A random mix from the whole library. Shuffle for a new set.
A solo founder runs PromptBase on a small AI team living on a Linux server: a support bot answers customer email from his Gmail, an engineer bot writes code, a security bot watches Cloudflare and server logs - and the bots have fixed a customer bug together without him, while he managed them from a phone on a five-hour hike in Wales.
For his wife's business, the AI reads hundreds of emails a day and prints her a short brief of what matters, files the rest, updates her website, runs her Square and her Google Ads, and prints a weekly report every Saturday night. It caught a licence expiry buried in the email, stays inside budget, and replaced a person who charged $600 a month to run the ads, with better results.
Jon Udell recorded himself doing a final audio pass in Bram Studio, then had the AI draft a screencast from the capture. The AI used FFmpeg, Apple's Vision framework, the Swift compiler and Bram's timed log to make a tightly edited two minute video that picks out and labels each use of FFmpeg.
In the same post he describes tools he built for his own work: invoicing and proposals. Writing a proposal used to take a few hours of his day, enough that he sometimes did not bid on a job at all and left money on the table. Now a proposal takes about five minutes, more of them go out the door, and more work is coming in as a result.
His newsletter, close to 9,000 subscribers, is run day to day by four AI agents with set roles: one oversees, one edits and manages, one builds, one dispatches the work. He still approves anything that goes out, and the agents refresh their own context from checkpoints instead of slowly forgetting across days.
A man reimplemented his GIS science code from Python into Rust using LLMs, with a hard test: identical inputs and outputs at 10,000 points. Where the rewrite differed, the agent researched other implementations and tried again. The result runs 10 to 70 times faster with far less memory, and the service now does the work essentially instantly.
Opus built a clean side copy of his project to work around uncommitted changes, linking folders back into the real project. Deleting the side copy deleted through the links into data that existed nowhere else. He restored the folder from a Windows backup made the day before, and had the agent write a hard rule into his instructions: never work around uncommitted changes, and remove links one by one before deleting anything.
A Korean creator set up the AI to find possible clients on its own. Every Monday at 7 in the morning it does the research, finds each contact person's job title and work email, and puts the results in a Google Sheets spreadsheet.
A network engineer with two school-age kids built ProgressCove with AI after no task app fit his family's project tracking. It is released on Android, iOS, and web with a Home Assistant integration, family accounts, and a paid tier funding its upkeep.
WisePPC runs a scheduled the AI check over its own Amazon catalog. The bot reads listing content and listing issues and compares them with the previous run. If nothing changed, it says nothing at all. If a new listing issue shows up or a title was edited, it reports what changed and where. It only reads, and it asks before it changes anything.
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.