A random mix from the whole library. Shuffle for a new set.
He has worked in SEO since 2009 and has no coding background. He shipped a SaaS with paying users anyway. His rule is that a different model reviews everything the AI builds, and that habit once caught 14 real bugs while all 10 tests were green. He liked the workflow so much that he turned it into his product, MegaLens.
A reviewer uses AI as producers for his projects, with the bots managing multiple Cursor Cloud Agents doing the underlying work.
A user ran a wide-research task with a detailed brief demanding context-rich, specific transcript passages; the AI delivered a generic extraction instead and consumed 10,000 credits. The AI admitted in writing that the output did not follow the requested standard, yet support refused to refund the credits.
The same side business owner had the AI redo his website and take over its search work. The AI logs into his Google insights and handles the weekly optimisation for the words he wants to rank for. After two weeks the site sat at the bottom of the first page for those words, on an old Weebly site he expected to hold it back.
An agent works his support queue and processes refunds on its own when the order is under $50 and inside 14 days. It cut about 40 minutes of daily sorting and checking, and he now looks only at the cases it flags.
Reporting Anthropic's September 23 engineering post, this analysis describes the AI running a two-week performance sprint from a Slack channel: 150-plus threads, benchmarks built for each bottleneck, and more than 3,000 merged changes with no customer-facing incident. Time to a typeable page at the 75th percentile fell from 3.1 seconds to 0.55, with a human approving every pull request.
A Creative Cloud user wanted to move his work laptop to Linux, but Adobe makes no Linux versions. With a lot of help from the AI he built a patched version of Wine, the tool that runs Windows programs on Linux, and shared it free. On his laptop, Photoshop, Illustrator, Premiere Pro, Audition and Media Encoder now install and run through his normal paid account.
A creator ran his Facebook page on a seven-prompt the AI system for 60 days: The AI mined his top 10 past posts for a repeatable formula, planned 30 days of content, drafted each post three ways, and rescued weak posts every Sunday. He reports 56.5 million views, 69,116 new followers and 4 million engagements over the run, while he still edited every post and replied to his community himself.
A person's OpenAI dot could not push its work to GitHub. OpenAI then deleted the virtual machine the dot was working in, and hours of work disappeared with it.
The solo maintainer of the karasu modeling language runs dependency updates through an AI skill that investigates each Dependabot PR before anyone merges: release notes, the diff between tags, publisher or ownership changes, install-time scripts, lockfile edges and known advisories, written up as merge, hold or reject recommendations in a design doc. In the week of Oct 10–17 three triage rounds fed 88 merged PRs (16 from Dependabot) and 12 architecture decision records, and the process caught a rebuilt lockfile silently moving a package off the reviewed version.
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.