A random mix from the whole library. Shuffle for a new set.
Ethan Mollick writes that the AI noticed an airline credit of his was about to expire and, when he asked, contacted American Airlines to request an extension — an example of agents catching deadlines their owners miss.
His mortgage servicer first said his loan could not be assumed. He used AI to research why the loan did qualify, draft the letters and request packages with the supporting evidence, and find the right government complaint portals when the lender kept stalling, and the assumption went through instead of a refinance at current rates.
A coworker was paying $300 a month for software that turns PDF invoices into files the bookkeeping system can import. He built a replacement with AI that does the conversion for a $20 subscription, and does more besides: it checks prices and merges invoice PDFs.
She kept forgetting to log her own progress, and failing. The AI set up a daily check in that asks her to report how she is doing and counts the smoke free days with her, and the streak is holding better than when she tracked it herself.
Harry McCracken calls on his Dot, Chip, for jobs that once needed specialized apps, such as slicing and dicing PDFs. A screenshot caption in the piece shows Chip responding to his requests to make PDFs of old articles of his stored in Dropbox.
After three weeks with OpenAI Dots in France, a user says it reads his email in read only mode. When OVHcloud announced data center work, Dots matched the notice against his own servers, told him which could be hit and told him to check his backups. It also warns him ahead of renewals like Amazon Prime.
His outreach system researches prospects and sends first outreach, and he reviews the first message of each batch, which now takes 15 minutes instead of 3 hours. Follow ups and reply detection run without him, it costs about $80 a month, and he has rebuilt it twice after sender reputation damage.
Shriya Nevatia had the AI build a personal fashion app from her measurements, photos, favourite stores and budget ranges. The app picks a hero item, builds outfits around it, and keeps a saved list.
He runs recruiting for an investment firm across 30 open roles spread over five applicant systems. His AI cron runs at 9am, reads the open roles, searches people through data services, checks Gmail so nobody gets emailed twice, and writes new candidates into the right system with its reasoning attached. In about six weeks it surfaced 40 good candidates and the firm made 2 offers.
A Magic player built a collection manager with AI and needed every card sorted by what it does in a deck, not by the words on it. The AI ran his whole collection, 2,527 different cards, through a classifier that gave each card a fit score for 61 roles like ramp and card advantage. It took minutes and cost about 22 cents, and the AI wrote the method into a reusable skill for next time.