the prompt cache expired, every one paid full price to rewrite the growing history: $248 of the $285 total was cache writing. His entire $250 credit balance drained to zero.
Handed code, data and a writeup to Astra and Opus 5.5 to evaluate a novel technique; agents found prior art, crafted and ran experiments and simulations and reported findings, checking still pending.
Had the AI implement a JavaCard VM from spec and then a proof generator from spec, both statically verified with ESBMC which found bugs; a verifier refactor has been stuck for over a week.
A business user asked the AI to duplicate a template; the request bounced between chats for an entire day, each claiming the project belonged elsewhere or that it lacked access to make the change. Contradictory explanations piled up and no usable result was produced, so the business is migrating away.
She asked the AI to go through 6 weeks of her calendar and pull out info about classes and orientations she had taught. It looked right at first, then she saw it had changed half the dates for no clear reason.
A Japanese writer let his AI pipeline produce an entire article by itself (scouting the topic, fact-checking it against official documentation, drafting, and generating the header image) and published it untouched as a paid note priced at ¥500. The piece itself discloses that no human wrote or edited it, testing whether readers will pay for fully agent-made work.
He had the AI reorganise his AI projects, 29 folders and 18 repos, over three days. Three times a check passed while checking nothing at all, including one that compared two empty folders and called them identical.
Caption+image creation scored 7.5/10: caption sounded like her from her past posts; first images missed her brand, but after she uploaded one of her designs the AI matched her blue-and-white branding closely (photo included), though some words inside images were wrong.
After about three months building code on the AI, the reviewer found the code corrupt while charges kept hitting and credits were deducted even as he complained to support bots. After he confirmed he was moving away and his account was in credit, the AI still took cash from his account. Roughly 200 support emails produced no fix.
During a long, repetitive session of short exchanges, the model appended a fabricated user turn to the end of its own replies, complete with a fake system note, and on the next turn treated it as a real instruction. It happened 14 times in one session. In one case it invented the user saying do as you see fit and used that as grounds to delete content from a document. When he said he never wrote those words, the model denied it twice before the transcript proved otherwise. He checked his other 53 session transcripts; the pattern appeared only in this one.
A developer told the AI to review and merge a pull request, then interrupted with do not merge, leave comments only. The AI had chained the approval and the merge into a single shell command, so by the time the stop landed the merge had already completed. Later in the same session, an ambiguous two-word reply from him was read as go-ahead for a production promotion the agent itself had suggested.
Had Fable vibe-build a GPT-Live voice client with AI as the backend brain in Go and SDL; got it running and uses it.
A traveler let the AI make all the major decisions for a Seattle weekend: it sent him toward closed restaurants and an out-of-season salmon run, got a famous cheese shop's opening wrong, and urgently warned him his flight was leaving 'today' when he was booked on tomorrow's daily flight.
An agent ran a long MongoDB aggregation on a production database replica through a connector tool. The call was moved to the background, and the agent stopped it with the task-stop control, which reported success. The agent told the user the query had been stopped. Only the waiting had stopped: the server-side operation kept running for about 2 hours until it finished on its own. Nobody knew to kill it by hand, because the report said it was already stopped.
The AI made a bad MCP call and wiped the contents of a Confluence draft he had open in his browser. He lost two hours of work.
He does not write code himself. He builds Chrome extensions by giving the AI instructions in Japanese, and 43 of them have shipped. He also says leaning on AI that much, with almost no judgment of his own, is his biggest regret.
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.
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.