A random mix from the whole library. Shuffle for a new set.
A video summary was made for others to use in their teaching. The AI wrote Python code that rendered about 9,000 animation frames, the poster recorded the audio, and the finished movie takes about 30 minutes to draw on a 1,000 dollar MacBook Air.
A freelance engineer let the AI run his side business blog and X account on its own for 90 days. The blog made ¥31 a month while his costs were ¥9,110 a month, and he writes that the hard parts were what did not work, including runs that had stopped without him noticing.
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.
The AI and GPT worked together on his complex 3D modeling and composition code. In the morning a run took 769 seconds on average. By the afternoon it took 58.6 seconds, 92 percent faster.
Boston demolition startup Circa built Waste-Less Vision with AI: customers submit photos or video of a space, the system identifies materials and prepares a preliminary estimate of disposal costs and labor hours for human review. A 15-minute basement video that once had to be watched fully now becomes a line item automatically.
John Voorhees has his Dot, Puck, coordinate his work: he spins large projects off into AI threads and lets the Dot manage them, alongside setting up tasks, checking email and doing light research. He says the delegation has worked reliably the couple of times he has used it.
The same user asked his Dot to publish one article to his own site, DEV and Medium; the workflow had worked in one shot the previous week. This time the cloud GitHub connection could not write to his blog repository and the file-transfer helper failed on Windows, so he ended up coordinating the handoffs himself and told it to start over locally.
Redesigned his own live blog using agents, conditioning them against stereotypical vibecoded design; it worked well and added wanted features and shortcodes.
Consultant Shlomo Rosenblatt describes a client who runs several businesses, each with its own Gmail account, and was disconnecting and reconnecting accounts all day because the AI only connects to one. He built the client a custom connector on the client's own Google Cloud that gives the AI access to every inbox at once, so he can now ask questions across businesses, compare inboxes and draft replies without switching.
He runs about 15 apps and sites and could not keep track of what needed doing. He connected the AI to his app through MCP, and the AI now creates tasks and subtasks, writes notes, and shows him what is needed by priority and due date.
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.