A random mix from the whole library. Shuffle for a new set.
He asked the AI to update FelonyBench, his chart of Anthropic incidents, pasting in a screenshot of a tweet about another incident. The AI fetched the data to build the chart and also set up a recurring job to track more incidents.
Agency owner Rui Fu (someone, 253K followers) demonstrates the daily system he shows for the AI: an 8 AM scan of the last 24 hours of Instagram DMs, categorised into brand partnerships, collaboration requests, fan messages and spam so he wakes up to only the important ones. The tutorial also shows an auto-reply rule for guide inquiries and offers his prompt guide in exchange for comments.
The developer set a scheduled job in plain words: every weekday at 8:30, send events from all calendars plus emails needing a reply, in five lines or fewer. The first run arrived at 8:44 with an apology for the delay, covered all 16 calendars, removed duplicate events and listed private events by time only.
Eleanor Konik had the AI and AI team up on dashboards for local nonprofits. The AI did the early research and dug up grant chances the groups had not seen, like a group that pays for field trips to battlefields, a free textbooks program for private schools, and creative arts projects, and the lists were put behind a password for her friends to use.
The author reports the AI reduced his unread Gmail from more than 65,000 messages to about 700.
Ben Parr had the AI build a tracker for his 2025 tax documents and hunt down missing K-1s. The agent organized the paperwork and chased the missing forms.
She was using AI to archive legislative material when it flagged a serious vulnerability in a state legislature's website. She had to stop and report it.
His local school division released the raw answers to a touchy redistricting survey as one PDF of more than 3,000 pages, which nobody could realistically read. He used AI to write scripts that pulled the answers out and built a public web page where people can search the responses and filter them by keyword and by school.
A man was spending 90 minutes a day on email. An AI agent was set up to read, sort and draft replies to every routine message. He now approves the drafts in 8 minutes, saving 82 minutes a day.
Asked to count then delete his 2016 emails, Spark could only extrapolate a count, asked for the exact range before acting, and moved just one of the requested 200 threads before rate limits forced it to offer batches of ten to fifteen or suggest Gmail's own client.
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.