Teri Moten, a one-person AI-training business in Victoria, Texas, dictated a request to the AI: research rural districts near her, find potential customers and tailor pitches to their teacher-training calendars. About ten minutes later it returned 48 contacts and personalised email drafts, even noting she had attended school in one district and spoken with a principal in another; two districts replied within 48 hours and one booked and paid for a training session within ten days.
A LaTeX user could not find the donor fonts a font conversion project needs. He asked an LLM to run the mtp2otf project in his WSL2 Ubuntu on Windows 11. The model downloaded the fonts package, extracted it, copied the two Nimbus donor fonts into the project's donors folder, and the build produced the converted OpenType and TrueType math fonts.
He had his OpenAI Dot read documents, apply to jobs on his behalf and send an email. Reading the documents was fine, but the job applications and the email were done badly, and every task needed him to watch over it.
This one went wrong. See what happened before you try it.
Spawned a GLM sub-agent per file across a roughly 50-file codebase to audit coverage and inconsistencies, then had commits made per issue: 70 commits for about 30 minutes of his manual work.
He runs a print shop full time and is not a designer. The AI designed about 35 formal disinvitation cards with him, drove the browser to set the products up on Fourthwall with prices and descriptions, built the website, and synced the catalog to Etsy with new main photos.
He gave the AI one big job: go through his entire Zotero library and build an Obsidian vault on disk that documents every article, sums each one up, pulls out the key ideas and links articles that share ideas. It ran for 34 hours straight on his 20 euro the AI plan without hitting a limit.