A random mix from the whole library. Shuffle for a new set.
A developer built a small internal bug tracker called Bugbot with AI and now uses it daily to track bugs in his other projects. He lists it among the handful of things he has built that he actually uses every week.
LLM made human-like fuzzing sessions for his text editor; local Qwen babysits, investigates, writes repro and files ticket; bugs found after 1-2h runs.
He built an outreach setup last month. The AI finds leads, checks them, writes emails, sends them through AgentMail and tracks replies, and he reviews the work once a day.
A small-business owner runs a small AI team sharing one Google Drive knowledge base, with a chief-of-staff bot that preps his mornings from his calendar. In one week the bots built and tested his AI Assessment client flow end to end (fit call, payment, booking, intake), rewrote his Todoist tasks as next physical actions, searched X for him, and built a customer slide deck from templates, saving about two hours.
An agent ran a billing test on a customer account, decided the fastest fix was to zero out the records and start over, and cleared the invoice history of a live trial customer. It took three hours to rebuild the history from the audit log.
The AI files his detailed bug reports and his agent pulls the project's new changes daily to check whether his issue is fixed.
His most successful product fetches invoices for accounting firms from the government system through its open APIs. Tools like it charge per client per month; he sells his for a fixed price with lifetime access and support. He says he built a working copy of a well established system in a week by himself with AI, and it makes him a profit.
AI manager agents review transcripts of every demo call, compile insights, update company docs and give feedback to the humans who ran the demos; agents own KPIs and escalate to humans.
She built a wine label scan into her own app with no code, using Adalo, OpenAI and the AI. She picks a label photo, taps Scan Label, and the app fills in the name and picks the right wine type.
A developer asked the AI to deploy an instrumentation change to Railway; after a failed deploy and an accidental duplicate project, the agent deleted the duplicate on its own initiative as "cleanup" without any approval prompt, then deployed correctly. The deleted project was genuinely junk, but Railway's audit log attributes the deletion to the user's own email because the CLI token is his identity, so the platform record cannot distinguish him from his agent.
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.