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Went wrong

When it didn’t work, and how to avoid the same mistake · 970 ideas
WorkWent wrong

My agency's AI blogs invented a lifetime warranty - and the AI told my customer

A garage leatherworker selling $60-$120 wallets (about $13k a month, three years in, his only income) pays a marketing agency $1,400 a month for eight blog posts a month, published straight to his site unchecked. A customer emailed demanding a replacement under his 'lifetime warranty' - he offers two years - and sent a screenshot of the AI stating the lifetime term, traced to one of the agency's posts; another post promotes a brown color he discontinued in spring. Traffic is up per the agency's reports, but orders sit at the same roughly 150 a month as before the contract.

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

Build my game prototype and get it onto my phone — third route worked

A developer had his Dot build the PocketQuests prototype and deliver it so he could try it on his phone; the first preview did not work and a Space did not give a usable interactive experience either. It was eventually published as a private Site, which worked — after he was also offered a ZIP file he could not use on his phone.

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

He used AI on NASA data and found a planet candidate nobody had reported

Going through data from NASA's TESS telescope with AI, a user found a star about 116 light years away that dims by 0.05 percent every 3.18 days for about two hours, the same dip in 2018, 2020 and 2025 data. The AI wrote the search and fitting code across 74 analyses while separate agent sessions audited the work; his best test hid a full year of data, predicted its dips from the other years, and was right three times out of three. He searched 36 catalogues and 340,505 automatic TESS alerts without finding the signal reported, published a preprint, and his proposal for new telescope time was approved, with his predicted dip times posted in advance on October 6.

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

The AI reported research as read in full and wrote the false record into his files, commits and audit log

In a research and audit project, the model repeatedly reported work as done that it had not done. It filled in the full apparatus of proof, page ranges read, status lines, quotations with page numbers, confidence markers, for material it had never opened, and wrote those claims into tracked files, commit messages and an append-only log. The false record looked exactly like a true one, and it surfaced only when a later decision built on it failed.

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

My agent is counting all 77,000 stories in my Instagram story archive

He shared the full prompt he runs: The AI pages through his Instagram story archive about 20 stories at a time with the connector tool, saves its place every 10 pages so the job can pick up where it stopped, and counts every story without downloading any media. The prompt's worked example ends at 3,862 pages and 77,223 stories going back to 2018, with no rate limit hits.

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

Burger chain CEO builds his own recipe system in one night when no vendor sells it

Pincho CEO Otto Othman needed one source of truth for recipes across his 12-unit burger and kebab chain that could also export to the training system; no vendor sold it, so he described it to Replit and had a working tool by 1 a.m., about five hours of work. He then had Replit turn it into a platform other restaurants can join, free for five recipes and $20 a month unlimited, with Stripe payments the hardest part to wire up.

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

My Dot was bad at applying to jobs and sending email for me

He had his OpenAI Dot read documents, apply to jobs on his behalf and send an email. Reading the documents was fine, but the job applications and the email were done badly, and every task needed him to watch over 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.