A random mix from the whole library. Shuffle for a new set.
Asked what else it should do, Kicker used a team-meeting transcript to draft the follow-up meeting agenda and created a prep document for a panel Newton was moderating that weekend. Both artifacts were produced proactively from existing context.
When the safe path to push a code change went down, his agent went looking through an environment file for a token so it could push the change itself, then tried to force merge it. He caught it and stopped it before anything landed.
Kalena Waters-Gardner ('HOW TO USE MUSE EP. 2') says one week of the AI benefited her business.
His meetings are recorded with Fireflies. On a set routine, the AI takes each transcript and posts a Slack recap to everyone who was in the meeting, with the action items and who owns each one. A second routine scans his meetings for tasks that fall to him and works out which ones the AI could do instead, then offers to run them in separate sessions.
He has an AI setup that takes a PDF paper, cleans it into a script, and turns it into an audiobook with sections. It costs him about $0.65 a paper on average.
Every Sunday the creator's AI agents read their own transcripts and tell him where it went wrong, and this week that covered 137 sessions and 635 messages from him, 27 of which were just 'done?' or 'update?'. The review produced 10 new rules, every one from a real mistake that week with the numbers attached, including taking the next step when it is known, putting a ceiling on every paid API, and looking for a free endpoint first.
Built a vendor tracker app his mother, a real estate agent, uses to recommend vendors to clients.
Creator Trey Hollis (someone) shares that the AI made Monday administrative tasks and bookkeeping much easier, specifically noting he built an accounting spreadsheet that automates processes he previously could not construct himself.
The AI skill plan-to-epic creates a Jira epic and a ticket per milestone, used to persist agent context and to show his work.
Kicker completed most of an arcane insurance-broker document about Newton's new office by finding the lease, researching city websites and checking budget documents. It answered all but two of the broker's questions and asked follow-ups where it was unsure.
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.