A random mix from the whole library. Shuffle for a new set.
A lead asked a business owner for a $999 job; his AI answered the lead’s two questions and sent a Stripe payment link, and the lead paid the same day. Speed-to-lead, handled end to end by the bot.
During a migration, a written plan in the session said nothing in the legacy repo gets touched. The plan was re-shown in full mid-session. When the user later asked for a follow-up change, the AI searched the folder it had been working in most recently, which was that repo, found a file that looked right, and edited it there. The user caught it, and the edit was reverted and redone in the correct repo.
The owner of a small technology company called ALAPKO runs AI as the reasoning layer for an internal support worker they call Mabel, with 41 purpose built tools tied into their systems. In a shown run she read a ticket with its customer and asset history, worked out the likely cause, claimed the ticket, replied to the customer with troubleshooting steps, wrote an internal engineering note, and set the ticket status, in about 34 seconds. Business actions go through permission scoped tools and every action lands in an audit log; her normal shell access is read only.
A digital-health CEO reports his businesses have no full-time developers, DevOps, designers, analysts or product manager: scheduled AI agent shifts handle deploys, an agent-built CRM, per-business-line email sorting, meeting scheduling, technical support and publishing news four times a day. The work runs on three $200 AI subscriptions — $600 a month against roughly $38,500 a month at US median pay for the replaced roles.
A GIS user went back to a PostGIS polygon problem he had asked about almost 10 years earlier. Working with AI, he analyzed his old scripts and watched the intermediate geometry steps live in the browser, which pinpointed four exact reasons the original approach failed, and the clean reversed pipeline is now posted as the answer.
A solo non-engineer founder building a salon SaaS commented that the AI handles his coding while an AI chat acts as strategic advisor; that week they shipped 7 PRs and found 12 production bugs in manual testing. The advisor vetoed two feature ideas and made him draft a formal contract change.
Nuno Tavares connected the AI to his HighLevel CRM (172 permissions, demo sub-account), had it audit all 55 workflows and identify gaps, then watched it open a browser and build a missed-call text-back workflow hands-off. The build landed as a draft: missed-call trigger, tag and wait step.
WisePPC has AI agents fix its Amazon listings. An agent reads the live listing and Amazon's listing issues, drafts a corrected title, bullets, description or attributes, and shows the draft. Nothing is submitted until a person says go. After the person approves and Amazon accepts the change, the agent reads the listing again to confirm the new content is really there. Price, images and deleting a listing are kept out of these copy fixes on purpose.
A Creative Cloud user wanted to move his work laptop to Linux, but Adobe makes no Linux versions. With a lot of help from the AI he built a patched version of Wine, the tool that runs Windows programs on Linux, and shared it free. On his laptop, Photoshop, Illustrator, Premiere Pro, Audition and Media Encoder now install and run through his normal paid account.
The AI and then Opus built a tool that mounts app UI in headless Chrome and takes screenshots for help docs; the Opus version was pixel-perfect.
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.