Four the AI skills turn one raw podcast recording into finished pieces
He drops one raw podcast recording into AI. Four skills turn it into an mp3, a transcript, a description on his clipboard, and a pull request on spring.io, with no manual steps.
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He drops one raw podcast recording into AI. Four skills turn it into an mp3, a transcript, a description on his clipboard, and a pull request on spring.io, with no manual steps.
A call center replaced its press a number menu with a system that listens to what the caller says in the first 10 seconds and routes the call. Wrong transfers fell by almost 40%.
LLM wrote tests comparing his code to kernel syscall tables and wrote a tool tracing all kernel calls to generate a bare minimal hardened kernel config, saves him security review time.
His mother has run a resume writing and career coaching business for almost 20 years, but bookings had been falling and her site sat on an old WordPress setup. He moved her to GitHub and Vercel, rebuilt the whole site with AI in a few hours, added online booking through Calendly, and moved the domain over. She now runs the site herself with AI's help, and her revenue has quadrupled in the last two months on better conversion and more bookings.
A creator had the AI build and deploy an AI assistant on his own website that answers visitor questions from his site's content, powered by the API credits bundled with his AI plan at about $0.0006 per question. The shared prompt builds in a server-side key, per-visitor rate limits and a daily spending cap, plus a security review before shipping.
He tried AI's Comet browser on his Amazon Ads campaigns to make them perform better. He says it raised his ROAS by 120%.
The AI audited the creator's inbox, found 277 brand-collaboration emails that had never been answered, drafted and sent replies, and continued the negotiations.
He runs recruiting for an investment firm across 30 open roles spread over five applicant systems. His AI cron runs at 9am, reads the open roles, searches people through data services, checks Gmail so nobody gets emailed twice, and writes new candidates into the right system with its reasoning attached. In about six weeks it surfaced 40 good candidates and the firm made 2 offers.
Said asked the AI to find every locksmith in a city for Partexia and pull emails; he sent 15 personalized outreaches and one business replied asking for a call.
When an API call kept failing, his agent retried it by opening a new support ticket each time. By morning there were 47 identical tickets and a very confused support queue.
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.