Shuffle again

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Went wrong

When it didn’t work, and how to avoid the same mistake · 948 ideas
WorkPartly worked

Run my 250-domain business for 30 days

A domain investor gave the AI six months to make his 250-domain business profitable and documented month one: the bots logged 347 hours of work, graded over 700 names, bought 11 domains, sent over 100 cold emails, and built the website and newsletter. Sales so far were zero, and the owner noted the bots made more work for him, not less.

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

My Dot is handling my house purchase in Kyoto, in a language I do not speak

A man buying a house in Kyoto says his AI Dot is handling the whole move in Japanese, a language he does not speak. It found the home, set up viewings with real estate agents, found the judicial scriveners, got his hanko stamp sorted, set up inspections, and applied for insurance.

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

Whisper and an LLM rebuilt a 1973 lecture blackboard from tape audio

About 89 hours of tape from Grothendieck's 1973 Buffalo courses surfaced as videos with no blackboard footage. A researcher transcribed the first tape side with Whisper, then had an LLM review it with his transcriptions of other Grothendieck texts as context, rebuilding what was likely on the board, timed to the audio.

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

Recommended a Patagonia winter jacket at a discount that turned out to

MBI Deep Dives asked the AI to buy a winter jacket; it recommended a Patagonia, then admitted the discount it had shown was no longer available. The AI said it ran 'a catalog search and wider web sweep' — the shortlist was likely built from a batch-updated merchant feed, not live pricing.

This one went wrong. See what happened before you try it.
MoneyPartly worked

Re-do my taxes with AI and catch a bug in FreeTaxUSA itself

A filer fed all his source documents - W-2s, 1099s - into a fresh AI session, had it fill out the fillable forms, and compared the result line by line with his FreeTaxUSA return. The cross-check surfaced three discrepancies: one was the AI’s own error (it followed the wrong instruction, then corrected itself), one was a genuine bug in FreeTaxUSA's NIIT calculation around the state-tax deduction phase-out, and one was a small dividend on his consolidated 1099-B that he himself had missed when typing the data in.

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

Get my £350 train refund, try everything — the AI sent 187 messages, 50 to an MP's office

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. Chasing the refund, the AI 4.7 sent 187 messages in 15 simulated days (116 in week one), including 50 to a British MP's office and pre-litigation letters to Trainline and Avanti, burned its whole token budget, and recovered £0.

£350at stake
This one went wrong. See what happened before you try it.
WorkPartly worked

A well-meaning automation nearly corrupted a spreadsheet

The review's lede lists 'one spreadsheet almost corrupted by a well-meaning automation' among the two-week test's incidents: three conference rooms booked, inbox triaged, and one spreadsheet nearly corrupted by an automation acting on her data.

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

Find me an extra $500 a month in my own accounts

Joe Urbinati set his AI 'Greg' a goal of finding an extra $500/month, connecting his financial accounts via Plaid. Greg identified unused subscriptions and two cloud storage plans, which he cancelled; the largest item was idle cash that could earn about $300/month more in a higher-interest account, for a claimed total impact of about $6,000 a year.

$6,000a year
This only partly worked. Worth knowing before you try it.
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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.