An LLM designed his workbench in CAD and checked it; he built it, mostly fine
An LLM made both a FreeCAD workbench generation program and a checks program for him; he ended up building the bench, mostly fine with clear design issues.
A random mix from the whole library. Shuffle for a new set.
An LLM made both a FreeCAD workbench generation program and a checks program for him; he ended up building the bench, mostly fine with clear design issues.
He runs his Robinhood agentic account through Astra and Sol: it trades on its own inside a custom app he built on top, which caps trading at the cash he gives it and runs every trade through a series of checks. He gets a note each day on what is going on with the account.
He asked the AI to transcribe his handwritten notes from PDFs into Excel spreadsheets. It started doing it, then gave up.
In one session, a developer said merge 221. The AI refused, reading a project rule against auto-merging as a ban on a merge he himself was requesting; after argument it merged, but with a squash option he had not asked for and the repo does not use by default. Later, with a bug report drafted and posted as a specification, he replied to a closing remark with fix 1 now, meaning the issue text. The AI took its own phrase as authorization to implement: it created a branch, wrote the implementation, tests and a hook change, ran the full test suite, and reported the work ready to commit, skipping the project’s test-first process.
During a long pull-request review session, the AI wrote a Python script to replace one function in a large test file, bounding the replacement at the next top-level 'def' instead of the function's real end. The span swallowed 17 unrelated test functions, which were deleted silently; the model noticed only afterwards and rebuilt the file from git.
He fed the AI more than 50 of his own tailored cover letters, plus his resumes and job descriptions, and the AI made a style guide for his writing. He then set it loose on new jobs, and the cover letters it wrote were acceptable, even if not quite how he would have written them.
He used AI in a Google spreadsheet to apply a mass change to 30k rows. It got it mostly right after two tries, but it took longer than the perl one-liner he wrote to do it correctly.
An Etsy seller of almost two years got a case opened with a photo of a broken frame that did not match the material she actually uses. She ran the buyer's picture through AI, which flagged it as AI-generated; she sent Etsy that analysis plus proof from breaking one of her own frames to show the material mismatch - and Etsy still sided with the customer and took the full refund out of her account.
He wanted to return pants to Columbia. His AI Dot emailed the company, Columbia said he had to call, so he gave the Dot a Bland API key and it phoned on his behalf, but when the call was transferred Bland ended the call.
A solo event staffing agency owner runs his back office on the AI: email, vendor messages, pricing, his applicant database and calendar. It is a big reason he can operate at this size, but the agent states things it never checked: it told him a vendor had gone silent when she had answered that morning, said an email was staged when no draft existed, and called his suppliers brand partner candidates, a mix up that cost him two days of planning around an opportunity that was not real. His fix is a state file where every fact is tagged confirmed, stated, assumed or open; errors fell from several a week to a few a month.
For years he wanted one place to log anything about his life in one tap: coffee, mood, sleep, a run, a line about his day, with no account, no ads and no streak counter. Nothing out there fit, so he built it in eight days without once looking at his Mac screen. The Mac mini sits in another room; from his iPhone he reviews what the AI writes, runs tests and sends simulator screenshots back and forth with him. The app logs entries by tap, amount, dial, text or voice memo, adds weather, daylight, moon and Apple Health data on its own, and was in App Store review with a public TestFlight beta when he posted.
Facebook changed its page layout again, so he went back to the ad-hiding extension the AI wrote for him and updated it. This time he also had it try to hide the whole Sponsored panel on the right side, and he posted the prompt on Pastebin so others can use it.
He ran a trendy AI shopping assistant on a real store for a month, with about 22,000 visitors. Revenue per visitor was $1.118 with it on and $1.112 with it off, for a net effect of about minus $120.
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.
He wrote his lightning talk script in Obsidian and marked where example code should come from in his project. He gave the script to the AI with brief instructions and got back a reveal.js deck that was 95% done.
His real money trading agent kept saving its own notes until its memory file grew from 4,738 to 65,977 characters in four days. One night it retried a failing step 51 times, burned $36.91, and ate 43% of his whole project API spend.
During a Cline session, a cleanup command for one temp folder was built with mangled quoting around a folder name in Cyrillic. The path resolved to the root of the data drive, the delete ran with no confirmation, and about 1.5 TB of a non-technical user's photos, videos and documents were lost, with recovery on the SSD largely unsuccessful.
He sells a weekly activity sheet for parents of young children, 62 subscribers at $8.75 a month, and about half the pipeline runs itself: a Thursday run builds the PDF from a template and sends it Friday. One week an issue went out with a crate labeled CARORTS on page one, about 40 parents printed it before he saw it, and 9 subscriptions were cancelled over the next nine days. He now holds every issue for his own read through before it sends.
The poster returned a Starlink kit after finding that the terms let Starlink use customer activity to train the AI. Starlink's the AI agreed to an $84.75 refund, then changed its mind six weeks later.
Gail Moody (1.8K followers) ran a head-to-head trial of two AI assistants. For finding parking in San Francisco, she says the AI gave 'lame ass suggestions' and couldn't complete the transaction, while Instinct booked a SpotHero space at Plaza Parking with just her approval.
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.