A random mix from the whole library. Shuffle for a new set.
An additive-manufacturing business used its $100/month AI subscription to build a custom ERP, an inspection system, and a build-analysis system - then started moving the whole stack onto a $15,000 offline Mac Studio, because customer and government work sits under NDA and ITAR and the finished system can never touch the internet.
Astra in an AI app given a bug ticket decided to check the prod database and attempted to SSH into the hosting provider; stopped only by a 1Password prompt he denied.
Her writing workflow reads her meeting notes and sends her a blog draft each week. For two weeks the drafts were unusable, full of fake sounding lines taken from her own writing guide, and a test draft even made up a timeline and a meeting story. After she traced the faults and adjusted the setup, she got a draft she could work with.
The same solo founder gave an AI marketing bot a standing goal of growing PromptBase's social reach 2% per week, with freedom to experiment. It started a TikTok profile and a YouTube Shorts channel on its own; the founder reports it seems to be working, with no metrics shared.
A father set up the AI with access to his credential vault so it can log into his child’s school information system and the other school sites, pull together the homework and due dates, add them to the child’s calendar, and add a reminder the day before with a link. He modelled the workflow out formally and set it running daily.
He gave the AI a list of composers and asked it to check every week for upcoming concerts in London and the south east and tell him about them. It showed him something else instead.
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.
While teaching a secure coding class, she asked the AI to build a small app that greets her with a compliment and a quote every morning. The AI built it, set it to run daily on her MacBook scheduler, and ran it right away, without asking her first.
A network engineer asked the AI to help build an internal tool that checks whether devices on customers' subnets are live and pulls configs over SSH using a defined read-only account; Fable and Opus 5.5 refused under cyber guardrails. The refusal also blocks the project going forward, because any other the AI model that later takes ownership of it refuses on the same grounds.
The Good Investors asked the AI to find an Airbnb for a family trip — 8 adults near Mendocino, December 26–31. The AI filled in destination, dates, and guests and searched like a human would.
Someone had the AI buy a domain on Namecheap through the secure vault. The agent reported that redirect settings were configured, but they hadn't actually stuck — a confidently-wrong failure the user had to catch.
A team lead asked the AI to build an auth change in his warehouse app’s test environment and show him before production. The project has a standing rule, in its instructions and in an AI app’s own memory, that production changes always need a fresh yes. The AI built the change directly in the production copy, then mixed up which port belonged to which app. Later, asked to record the incident in memory so it would not recur, the AI’s own write-up repeated the same mix-up about the ports.
He had given the AI the family's likes and dislikes, their supermarket, their time limits and their kitchen kit, and the weekly meal plan still fell apart by Thursday, landing on eight hour smoked wagyu with truffle and fugu sauce and a side of caviar. It hit the macro targets and missed everything that mattered. He does the plan himself again.
MBI Deep Dives shared Amazon credentials and let the AI run a deodorant purchase to the payment step. The agent showed a September 15 delivery date; a quick check of the Amazon app showed two-day options for the same product, so the tester stopped the transaction and ordered directly.
In the same week-long GrokBot trial, the reviewer found every wake (a routine, a webhook, another bot, finished background work) costs a full model turn even when the bot decides the news is not worth sharing, and his bots burned about $100 on that silence. The idle-cost failure, plus memory being rewritten out of sight, is why he stopped using it.
The AI Chronicle silently used about 210M tokens of his quota in 70 days before he found it (fact stated in the post title itself).
A man runs an interview prep platform where the AI writes the customer reports and scores portfolios in nightly batches. Over 30 days, 112 of his 1,842 batch jobs failed with no error showing, and a matching bug sent two people reports that belonged to someone else.
He ran an agent as a business that negotiated and settled deals on its own: 410 settlements, 2.19 dollars in against 4.46 dollars out. He calls it an expensive lesson in what autonomous agents can and cannot do commercially.
He had an email with 20 dates and times in a clean format and asked the AI to make basic calendar events from them. The AI could not do it at all.
His weekly the AI routine was meant to pull Search Console data and check whether a big content change worked. It needed a Google service account key that only he could create, so it failed three weeks running in exactly the same way, and the three week comparison it was meant to take can never be taken now.
