A random mix from the whole library. Shuffle for a new set.
A Genworth alternatives analyst built a SharePoint-based credit surveillance agent in an AI app Studio. It reviews more than 1,000 documents across 250-plus fund investments and surfaces trends, risks and upside from completed deep reviews.
Eric shipped a phone trade-in weeks earlier and the credit still had not appeared. He handed the chase to Jarvis, which is now tracking the trade-in through to the credit landing, part of the same loose-ends list as a stuck reimbursement claim whose itemization Jarvis also sent in.
The AI built the user's full budget plus two Google Sheets, a personal budget for 2026 and business books for 2026, in under 30 minutes.
He gave the AI a prompt to search 24 months of his Gmail, 2,812 emails, and list the subscriptions he was still paying for. With his approval it cancelled ClassPass at 9,900 yen a month, a saving of 118,800 yen a year, and a confirmation email arrived to prove the cancellation went through.
Parker Pannell asked the AI to save money on subscriptions. It found and canceled $295 in unused subscriptions.
Meta design director Alex Cornell demonstrated live how the AI converted his years of saved Instagram posts into a SkyMall-style shopping catalog — a personal-commerce use case built on the AI’s access to his connected Instagram account.
His finance agent paid invoice 4421 for $14,100 after late fees had raised it from the $12,400 that was approved. The approval was tied to the invoice number, not the amount, and nobody noticed for two weeks.
He says he has zero knowledge of coding. He built full accounting software that reads his invoices and processes them at a 98 percent rate, working with a local AI. It replaced the package that cost him $1,000 every year. He does not know if the software is well coded, but it works, and if it eventually stops working he says he will just pay for more tokens to patch it.
Had the AI install DuckDB and it is now running automated exports into DuckDB for his budgeting.
He has the AI watch his email for purchases, then check the store site for each one during its price match window and alert him when the price has dropped, so he can ask for the difference back. He says he is over $700 saved so far. In an earlier comment in another thread he named Best Buy: The AI monitors his Best Buy purchases for drops inside the 15 day return window, and the total there had passed $400, then $437 from asking for retroactive price matches.
He withdrew from a university program inside the refund deadline but was still charged about $7,000, and months of his own emails went nowhere while the school kept adding charges and warning about collections. The AI logged into his university account, pulled the records showing when he withdrew and what he was enrolled in, found charges for later courses he never took, worked out who at the school could fix it, and sent them the evidence. The balance was removed.
A shipwithmuse.live user asked the AI to call Spectrum and lower their bill. The AI got the monthly bill from $75 to $40.
His real money trading agent kept saving its own notes until its memory file grew from 4,738 to 65,977 characters in four days. One night it retried a failing step 51 times, burned $36.91, and ate 43% of his whole project API spend.
A Dutch man brought his own AI assistant, Eva, running on the AI, into a live call with his provider Ziggo. Eva had compared a rival offer against his contract, and spoke during the call when he asked her a question. Inside 30 minutes he had a renewed 24 month contract that cuts his total bill by 1,250 euros.
A man gave the AI strict tag research tasks and had it work through the whole ticker list again and again, searching and comparing XBRL tags in SEC filings. The pipeline now pulls 10-K and 10-Q filings for more than 600 companies, maps tags onto about 35 financial concepts, and produces cleaned data. Doing 3 tickers by hand had taken him about 3 weeks and still gave wrong data.
A reseller describes his valuation stack in a thread mocking casual the AI pricing: the AI identifies an item, its condition and model numbers; that feeds a sold-comps subscription and his internal database through Python to build a comp list; then a second classifier AI judges how closely each comp actually matches before the system takes the low end of the surviving comps and calls buy, watch or pass. He is blunt that naive copy-paste pricing pulls stale comps - the pipeline exists to fix exactly that.
Colombian consultant Darío Palacio Isaza sent his Instinct agent to find a product with exact specs across online stores. Mercado Libre's security check blocked the agent repeatedly, so the purchase went to Éxito.com, a store he had never used, because its product page was machine-readable.
The carousel shows a chat with 'Taylor' (branded the AI): the agent reported online chat wasn't available to existing GoNetSpeed customers, supplied the phone number and a negotiation script citing Spectrum's $60/mo offer. When pressed, it completed a browser task and submitted the contact form with the same pitch, confirming a representative would reply.
He asked his AI for a pet hair robot vacuum under $500. Instead of a long written answer, it sent four cards he could compare, each with a price, a photo, battery life and a source.
Konik's dishwasher died mid-dinner-party cleanup. She messaged the AI while her husband and a guest stared at circuit breakers; it researched options, dug up obscure pro-forum discussions, and priced KitchenAid vs Bosch across local stores including installation.
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.