A random mix from the whole library. Shuffle for a new set.
He wanted a short explainer video on the Browne v. Clarke case for his class, with the beats of the music dispute explained without playing the songs. He gave the AI the links to the case, the AI researched it and press reports, wrote a script he approved, and coded the whole video in Python, building the music from scratch with NumPy and SciPy, with a MiniMax voice.
Austin Evans (verified tech creator, 510K followers) showed his AI 'Lotus' building a full 'Collectibles Tracker' database: The AI pulled over 300 purchase receipts from his Gmail spanning six years and created a spreadsheet for his accountant in about 30 minutes. He noted the AI asks for permission before doing anything big, remembers everything, learns his routine, and proactively offers help — calling it 'legitimately impressive' though 'not perfect.'
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.
A contractor onboarded Instinct through a WhatsApp chat that simply asked what he had been putting off; it now prepares his contracting invoices and drafts his outgoing emails - the two admin jobs that used to pile up behind the actual work.
Orange Spain employees in HR, IT, sales and customer service built more than 1,000 custom the AI Enterprise agents. They automate incident triage, analyze network issues and retrieve corporate knowledge.
His agent runs once a week: it finds companies on Google Maps, finds a real person's contact details on the web, and drafts a personal email for each one, which he approves before it sends. Across 200 companies it produced 20 interviews in four weeks, and he spends about an hour a day on the replies.
Lets agents run deployments for his side projects; they read all the logs and debug fast, and deployments and CI became a breeze versus waiting days for DevOps.
An IT provider managing multiple Microsoft 365 client tenants asks the AI to take a new-user request straight from email, create the user in the right tenant, and email the client back with the details - work his technicians previously did by hand across many tenants.
After his promised promotion turned out not to be budgeted, a laboratory-science professional built a master resume with 20+ bullets per job and bucketed skills, then ran every target posting through AI with a stricter brief than tailoring: trim to one page, polish without inventing anything, tell me whether I am actually qualified, and tell me what kinds of positions I would suit better. The fit verdicts across applications narrowed his search to four categories - project management, training, health and safety, environmental - and from category base resumes he sent just 17 applications in four weeks, landing an environmental role; 77 days from first application to start date.
The AI, asked to create a public messaging web app, created an unauthenticated filedrop and an unauthenticated web chat interface to the AI that let anyone send it files and tell it to execute them.
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.