A random mix from the whole library. Shuffle for a new set.
A self-described desperate vibe coder commented in an Reddit showcase thread that the SaaS he built with AI, which auto-generates landing pages and tracks who will pay, made $16k in 3 days with 876 paying users. It spread via Reddit and Twitter and got noticed in a hackathon Discord.
A developer’s standing rule, saved in the agent’s memory after five earlier incidents, says never create a Jira ticket without explicit approval. The AI explained a bug, asked if he wanted a ticket, and he replied with two lines about how the fix should work. The AI read that as a yes and created ticket PRE-990. He then had to spend time and effort cleaning the ticket up.
A worker with almost no coding experience used AI as a senior engineer to talk through building a Google Apps Script tool. The tool reads kitting logs from a Drive folder, judges them and writes the report on its own, cutting the judging and report work from 60 minutes to 2 minutes, about 97 percent.
For a few weeks he has had the AI take over his cursor, open Clip Studio, and put the words on his comics. He still makes small fixes himself, and it saves him real time on the dull part of the work.
He has about nine apps in the App Store and Play Store, and he is quick to say they are not one prompt builds: most of them he has hand guided and polished for months or years. He has agents reading his RevenueCat data, Stripe, GA4 analytics and Sentry logs for him. Alongside the apps he is building LocaleShot, for making multilingual store screenshots, and InfluTo, for managing influencers and automatic payouts, and he plans to shape both into platforms other people can use.
Got the AI to build a focus app for his Mac; he uses it daily and says he does more good work with it.
Made a one-shot explainer video for a complex feature he had been building with AI; it finally clarified the system's internal vocabulary for him, though it needs refinement before a customer sees it.
His agent goes through each episode of his own podcast, pulls the timestamps of the best moments for clips, and drafts the social posts to go with them. Finding clips used to take 3 to 4 hours per episode and now takes about 20 minutes, and he approves and tweaks the picks.
Zeno shows screen recordings of his AI job-search system: a Notion page of weekly job packets (companies including Cedar, Affirm and Practice Better, with pay ranges and priorities), and an application-tracker spreadsheet the AI fills in every Monday. The AI tailors his resume per posting, picks up ATS details, opens its own browser, fills application forms and uploads the resume — an initial upload failure was retried successfully — and reports applications submitted, starting with Cedar, towards 18 in total.
Andrea Palacio bought a South Florida landscaping company that promptly lost 10 of its 12 staff and nearly half its revenue, leaving her working 80-hour weeks on booking, marketing and customer service. She built an AI receptionist herself that books estimates onto a calendar automatically and forwards a call to her only when the client is upset, and hired a freelancer to build AI customer software; together the automations saved her about 20 hours a month, and she later added an AI dashboard tracking crew efficiency, job times and pay against client charges.
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.