A random mix from the whole library. Shuffle for a new set.
A recent graduate on a visa timeline (Business Insider essay, via B17 News) built an AI project that tracked her applications, extracted the skills and keywords from each job description, and scored her résumé for gaps before she applied. The dashboard she had the AI build shows the funnel that ended in a job: 186 applications, 44 cold outreaches, 19 interviews, six take-home assignments, three final rounds and one offer.
Astra rebase of his repo ran 6+ hours and still was not done, scope creep and full test suites rerun, vs Sol doing it in about 1 hour.
Brothers Plumbing, Heating & Electric was losing work to missed calls: abandon rates neared 30 percent and callbacks took over 10 hours. ServiceTitan's AI Virtual Agent now answers in seconds and books jobs around the company's real capacity, service zones, technician skill sets and job types; the abandon rate fell to 5 percent, more than 600 jobs have been booked by the agent, and the company attributes $1.33 million in revenue to it.
A system admin moved his workplace off an old domain that dated back to the NT4 days and onto a new one. Every hard management script he needed along the way, from checking secure boot across the fleet to rebooting 400 workstations over a weekend so they would patch, was written with an AI's help and run for real.
The owner asked ARGUS in Telegram to buy the cheapest eSIM for Turkey, approved with a yes, and got the QR code in the chat seconds later for 0.31 USDC. Thirty-four minutes later he asked for a refund because he had not installed it, approved again, and the 0.31 USDC came back after the seller checked the eSIM was unused.
He had always wanted a compact guide to probability distributions, what they are used for and how they relate to each other. The AI built the site he designed, with 15 core distributions and an extended map of 32, where clicking a distribution gives an interactive graph and clicking a link explains the relationship.
A user asked the AI to build a multi-agent outreach pipeline. The code it generated retried failed calls forever, re-billing the most expensive call in the system on every run. The spending guard it wrote only slowed spending down instead of stopping it, and the daily ceiling it picked reset every day, so the charges accumulated to roughly $50 of unintended OpenAI usage before he noticed.
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 Persian-language reel demonstrated the AI managing emails and sending auto-replies, handling Instagram direct messages and comments, generating full page analytics with growth charts, and producing weekly content plans — then creating a custom avatar and a product video for a QCY SP2 Bluetooth speaker. It connected to Gmail and Instagram.
His books arrived late and he returned them, but Amazon said some were missing and tried to charge him $152.35 again. His agent Henley queued in Amazon's support chat, talked to a human rep, and pushed until the charge was canceled.
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.