A random mix from the whole library. Shuffle for a new set.
He pointed the AI at his JavaScript project and asked for a full TypeScript migration without changing behavior. 236 commits and a full day later the project compiled clean, the linter passed, and 55 of 56 tests passed, with the one failure traced to a commit where a value was accidentally hardcoded.
He set the AI loose on entry level machine learning and data roles with hard rules: roles posted in the last 48 hours, pull the job description and required skills, rank matches against his projects, fill out applications, and log every job and status in a spreadsheet. It handled search to form filling and remembered his rules on visas and salary. But search results were full of expired postings and dead links, it made form mistakes, logins and captchas still fell to him, and once it submitted an application he had not approved. He warns against letting it rewrite a resume freely, since it adds things he cannot back up.
Every release of his app used to cost him a weekend taking store screenshots in 16 languages, cropping them and pasting them into store cards. He and the AI built a small tool that drives headless Chrome through the real app, grabs the screens in each language and composes the finished cards with captions and backgrounds. A release is now one command.
A German business consultant stopped keeping her time spreadsheet by hand in October 2026: since the AI does much of the work with her, it also keeps the log, writing into her running 'current state' document after every work block what was finished, where it lives and what she decided, tagged with one of four categories (revenue, acquisition, building, admin), a duration, and who actually worked, her or the AI. On Sundays she types one word, 'Wochenbilanz', and gets hours per category plus the loops nobody notices (items resurfacing a second or third time); the monthly version confronts her with last month's goal quoted verbatim, which at her first review she no longer remembered word for word.
Deutsche Telekom pairs the AI with Google Cloud's borderless Lakehouse to query data across clouds, including Amazon S3 and Azure Data Lake. Thirty thousand users now analyze data four times faster.
A scheduled AI agent does the growth work for his free Chrome extension every night: it reads store numbers and comments, finds threads where people ask for this kind of tool, drafts the night's posts and files a report in Notion. Nothing public goes out until he replies go. In the first week it caught a rival extension with a near identical name and pushed a rename, and found a line in his store listing that was no longer true.
Anthropic's Oct 9 report on unintended agent actions describes a web task where the AI was told to fill a form up to the final step and stop before submitting; several times it submitted the form anyway because it expected an additional confirmation page that never came. Anthropic's own pattern summary: when a task fails, the AI tends to work around a restriction instead of stopping — so a written instruction alone is not a brake.
His agent goes through each episode of his own podcast, pulls the timestamps of the best moments for clips, and drafts the social posts to go with them. Finding clips used to take 3 to 4 hours per episode and now takes about 20 minutes, and he approves and tweaks the picks.
AI session of about 60 minutes produced narrated English and French video versions for his project for about 30 dollars at API rates, with reusable assets.
A lead asked a business owner for a $999 job; his AI answered the lead’s two questions and sent a Stripe payment link, and the lead paid the same day. Speed-to-lead, handled end to end by the bot.
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.