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 hates filing quarterly sales tax, so now the AI gets the data, works out what his business owes, and fills in the state website. He checks it and pushes the final button himself.
A Japanese creator in vocational training had the AI analyze her past articles' tone, draft two note posts and build a review board with cover-image briefs; both posts reached scheduled publication with only her OK. The one step the AI could never complete was uploading the cover image, because the OS file-picker dialog is unreachable to it, so that step stays manual every time.
Before he writes, the AI opens a blank page in Obsidian and pins it, splits the window into two panes, and puts his notes and research in the second pane. He says the small setup steps are done for him, so he can start writing right away.
A marketing-business owner who is not a developer used AI for strategy, planning and technical thinking and the AI to build, with himself making decisions and testing in the middle. The outputs were a real business website built and launched (his SearchyFound business), a schema generator and other tools, and a lead engine for finding and evaluating potential customers; the video also shows failures, including Google Analytics not actually tracking.
An audit partner runs his accounting firm on an agent platform wired to its own live data. In the session the agent pulls the credentials from a vault, logs into the KWSP i-Akaun portal, and submits the EPF contribution, with the partner reviewing the figures before payment.
He runs Svippit, a small shop platform for creators. The AI watches it for errors and works out fixes, reads customer emails and drafts replies he checks before sending, and finds receipts in his email and matches them to payments.
A solo founder told his AI project-manager bot to ship one secret feature to PromptBase at 4am and deploy it while he slept, with only the rule that it had to benefit the site. Drawing on support emails, it built and deployed an alert that warns users before their account times out from too many declined submissions, and it worked.
In their apprenticeship, trainees had to log their on the job hours on a paper form and email or text it to the office manager, who then typed every entry into a spreadsheet by hand. He built an app so apprentices can submit their hours directly. Now the office manager just has to make sure everyone submits on time each month. If someone still wants to turn in a paper copy, she can enter it through her admin login, and the app does all the math for her.
On its own Jacksonville headquarters buildout, Haskell posted QR codes around the jobsite so any worker or trade partner can ask Procore's AI questions against the project's specs, submittals and drawings and get answers linked to the source document, saving an estimated 10 minutes per inquiry across hundreds of daily workers. Its assistant project managers also use a custom-templated agent that compares each trade partner's submittal against the design specs and lays the variances out in a side-by-side table, reclaiming over an hour per submittal review.
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.