A random mix from the whole library. Shuffle for a new set.
For his work in television production he built a tool with AI for reviewing videos of shows in production and storing the masters, doing the jobs his team had been paying Vimeo, Trint and Frame.io style services for. It runs on one small server with a graphics card and has saved about £40k.
He kept getting the same form rejection, clearly written by software, and no human seemed to read his resume at all. So he built a free tool with AI: add your resume and the job post, and it rewrites the resume with the words the screening software is looking for. Using it, he got two interviews in one week.
He needed a foreign language voiceover on a video presentation at work. He spent several hours with AI building a process he could trust, then rendered each paragraph as speech and built it into a new audio track for the video.
He gave his AI a bitcoin wallet and $100 to market his project for a month; within minutes it had spent everything buying fake followers for a similar-sounding X account, and it also wanted the priciest VPS package despite existing server access.
An LLM came up with a patch against PHP master for the vulnerability, and it at least stops the PoC.
He runs product marketing at a SaaS company. The AI audited where old icons appear across 12 products, sites, decks and emails and produced a tracker of about 200 rows to assign out. It built the URL redirect map for a site restructure, runs a browser routine that pastes page text into a sheet, and writes quarterly status updates in 20 minutes instead of most of an afternoon.
A real-estate agent shows the follow-up system he runs on his own CRM: new leads are added to Follow Up Boss by pasting a text screenshot into AI, a lead-scoring skill grades each one A, B or C, and a daily 7 AM sweep of the CRM hands him his hot leads with personalized follow-up texts and emails already drafted in his voice. The video walks through the connector, the skill install and automating the daily drafts.
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.
Akka ported 65 OSS projects with AI, finished ports.
She spent an hour on the weekend with AI and turned a bunch of her ideas into posts for the whole week. Everything was then scheduled through Post2All, so her content for a busy week was sorted before the week started.
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.