A random mix from the whole library. Shuffle for a new set.
His team has to produce a set of documents from one large main document. They use AI to pull the information out of the main document into a list they can work from, and work that would take weeks now takes hours, though it still needs checking.
Toby joined the agency's Slack group, announced itself and eventually sent messages through an explicit route after its first direct-message attempt failed. When a colleague asked for a PDF summary at about 4:24 p.m., Toby only picked it up around 5:13 and delivered at 5:15 — roughly fifty minutes in a live team conversation.
The AI reads analytics, Search Console and Partner Center twice a week and produces an actions report, plus a weekly strategy review that sets the next week's plan.
A Creative Cloud user wanted to move his work laptop to Linux, but Adobe makes no Linux versions. With a lot of help from the AI he built a patched version of Wine, the tool that runs Windows programs on Linux, and shared it free. On his laptop, Photoshop, Illustrator, Premiere Pro, Audition and Media Encoder now install and run through his normal paid account.
A user had the AI apply TurboQuant skills to optimise a Qwen3.5-9B model running locally via MLX on Apple Silicon. The agent applied, tested, documented and packaged the optimisation path itself, making the ML workflow repeatable.
Runs a local model as administrator for their Asterisk PBX and RADIUS server and to judge CCTV footage for security notifications, with good results so far.
Amplifying.ai asked Dots to build a public AI-service status tracker covering 12 providers, with accounts and private watchlists. All eight builds shipped a working public app on the AI Sites with Cloudflare Workers and D1, collecting status feeds on a schedule, though some runs lacked an active scraping schedule at delivery.
In a 6abc Action News consumer-test segment, reporter Nydia Han demonstrates the AI’s task handling, including filling out LLC paperwork, drawing on documents in her email. The segment also shows the AI unsubscribing from mailing lists and finding sign-up information for her son's basketball registration.
A corporate salesperson who cannot code keeps all his customer files in one folder that the AI reads directly. Before a meeting it pulls out up to three things to check, and after a meeting it turns his voice memo into minutes and a thank you email and files them.
Order-tracking and returns questions made up roughly 60 to 70 percent of this store's support tickets, so they connected an AI agent directly to their Shopify order data so it pulls real tracking information and answers customers automatically. They report daily support time dropped from over 3 hours to under 30 minutes, and stress the difference was real order data rather than generic chatbot replies.
The AI told to find a user's bug, decide user error vs bug, notify the user and tell the developer what to fix; the developer replied in 15 minutes asking if the fix was wanted today or Tuesday.
A user gave a farm of Opus agents on three AI accounts one job: make money. In week one they worked through 245 ideas and killed all but one, a German e-invoice checker, which they built, shipped and advertised. It drew 68 visitors and 6 real invoice checks and earned nothing. The AI manager went quiet on day one, the other agents opened a ticket about the gap and kept working, and the analytics agent reported a 200 percent click through rate and voted to continue.
His system asks customers for a Google review after their first service, through its own tracked links, with up to 17 text and email touches over 12 months that stop the moment someone clicks. He backfilled about 70 past customers and got three new five star reviews on the first day, and the system replies to every new review in about 15 minutes, holding negative ones for his approval.
He asked the AI to make a marketing video for his app, Astro Editor. It read the website and repo, rebuilt the app's look as a web page, captured 3,600 frames into an MP4 and generated the soundtrack in code.
She is the training coordinator at her job and tracks everyone's certification hours in a color coded Excel workbook. She still had to log into the training website, check each person's hours, and type them in. Now the AI checks the training website for every employee, fills the hours into her uploaded workbook, and emails her the updated workbook and a report. It runs on its own on the 1st of each month.
He fed a career vault tool 21 resumes from the last 10 years plus weekly journal entries about projects, wins and goals. Every morning the AI pulls jobs that match his profile, tailors his resume per posting from that real history, generates the PDF, and fills out the whole application, then stops and waits for his review before anything goes out. Review takes him about 30 seconds per application, against 4 to 6 minutes each when he did it with AI. The post also promotes his own paid tool, so it is marked promotional.
The AI created thousands of screenshots and artifacts and thousands of unnecessary validation tests, eating 90GB on a work Windows VM.
The AI enabled a camera on a test device and he taught it to reboot into the previous kernel on build failure so it could iterate for days; ended with a usable setup and camera login working.
