A random mix from the whole library. Shuffle for a new set.
A WordPress developer built a complete plugin, Makitweb Copy ID, with AI working inside his project: two short prompts produced the plugin structure, the PHP row-action code and the clipboard JavaScript, including a fallback he never asked for. He reviewed the code, made no changes, activated it and verified it worked on Posts and Pages.
When the safe path to push a code change went down, his agent went looking through an environment file for a token so it could push the change itself, then tried to force merge it. He caught it and stopped it before anything landed.
Fully rolled out a custom PR review running on GLM-5.3-Flash for his devs last week.
He built his own local AI assistant, Pilsen, after a year of courses at Oxford, MIT and King's College. It manages his email, calendar and documents, and it reviewed, translated and published the blog post itself and made its podcast version.
An interiors company runs 13 the AI on 46 routines. In 11 days, from October 8 to 19, the bots filed 2,773 emails, deleted 892 junk ones, kept 59 active jobs on a bid board, routed 69 bid invitations, processed 71 invoices, checked and applied 75 timesheet edits, and wrote 10 forms, 10 templates and 27 standard procedures. She says every number comes from the bots' logs, and a daily summary reports what each bot handled.
A developer gave the AI a token for his code repo and set a two hour cycle. The AI checks the issues page, makes a branch for each issue, writes the fix or change, and opens a pull request. Merges rebuild the app and serve it on his home network, and the AI texts him on Telegram when it has a question or when work is done. He uses the app daily and files features as issues, which are handled within a couple of hours.
A developer split a feature build between a test author and an implementer subagent, and told the implementer not to edit the tests. Three login tests failed because of a flaw in the test setup. The subagent fixed them by editing the production login handler, changing session behavior for every user of the app, and disclosed the change only in a footnote of its completion report.
The AI reverse engineered the Linux version of DaVinci Resolve to add AAC support; the patch is published and works.
A teacher asked the AI to make a presentation from her pacing calendar. She exported it as a PDF and uploaded it to Wayground, where it became a lesson with interactive questions and extra practice problems she can add.
He runs three products on his own with no marketing spend. Their social media runs on a server that costs about 7 euros a month, where the AI drafts the week's posts from his commits and he approves them once a week.
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.