Rachel D. Gainsbrugh (someone, ~3.5K followers, AI/systems creator) signed up for the AI on Sept 13, 2026, connected her calendar read-only, and typed six standing errand rules once — including a 7:05 AM daily calendar scan that flags overlapping meetings or ones falling inside a flight — then handed it two long-dodged errands (an appointment blocked by a flight, a subscription update).
A Moneywise reviewer testing the AI on money tasks asked it to help buy a used Jeep Wrangler. The AI researched comparable listings and produced a two-page PDF: a side-by-side comparison to show the dealer (four newer Wranglers priced below or near the target, plus a '$3,816-over-good-deal' verdict box) and a one-page cheat sheet (open $19,000, target $20-21k, walk above $22k, with 'if they say / you say' responses) — implying about $4,000 in potential savings.
$3,816
This only partly worked. Worth knowing before you try it.
The studio had the AI and PixelLab make one sample icon and waited for their OK. Then it made the other 24 in the same style, plus the gray locked versions Steam needs, for a demo at Next Fest in October.
Two of his astrophotos, M 27 and the Pleiades, went through a local processing pipeline that his AI agent Orobas built and ran. It stacked the images in Siril, cleaned up the background in GraXpert, and stretched them with logged settings.
A traveller's the AI checked him in for his flight automatically as soon as check-in opened. It told him his boarding group and sent him his boarding pass, with nothing for him to remember or open.
A Japanese soba maker set the AI a standing job: find the key US economic releases itself, register them in Google Calendar, and email a forecast report 30 minutes before each release. On test day the 21:00 report did not exist and no email arrived; asked to investigate itself, the AI checked the AI’s schedule page and answered 'no schedule found', while every retry burned credits (52 for the report work). The report finally appeared at 21:09, good but late, and the full email automation was never achieved on the free tier.
This one went wrong. See what happened before you try it.
His AI rechecks all 31 providers and 89 plans on TokenPlans.dev on a schedule. It writes the changelog and drafts posts like the one announcing it, and every price is dated and linked to its source.
He needed a foreign language voiceover on a video presentation at work. He spent several hours with AI building a process he could trust, then rendered each paragraph as speech and built it into a new audio track for the video.
Figuring out USPS forms is a headache for this poster, especially for international shipping. They told their AI agent what they needed, and it got a shipping label ready to go, leaving them to purchase, print, and drop off the package.
The shop's cost log shows the agents priced Amazon paperbacks on a planned $2.32 print cost when the actual charge was $2.87 — a 55-cent loss on every sale — and burned roughly 20,000 ElevenLabs credits re-recording a single wrong number across three videos, because re-records cost more than the first draft. By day 10 the shop had spent $42.60 with $0 coming in.
$42.6
This only partly worked. Worth knowing before you try it.
A someone testimonial graphic quotes Barron's reviewer Josh Schafer: he uploaded his credit-card statement PDF to the AI, which flagged an Adobe subscription he did not realise he still paid for. Because the AI had no access to his accounts, it walked him through cancelling on Adobe's site himself, saving nearly $25 a month.
Kranda had followed more than 5,000 accounts on X over the years. He handed the cleanup to GrokBot, which worked through every single one over a few days and unfollowed the spam accounts — a backlog job he says he would never have done by hand.
In a compilation of published the AI tests, The Verge's Emma Roth had the AI delete thousands of promotional emails from her Gmail on her laptop; on mobile, the Google sign-in kept glitching, limiting the cleanup.
This only partly worked. Worth knowing before you try it.
He dictated his training to the AI: the exercises, sets, and weights. The AI added a warmup, rest breaks, and a rule for when to add weight, then made it into a page he opens on his phone. It took about 15 minutes and he installed nothing.
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.
A Genworth alternatives analyst built a SharePoint-based credit surveillance agent in an AI app Studio. It reviews more than 1,000 documents across 250-plus fund investments and surfaces trends, risks and upside from completed deep reviews.