ThursdAI host Alex reported that his AI 'Wilfred', newly flipped to the AI Wonder on his paid plan, found the New York podcast studio he recorded the show from. The AI then emailed Ezra at Virgo Studios with his requirements.
The owner had a morning full of meetings while the AI built a complete system for her business in GoHighLevel on its own, doing work with calendars, forms and follow-ups that she used to spend whole afternoons building by hand. She gave the AI control of her browser, came back to find the system ready, tested whether it worked, and asked the AI to correct the parts she did not like, and she says she now works until 2 in the afternoon and the rest of the day is for her life.
This only partly worked. Worth knowing before you try it.
His quit vaping app Puff Counter passed 10,000 downloads with a 4.1 star rating after he built it in 2024 and never advertised it. Last week the AI rebuilt the app's whole website in one day.
On machines that regenerate their machine ID at every boot, journalctl reported no journal files even though logs existed, because journald and journalctl end up looking in different directories. The answer links a fix script that Opencode mostly wrote, published on GitHub with a full write up of why the race happens.
He runs a five level system where the AI Design makes his Instagram carousels, from a basic prompt up to a full design system with AI generated images and a looping video cover. The first carousel made this way reached 4,500 views with 89 saves.
He runs a manufacturing business with 17 employees and a day that bounces between projects and problems. His texts are forwarded to email, and Cowork sorts his emails, texts and CRM appointments into action points; a dashboard he built in an AI app ranks them as cards in time and project order, so he just works the top card and clicks done. It is learning how long his tasks take and how far away each one sits.
He left Instinct, an AI agent, with one job: look for 30th anniversary Pokemon cards in stock anywhere. It sits in the background and alerts him to places that have stock.
Every CEO Dan Shipper was changing a flight out of San Francisco with his Dot when the agent interrupted its own flight research with a warning: the option might overlap with head of video Randy Counsman's Wednesday morning recording. There was no such recording on Shipper's calendar — the Dot had read a Slack discussion he had never seen, clocked the proposed schedule, and connected it to the flight he was about to pick.
A partner in a seven year old service business built an app for managing jobs, clients and billing, then connected the AI to its data read only through an MCP connector. Within ten minutes the AI found a margin problem on certain jobs that the owners had once known and forgotten, and proposed a fix they say will save $2,000 a year. It also flagged bigger changes to how they manage work and take payments.
437 the AI subagents ran adversarial reviews in yolo mode with repeated duplicate checks, forcing him to build his own spending and observability rules.
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Had the AI build an open-source source control system, benchmarked on a 100k-file monorepo as 12x faster sparse checkout and 82x higher concurrent land throughput than git.
LTM's RAIma super-agent, built in an AI app Studio and embedded in Teams and Microsoft 365 the AI, handles attendance corrections, leave applications, seat booking and hardware requests across more than 87,000 employees. It has resolved over 600,000 queries at roughly 100,000 prompts a month, verifies medical documents for sick-leave approvals, and cut automated campus-onboarding email effort by more than 90%.
Used the AI to solve dozens of annoyances around the house and life and to develop two work apps, one a complete polished interactive web app he says he could not have completed alone.
Opus 5.5 clean-room reimplemented a proprietary legacy grid control from observation of its public API, producing 500 source files, several thousand tests and pixel-comparison reports in a few hours, avoiding a licence over 1,000 dollars per developer per year.
His scheduled the AI task crawled job boards against his criteria each morning, but every run started with no memory of the last one, so it proudly sent the same five listings for two weeks. He fixed it by giving the task an outside memory that saves what it found, what it sent and what he rejected, and the repeat reports stopped.
This only partly worked. Worth knowing before you try it.
Fed up with tailored resumes that read like AI slop and broke formatting on every edit, a job seeker built his own MCP server - a vault his AI can reach into. Section one is structured storage: ten years of old resumes organized into about 80 bullets (education, experience, projects, summaries, each written from technical and leadership angles), kept current by weekly journaling - he voice-notes incoherent drive-home dumps about projects and the AI pieces them into crisp bullets. Section two is tooling: bullets are tagged and ranked against each job description, then assembled in a web editor where he swaps bullets before downloading the PDF. Every morning the AI surfaces 4-5 high-value jobs and returns tailored resumes for his review; he later wired the same vault to the AI to fill in applications and upload resumes into a review queue. Six months: 250 applications, 39 callbacks, 4 offers.
Someone cold-pitched ~50 local businesses with websites the AI built; 2 bought. The website-flipping idea came from the AI itself; he just made the calls.
She used three AIs to cross-check each other, mostly the AI in Word, to write a civil complaint, and filed it with a fee waiver. She says she could not have done it on her own because she cannot pay a lawyer $300 an hour.