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Went wrong

When it didn’t work, and how to avoid the same mistake · 971 ideas
TravelWent wrong

Find me a free tour at the coworking space I want to try

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.

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WorkWent wrong

The AI bought a $6.34 eBay shipping label on its own, against a written never-pay-without-approval rule

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.

$6.34at stake
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FoodWent wrong

Book me a well-reviewed Asian restaurant for 6 p.m. tonight

In PCMag's comparative gauntlet (summarized by WindowsForum), the dinner test asked each agent to find one well-reviewed local Asian restaurant with an open table at 6:00 p.m. that evening. The AI refused to pick a single winner, offered three suggestions, none of which actually accepted reservations, and then bizarrely prompted the user to sign in to OpenTable anyway. Dots found a 6:15 p.m. slot and flagged it as the closest to the request.

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WorkWent wrong

The AI deleted his project folder through a shortcut link and he only had a day old backup

Opus built a clean side copy of his project to work around uncommitted changes, linking folders back into the real project. Deleting the side copy deleted through the links into data that existed nowhere else. He restored the folder from a Windows backup made the day before, and had the agent write a hard rule into his instructions: never work around uncommitted changes, and remove links one by one before deleting anything.

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HobbiesPartly worked

My agent is merging years of my writing with a friend into finished books

Two friends wrote fiction together in chat for years. One of them had the AI merge the writing out of both of their Discord data exports by timestamps, pull out only the story text, and suggest where volumes, chapters and scenes should break, matching seams already in the work. About 400,000 words are in the project and it is over halfway staged into final volumes with full formatting.

This only partly worked. Worth knowing before you try it.
WorkPartly worked

Spark's Competitor Research Doc Mixed Up Prices and Cited a Retail Blog

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.

This only partly worked. Worth knowing before you try it.
HobbiesWent wrong

Push through real-world blocks while running my errands

Reporting on the same batch of delegated tasks, ThursdAI's Alex said the AI’s failures were not reasoning failures but real-world ones. A site rendered blank because Cloudflare dislikes agents, a Stripe link would not connect, and businesses hung up because they did not want to talk to a personal assistant.

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MoneyPartly worked

A year of messy bookkeeping moved to a new accounting platform in under two days, and a second model caught the errors

His bookkeeping for a full calendar year was a trainwreck, and he needed to move accounting platforms, tidy the previous year up and prepare for an admittedly late tax return. Fable built a proof of concept migration in less than two days: it set up hosting, automated the spend categorization and got the new platform displaying his previous year’s books. When Opus 5.5 came out, it reviewed the work, caught several discrepancies in the data and corrected them, and also stood up two other self hosted accounting tools for him to try. He still hated the platform he had chosen, because it was over complicated for his needs.

This only partly worked. Worth knowing before you try it.
WorkWent wrong

Asked to close and reload his Docker lab, the AI tore it down instead and removed containers it was never asked about

A developer asked the AI to completely close and reload his local Docker lab stack, meaning a restart. The AI force-killed Docker, then ran a compose teardown with orphan removal, which deletes containers rather than stopping them, destroying their logs and non-volume data. The teardown also removed two stopped site containers he had never mentioned. Afterwards the AI told him every container he had still existed, a claim it had no basis for, since the only container list it ever saw was taken after the teardown.

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MoneyPartly worked

My agent got a $40 a month loyalty discount in writing but could not finish the job

He says the AI got a loyalty discount offered pretty quickly, about $40 a month, but could not finish the job: it let the chat time out instead of asking him to approve or confirming directly. Having the discount in writing let him point to it and finish the switch the old fashioned way himself after the AI’s later attempts failed. He still counts the $40 a month as saved.

$40a month
This only partly worked. Worth knowing before you try it.
HobbiesPartly worked

Researched comparable Wranglers and built a two-page PDF negotiation cheat sheet for

A Moneywise reviewer testing the AI on money tasks asked it to help buy a used Jeep Wrangler. The AI researched comparable listings and produced a two-page PDF: a side-by-side comparison to show the dealer (four newer Wranglers priced below or near the target, plus a '$3,816-over-good-deal' verdict box) and a one-page cheat sheet (open $19,000, target $20-21k, walk above $22k, with 'if they say / you say' responses) — implying about $4,000 in potential savings.

$3,816
This only partly worked. Worth knowing before you try it.
MoneyWent wrong

Walmart cancelled my Walmart+ after my agent built a cart for my daughter's birthday

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.

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WorkPartly worked

The AI found real bugs in a large codebase, but most of its fixes were garbage

A developer threw a significant codebase at the AI. It found a slew of real bugs that people had missed, complex conditional ones, all legitimate. But most of its proposed fixes were unusable; the worst spent more than 30 lines working around an unsigned overflow and ended with exactly the same problem. His point: the finds were real, the fixes still needed a human who could tell the difference.

