He is job hunting in tech, aiming at startups and big tech. He gave the AI a list of up to 100 target companies, target roles, and his filters: salary range, posted in the last month, locations, industries to avoid, and sub rules like roles that do not need past experience in that exact title. Twice a week the AI sweeps the list and brings back matches. He reviews each role, tells it which were bad and why, or that he applied, and it sharpens the filters for the next run. He says the matches are strong and far quicker than scrolling LinkedIn Jobs. It cannot submit applications, and no interview has landed yet in the post.
Fable and the AI vibecoded a library improving text extraction from legal PDFs; it works pretty well but is stalled at about 80 percent on design and heuristics, with the models churning.
This only partly worked. Worth knowing before you try it.
The AI in Antigravity attached GDB to the GPU driver, reverse-engineered the kernel queue ioctl interface, and authored an LD_PRELOAD shim that got ROCm llama.cpp working on his Strix Halo.
He noticed people in his area were hesitant about AI and decided to start an AI consulting business. He built it from the ground up with AI: the website, the LLC, the EIN, the business bank account, marketing material, business cards, posters and a marketing strategy. On the day of the post he had his first customer, and was lining up free consultations for smaller businesses in town.
Ticket-driven agent setup: he adds a ticket, it makes a mockup and writeup, he approves, and it spins up a temporary webserver and iOS and Android builds to verify; review and testing loops run automatically.
A developer tasked the AI with fixing programs for analyzing historical options data, with one condition: change only duplicates and leave originals untouched. While tidying the test copy, the agent failed to recognize shortcut folders pointing at the main project and in under two minutes deleted 48,218 files along with their version history, then messaged the owner that it had broken something.
This one went wrong. See what happened before you try it.
He built a client performance dashboard in a day with AI, pulling four APIs into one live page for a natural stone company that takes enquiries online but gets paid weeks later, offline. He labelled the big number enquiry value, not revenue, and changed the page the same day after the client saw it.
A client needed a small design job that would have taken him hours. He sent the AI a screenshot and a few ideas he liked, asked for a print-ready Illustrator file, and the client approved the first attempt.
Austin Evans (verified tech creator, 510K followers) showed his AI 'Lotus' building a full 'Collectibles Tracker' database: The AI pulled over 300 purchase receipts from his Gmail spanning six years and created a spreadsheet for his accountant in about 30 minutes. He noted the AI asks for permission before doing anything big, remembers everything, learns his routine, and proactively offers help — calling it 'legitimately impressive' though 'not perfect.'