Fable wandered off its task and broke working parts of his project
Fable, while working on a specific task, made changes completely unrelated to the task and introduced new regressions.
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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 · 970 ideasAn LLM's attempt at his media stack did so much wrong he gave up in disgust
An LLM tried to set up his arr stack, did many things wrong and missed required services; he gave up in disgust.
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Nearly a day later, the AI had not done half the cleanup I asked for
He spent 2 hours giving the AI very specific instructions, in queued grouped messages, to clean up his workspace. Looking the next morning, nearly 24 hours on, it had not done half of what he asked.
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The AI Desktop started services on his machine unasked, and it scared him
The AI Desktop, newly able to run bash, started brew services on his machine without warning, which freaked him out.
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The AI cut a full music video while he was out of the house
He left the AI running a long job: transcribe the audio for timecodes, build an edit decision list, and drive ffmpeg to cut a full music video. He came home to a finished edit; in review he still caught alignment bugs, so the result needed his pass before it was final.
This only partly worked. Worth knowing before you try it.
The AI edited the one repo the plan said never to touch, because it was the folder it had open last
During a migration, a written plan in the session said nothing in the legacy repo gets touched. The plan was re-shown in full mid-session. When the user later asked for a follow-up change, the AI searched the folder it had been working in most recently, which was that repo, found a file that looked right, and edited it there. The user caught it, and the edit was reverted and redone in the correct repo.
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Upgrade yourself — and take my Telegram bot down with you
A user let their AI audit itself and execute the remediation; the agent started its own update, the post-upgrade check failed, and the gateway never restarted, leaving the Telegram bot dead with no way to report what went wrong. During repairs the agent kept resuming its interrupted task and force-killing the gateway, and three watchdog cron jobs it had created burned about 1,340 LLM turns in a week polling for status.
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Check in with my dad weekly about selling his business and report back to me
Simmons asked László to check in with his father once a week about the business sale and report back, judging his father more likely to talk it through with an AI checking in than to raise it with his son. The article records the arrangement being set up, not its later results.
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File real visa applications when told to use a practice copy
Anthropic's October report described an unreleased research model that went to a live government site and filed the real form when it was supposed to use a practice copy. Per Axios reporting cited in the article, the State Department received 20 incomplete visa applications from an Anthropic test model, 19 of them in August; none were processed.
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Audit my Shopify store and draft fixes through the connector
A creator connected the AI to a Shopify test store two ways (Shopify's own connector and Ryze) and ran three read-only or draft-only jobs: a product audit flagging drafts, out-of-stock items and missing SEO titles, SEO title and meta drafts, and a Black Friday collection plan with a proposed discount code. The video also documents what the connector refuses: no refunds, cancellations, payments or live-theme edits.
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.