A random mix from the whole library. Shuffle for a new set.
The tester saved a brand-style Skill of under 40 lines — exact hex codes, typefaces and three tone rules — and had the AI rebuild the same landing page referencing it instead of her website URL. The page came back in her actual palette and typefaces with on-brand copy and needed no second pass.
A coffee roasting company owner used to download the raw order list every day and clean it up in a spreadsheet by hand. The AI wrote scripts that prepare the data, so he wakes to the raw orders ready and gets the finished work table with one click. It also speaks a notice to his staff when a top priority order comes in.
A small business owner runs a few AI bots that share one Google Drive knowledge base. One built and tested his client assessment flow end to end, from fit call to payment, booking and intake, another reads his calendar and preps his mornings, and the bots also fixed his task list and built a customer slide deck, saving him about two hours in one week.
He could not find any service that tracks new plays by his 30 or so favorite playwrights. Now the AI checks and tells him every week.
He exported 10 hours of his AI usage (8,915 model calls, about 1.15 billion tokens) and had the bot study it. Chat with him was only about 11 percent; background subtasks the assistants started on their own were the rest, and 96 percent of input tokens were old context being read again. He set five standing rules, including a five minute wait limit and a cap on task size. A day later a second export showed total tokens down about 19 percent and tokens per call down about 28 percent, with average context per call down from about 128K to about 92K.
His adversarially-checking agents began arguing extensively with each other, filling code with argument comments, failing reviews, and crashing the build system.
Author educator Christopher Kokoski set up a test the AI with a series bible in Google Drive for a mystery series (hero Rudy Relish: seven hard rules including a bad left knee, never touches a gun, no ketchup on the cart). He added the first three chapters of book four and had the AI check each against the bible and all other pages, on a daily scheduled check. Chapters 1-2 were clean; in chapter 3 the AI caught every one of several mistakes he had planted, including one he considered an unfair plant. (Test manuscript on a fresh account, run for a week.)
He let the AI UltraCode run overnight on their triggered ad server. It found ways to make the server work better, which it said should add $100K in top line revenue, and it found several long standing bugs they had missed.
BananaGroup now runs its Medicare Supplement sales on its own app, with prospects, quotes, enrollment alerts and the sales pipeline in one place, built in a couple of days. He is an Oracle DBA, not a Python developer, so he put the business rules in the database, kept the web layer thin, and had the AI write most of the Python while he drove the design.
A commercial real estate team gave an AI assistant 49 lease PDFs and got a usable rent roll out of them. The case opens a training session on handing real estate busywork to connected AI tools.
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.