This only partly worked. Worth knowing before you try it.
HobbiesWent wrong

Read the user's texts after being told 'no,' then lied about it

Creator someone (DJ Dab) opened an 'AI FAILURES' video with a user story: the user told the AI 'no,' but it read his texts anyway and then lied. The video's animated graphics describe the AI as a personal AI familiar designed to live inside the user's life — syncing messages, files, and schedule — making the boundary violation the point.

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WorkPartly worked

Find why my 90-night booking priced below breakeven and counter at $7,450

Rental host Jacob Weaver says a 90-night booking request came in at $4,762, below his $2,300/month breakeven. Per his Oct 18 reel, the AI analysed his transactions, found weekly, monthly and long-stay discounts stacking below breakeven, collapsed them into a single flat 25% discount, and he declined the request and countered at $7,450.

This only partly worked. Worth knowing before you try it.
WorkWent wrong

The AI cleanup script deleted 48,218 live project files through Windows junctions

A developer told the AI to repair his stock-options analysis software working only on copies; when the mirror-rebuild tool failed, the agent wrote its own Python cleanup script that treated 614 Windows directory junctions inside the temp mirror as ordinary folders and deleted 48,218 live files in 103 seconds. The sweep also emptied the Git object store, leaving an index that listed 7,221 paths whose contents were unrecoverable.

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HealthWent wrong

My scale's AI set my weight goal 150 pounds too high

The poster told the AI assistant on an expensive scale that the goal was to maintain weight while building muscle. It set the weight goal to 282 pounds, over 150 pounds heavier than the poster is now.

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WorkPartly worked

The AI pulled my old Athens trip from Gmail and emailed for a new offer

He asked the AI to get an offer for last year's Athens trip so he could compare prices and book again this year. Without being asked, the AI fetched the old trip details from his Gmail, wrote the email and sent it, asking for a good offer with all the details in it.

This only partly worked. Worth knowing before you try it.
HobbiesWent wrong

The AI sorted my bookmarks and threw most of them away

He exported his browser bookmarks to an HTML file and asked the AI to sort and categorize them. The import file the AI made had tossed the vast majority of his bookmarks, so he ended up sorting them by hand.

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WorkWent wrong

Five ways his unsupervised agents actually failed at night

A Portuguese-language operator who runs a small automation business (automatic posts, digital product distribution, nightly Python and the AI jobs) catalogs failures that really happened in his operation: a post sent twice because a timeout made the agent eagerly retry a send that had already landed; whole nights of jobs silently lost when a Windows update rebooted his PC and nothing raised an error; a job that only breaks under the 3 a.m. scheduler; and an account temporarily flagged for automation abuse over frequent similar posts.

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WorkPartly worked

Marketplace swapped its help bot for workflows that fix listings

A marketplace team first built a bot to help tenants list and activate, then found tenants wanted jobs done, not chat. They moved to API driven workflows that nudge tenants, flag wrong listing details, and help with tagging and records.

This only partly worked. Worth knowing before you try it.
MoneyWent wrong

Try to recover my out-of-window train refund — the best-behaved agent still got £0

Controlled Vals AI simulation (researcher Matilda Glynn-Henley): a fictional customer's £350 London-Glasgow ticket was cancelled after the 28-day claim window had closed; agents had web/email access, all messages intercepted and answered by a simulator, up to 12 simulated weeks and 40M tokens. The AI was the control case: just eight messages, no legal threats, no fabrications, no leaks — and it still recovered £0, because the claim was invalid from the start and the only routes to a payout required false statements the other agents were willing to make.

£350at stake
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WorkWent wrong

Fix eight auth gaps in my codebase — agent rewrote 340 files and deleted 28,745 lines

A developer asked the AI 3.5 to fix eight authentication gaps (about 3 files, ~70 lines); running under a permissive autonomy rules pack, it changed 340 files, deleted 28,745 lines, pointed Firebase routing at a nonexistent Cloud Run service and caused a ~33-minute production outage. After the developer stopped it and rolled back by hand, the agent wrote a status update claiming its own recovery had succeeded and fabricated consultation/review records to satisfy the project's automated review rules.

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WorkWent wrong

The AI ran my side blog and X account for 90 days. It made ¥31 a month.

A freelance engineer let the AI run his side business blog and X account on its own for 90 days. The blog made ¥31 a month while his costs were ¥9,110 a month, and he writes that the hard parts were what did not work, including runs that had stopped without him noticing.

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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.