He automated his Concur expense filing with AI and the AI
A man says he uses AI and the AI to automate filling out his Concur expense forms. The filing manages payment for the AI and the AI itself.
A random mix from the whole library. Shuffle for a new set.
A man says he uses AI and the AI to automate filling out his Concur expense forms. The filing manages payment for the AI and the AI itself.
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.
A man with no coding experience used AI to generate a VBA script in Excel. The script fixed a manual data entry gap at his work and took the risk of typos and misreads out of the job.
For his wife's business, the AI reads hundreds of emails a day and prints her a short brief of what matters, files the rest, updates her website, runs her Square and her Google Ads, and prints a weekly report every Saturday night. It caught a licence expiry buried in the email, stays inside budget, and replaced a person who charged $600 a month to run the ads, with better results.
Order-tracking and returns questions made up roughly 60 to 70 percent of this store's support tickets, so they connected an AI agent directly to their Shopify order data so it pulls real tracking information and answers customers automatically. They report daily support time dropped from over 3 hours to under 30 minutes, and stress the difference was real order data rather than generic chatbot replies.
The AI modernized a 22-year-old legacy system, updating dependencies, auditing security and adding features, raising test coverage from about 65 percent to about 80 percent.
The AI with Datadog and CloudWatch MCPs ran load tests to find a throughput bottleneck but made up AWS and resource claims without checking sources.
Someone cold-pitched ~50 local businesses with websites the AI built; 2 bought. The website-flipping idea came from the AI itself; he just made the calls.
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.
Answering a how are you making money thread, he says a piece of business software he used does one thing and does it badly. With the AI’s help he built a piece of software that does the same thing better, with the features he always wanted. It took a lot of bug testing and had many errors at first, but it was done in two weeks. His version costs him $50 a year in server costs instead of $150 a month, saving about $1,750 a year.
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.