Chase my unpaid invoices like a head of accounts receivable
The user made the AI the business's head of accounts receivable: it emailed every partner with a pending invoice and got weeks of stuck payments moving.
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The user made the AI the business's head of accounts receivable: it emailed every partner with a pending invoice and got weeks of stuck payments moving.
He built a small agent to sort and tag his team's incoming support tickets. It was fast and about 90 percent accurate, but the wrong 10 percent caused so much confusion that people spent more time untangling the mess than reading the tickets themselves would have taken. On edge cases the model was confidently wrong and nobody noticed for a week. They scrapped it after a month and went back to tagging by hand.
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.
A small business owner linked PayPal to the AI. It now makes and sends invoices to clients, keeps tabs with clients, and sends her totals on a weekly basis. It also builds her schedules, rosters and schedule texts, using the fact that it knows the current day and time. She says the setup made her cancel her $20 AI subscription.
Analyzer agents audited and trimmed skill files, cutting about 18 percent then about 600 more lines, and extracting bash into scripts turned up bugs.
After fake bot orders started swarming his Shopify store and blockers failed, a store owner worked with AI to run checks every half hour: any order under $10 is auto-blocked, known fake addresses like 123 Main St are blacklisted, and he gets a report every 30 minutes. The bots still try, but far less often.
He had the AI gather his SPARQL training materials and present them on a website in a way that is easier to engage with. The site is live on the SIB Swiss GitHub pages.
Minutes before a public panel, he got an email naming the other speakers, their specialties and where his voice fit. Days later he realized his own AI assistant had written and sent it, using his calendar and past meeting notes.
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.
Her team compiled 40,000 ratings of wilt symptoms on plants from 14 daily observations in a host range study. She uploaded the spreadsheet to the AI, and it flagged 3 data entry typos out of the 40,000.
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.