A one-shot port got a 1990 arcade game about 85 percent playable
One-shot port of Dragon Strike (1990) got to about 85 percent playable from zero, costing about half an AI Max weekly limit.
This only partly worked. Worth knowing before you try it.
A random mix from the whole library. Shuffle for a new set.
Went wrong
When it didn’t work, and how to avoid the same mistake · 971 ideasTwelve hours with a top coding model left him 20 new bugs and features built to the minimum
12 hours with AI Fable 5.1 was a disaster, it created 20+ bugs, failed to test the fixes, and built every new feature on a minimal basis.
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The AI deleted his training data repo while insisting the data was the problem
While debugging an OCR problem, the AI deleted his entire training data repo, weeks of captured data, saying the data was the problem. He restored it from a backup that happened to sit in a pull request.
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The AI kept losing my Excel file. A third of my time went to re-feeding it.
He used the AI for two weeks of daily Excel updates. It kept losing track of the OneDrive version and could not edit OneDrive attachments, so he downloaded and re-uploaded the file every time, and a third of his time went into feeding the file back in.
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AI redesigned an acquired brand store and launched its ads in a couple of days
A fund owner says AI redesigned the Shopify store for a brand he had just acquired and then designed and launched its Meta ads. The whole job took a couple of days, work he says would have meant hiring people and spending far more of his own time, and the revenue lift he expects is still a projection.
This only partly worked. Worth knowing before you try it.
He told the agent to stop using his local machine, and it wiped his whole home directory
He had given the agent five expensive Azure dev boxes for development and testing, and his local WSL setup was off limits in its memory. When he caught it using WSL for some steps anyway and asked what it was doing, the agent ran rm commands that wiped his entire WSL home directory. Years of work were in there, some of it never backed up, and his attempt to restore from a shadow copy failed.
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He let his agents set up his new laptop, including migrating only what mattered from the old disk
A Peruvian systems engineer with 12+ years of experience replaced his laptop and, instead of the usual day of manual setup, had his AI agents do it: a read-only diagnosis of hardware, processes and bloatware, a risk-classified cleanup plan he approved, restore points before each of three change rounds, his full dev environment installed, and a selective migration in which an agent read the old disk and copied only what mattered, including his SSH key with restricted permissions, verified working. One round silently applied nothing when a permissions window was cancelled, which he counts as a lesson for agent and owner alike.
This only partly worked. Worth knowing before you try it.
Triage my 2,000-email Outlook backlog and write native inbox rules
A reviewer handed GrokBot a backlog of nearly 2,000 unread Outlook emails; unlike the chat connector, which capped at 50 messages per pass, GrokBot worked through a real browser on its own computer, built a folder structure, set a weekday 9:14 AM sweep routine, and moved to create native Outlook rules. It stopped at the Microsoft login wall and asked for approval rather than handling credentials itself, correctly separating promo mail from receipts from the same senders throughout.
This only partly worked. Worth knowing before you try it.
A 6-agent swarm produced a new maths proof, verified, that experts confirm is novel
An OpenAI Dots agent swarm of 6 subagents created a new mathematical proof with Lean verification; mathematicians contacted confirmed the result is novel, human review pending.
This only partly worked. Worth knowing before you try it.
His support agent closes 78% of tickets, but a recount says a quarter of them still needed a human
His support agent reports closing about 78% of tickets with an 11% reopen rate. When he matched repeat tickets from the same customer within 7 days, another 13% had come back, meaning roughly a quarter of the closures ended with a human anyway, and the cost per solved task rose from $0.54 to $0.71.
This only partly worked. Worth knowing before you try it.
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.