A random mix from the whole library. Shuffle for a new set.
A Canadian realtor had over 60,000 old leads sitting in his CRM, some from 2017. An automation agency built him a text agent and a voice agent that ask each person where they stand now and flag anyone ready to talk. Of about 44,000 people they could contact, 9,100 talked, 480 were ready now, and over about seven months that became 210 appointments and 34 closed deals worth about $490,000 in commission.
He runs OpenFree, a site that collects open source projects. The AI scans X every day for new projects, filters them, and submits them to his site backend, where a Cloudflare workflow parses each one and sends it to him to approve before it goes live.
Slack fix-it button tells the AI to fix an issue in his app, run tests, UI test with computer use, and deploy it.
His frontend launch scripts were failing with nothing in the logs. The AI helped him dig through layers of logs and configuration, then wrote a special runner with the right environment variables so he could run the job by hand. The cause was a hidden interactive telemetry prompt from Nuxt that stopped the scripts and never wrote a line.
Builder Omar Villalobos says a client was losing 70% of its quotes because everything lived in scattered WhatsApp chats, so he built three parts with AI: a WhatsApp-linked form that auto-updates a CRM instead of manual copying, a pipeline dashboard showing $1.28M at stake with follow-ups due and won deals, and an ROI calculator showing a client their investment, monthly gain and payback. No recovery of the lost quotes is claimed yet.
Frontier model reviewed his KiCad project, queried the AI vision for datasheet data, ran ngspice sims; $1-2 tokens saved $70-80 of bugged PCBs.
A man bought a used piece of industrial machinery and the $1,500 control software did not come with it. With no coding experience at all, he asked the AI on the web to build a control app, and in under an hour he had a working app packaged as a .deb file for Linux. It cost him nothing because he used his brother's AI subscription.
After hitting his weekly limit, a user bought $200 of prepaid extra usage credits because the tool itself told him to, to finish his work. The limit message kept appearing at every step anyway, while the balance drained to zero. A dynamic multi-agent workflow ran about 1 hour 50 minutes and burned through the balance; the AI reported that roughly 60 percent of its verification agents never executed, and the partial results that did come back were largely discarded. The $200 bought an incomplete verification.
The AI added programmatic PowerPoint screenshot support to his markdown-pptx tool in under 5 minutes.
Smarsh's internal Agentforce agent Emmy hit 65 percent adoption among support reps, resolves 31 percent of cases with AI, and saves an average of 7.5 hours per case.
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.