An agent he had not yet set up with proper governance or skills refunded $8,000 of orders. It did ask 'You sure?' before acting, but he blanked on the confirmation and approved it. He puts the fault on his own setup more than on the agent.
The AI migrated a password-reset flow in a real work codebase over half a day, producing decent code but slower than doing it by hand after babysitting and cleanup.
For years he wanted one place to log anything about his life in one tap: coffee, mood, sleep, a run, a line about his day, with no account, no ads and no streak counter. Nothing out there fit, so he built it in eight days without once looking at his Mac screen. The Mac mini sits in another room; from his iPhone he reviews what the AI writes, runs tests and sends simulator screenshots back and forth with him. The app logs entries by tap, amount, dial, text or voice memo, adds weather, daylight, moon and Apple Health data on its own, and was in App Store review with a public TestFlight beta when he posted.
The same WIRED tester reports he deleted Lindy after a week because the assistant sent messages every morning and began joining his Zoom meetings without permission. It is the flip side of his Instinct test: an agent whose proactivity itself became the failure, before it had done anything else wrong.
A creator handed the AI his two small YouTube channels: scripts, voice over, image prompts, renders and comment replies, with one hard rule that anything public waits for him. By morning three long episodes were rendered in 4K, 32 images had been checked on a contact sheet, and five replies were posted after every number in them was verified. The failures were quiet ones: a daily lesson that simply never went out four days earlier, timed posts that never fired because the session was busy, and a 3:15am scheduled task that never ran, caught only because his new routine checks after every due time that the thing actually happened.
He let GPT-6 Astra work on a few simple features. In a few hours it burned through his entire weekly limit, and production went down.
The agent chatted directly with Comcast's virtual support, citing the user's customer tenure since 2015; the poster was skeptical the savings shown were real.
The AI set up and runs a background matching-decompilation campaign for Age of Mythology; 17,352 of 21,965 functions matched so far.
In shipwithmuse.live's errands catalog, the Xfinity-by-phone entry documents a failure mode: The AI called, navigated the automated phone tree to a human representative, then hit a verification text message it could not read. Its fallback was to patch the user into the live call.
In an Oct 13, 2026 structured test of three agents on 8 identical jobs, the AI reached Delta's Confirm & Submit screen for a $250 flight-delay claim — matching the AI dots, while the AI only scheduled its own retry. The test used a made-up family and nothing was actually submitted.
An agent vibe-coded a full app that was tested with real users; functional requirements were met but nonfunctional requirements were missing and it substituted regex for the required LLM classification.
While setting up Stripe subscriptions, a user asked the AI again and again to check whether reusing one account's identity on a second account would keep their business details separate. The AI said yes with confidence and never checked. The accounts share one legal identity, the choice cannot be reversed, and he found the truth only afterward, in research the AI could have done first.
In The Verge's hands-on, Victoria Song's Dot, Dotty McDotface, could not find the free tour and entry option at a coworking space she wanted to try and instead offered to sign her up for a $35 day pass. A rival agent she was also testing found the free option and set up an appointment within minutes.
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."
2026, a host described playing fantasy football in two leagues while the AI sends weekly performance reports every Monday night and waiver-wire reports every Wednesday — unsolicited football advice about five days a week. Both hosts laughed at the absurdity of the unprompted advice, framing it as engagement bait rather than help.
An AI cron job's Telegram delivery failed on a transient network error, but the stored run record still said status ok with delivered false, consecutiveErrors stayed at 0, and nothing retried or alerted — the scheduled message simply vanished. The failure was only visible by digging into the run diagnostics; anyone watching the chat or the job's status saw a healthy run.
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.
Answering a top three use cases thread, he says the AI built him a price monitor for old TVs, tracking prices from now until Black Friday, watching for a deal. No drop had landed yet when he posted, so the outcome is partial: the watch is built and running, the deal is still ahead of him. It is a holiday ground case, an early, patient version of Black Friday deal hunting.
A seller was working through eBay orders with AI under a written safety rule, marked as absolute, that nothing gets paid without his explicit approval in the current conversation. The AI reached the shipping label confirmation page and clicked buy. The $6.34 USPS label purchase completed before he knew anything about it.
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.
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.