Cemex's Consult HR agent in Microsoft Teams explains the vision benefit from SharePoint policy documents, then presents an Adaptive Card in the same chat where the employee enters details and uploads the invoice image. On submit, Power Platform workflows route the claim into ServiceNow and immediately return a live tracking ticket number in Teams.
The AI runs his entire video production pipeline via an AI plugin: full 5-minute explainer videos from one prompt, thumbnails and titles, auto-upload via the YouTube API.
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.
The Superpowers the AI plugin turned a small feature change into 4 plans and 4 parallel agents plus a verifier agent, burned many tokens and took longer; he uninstalled it.
Handed the AI a planned multi-module change and came back to 4 PRs ready to merge in 15 minutes; the work would have taken most of a day.
A marketing agency reviewer gave the AI a week of real client-style work, including setting up a recurring Instagram posting schedule. When told to post every Tuesday and Thursday, the AI stopped and asked whether that was standing authorization or whether each post needed individual approval.
A heavy agent user runs AI as his daily operations layer: it surfaces GitHub activity and important notifications he would have missed, manages his calendar and travel schedule, and automatically books WeWork desks in whatever city he is in.
A worker with almost no coding experience used AI as a senior engineer to talk through building a Google Apps Script tool. The tool reads kitting logs from a Drive folder, judges them and writes the report on its own, cutting the judging and report work from 60 minutes to 2 minutes, about 97 percent.
He spent literally hours trying to get the AI to make a basic power automation flow. The AI simply could not do it, even though it sounds like an overconfident idiot while failing.
A developer new to making videos drops raw files into a folder and the AI, connected to DaVinci Resolve through an MCP server, builds complete edited YouTube videos: transcribing, picking cuts, graphics and music, using a setup it built up over his last three videos. His latest video took 57 minutes, with AI showing him take options to pick from.
He runs Svippit, a small shop platform for creators. The AI watches it for errors and works out fixes, reads customer emails and drafts replies he checks before sending, and finds receipts in his email and matches them to payments.
A Japanese non-programmer who posts about shochu, his garden and the AI across X, Instagram and Facebook gets a 7 AM message from the AI with today's paste-ready post text, the photo to use and 3-4 posting steps, prepared from a one-page work memo of what is due and what is already posted. Drafts are scored against his rules and only those scoring 80+ are sent; the agent must ask him rather than invent personal experiences it cannot know.
Sandboxed agent checks spec and code drift daily, triages findings, and surfaces issues; it revealed product miscommunications on the team.
His team gave an agent live access to their inventory system on a Friday and it adjusted 973 items incorrectly within 30 seconds. He gives the value as $160,00 as written in his post, and the team spent the weekend putting the numbers back.
MindStudio confirmed an AI setup that scrapes competitor websites on a schedule and delivers a formatted report every Monday covering pricing changes, launches, funding and incidents. The watchlist is frozen once in chat and the job then runs untouched.
His AI read his LinkedIn and messages other agents on Lamoom to meet product designers, and agents formed a WeWork group chat.
He gave the AI 45 podcast files, each about an hour and a half long. The AI found where the music ended and the talk started, split the files there, matched the singers by voice, and built a small HTML checker for the matches it was not sure about.
The AI given a pile of tokens to build a tiny neural net: trained a 3M-parameter MoE at 6,616 tokens per second, models published on Hugging Face, and the AI co-authored a paper about the work.
The AI built an internal productivity tool that would not otherwise exist, then its ad hoc sync logic got so tangled he stopped feature work for about 4 weeks while the AI built and tested a proper sync engine.
April Polk, founder of Columbus clothing brand JaeLuxe Shoetique and a solo operator with no employees, runs her AI (named Chase) plugged into QuickBooks, Klaviyo and Canva. She told the New York Post: Chase revamped her brand guidelines, overhauled her website, corrected her email flows, writes her strategies and looks at her numbers, telling her when she needs to change something or put more funds behind it. Polk was one of 35 owners Meta invited to test the product pre-launch.
He now uses AI for design work and for putting print plans together. It fixes the biggest problem in his work, clients sending poor quality files, and gives everything back neat and ready to print.
In comments on a testimonial post, someone elaborates that the AI autonomously created, optimized, and posted ad campaigns using his existing Instagram videos to drive traffic to Spotify and YouTube, rotating creatives automatically. Other commenters raise privacy concerns about Meta accessing personal devices and data.
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.