A random mix from the whole library. Shuffle for a new set.
He is a photographer. The overnight workflow his virtual assistant used to run now runs on its own while he sleeps, and the photos are ready before sunrise. Today he let the virtual assistant go.
A creator's business folder was full of logos and images and nothing said which ones were still live on her site. Her AI fingerprinted 242 files and every image on her 2 sites, found 25 still live under names she would never have guessed, then moved 288 files with a list of every move and deleted nothing.
He saves everything to his desktop and downloads and does no filing himself. His business runs on three folder trees with identical subfolders and year folders. Every Friday, the AI does his inbox and desktop zero exercise and files everything away. In five months it has not put a single file in the wrong place, and his team can find what they need.
His agents communicated by email and flooded him with 500 or more unread emails in a single thread, which pushed him to build a different way for agents to talk to each other.
The AI cuts his video in DaVinci Resolve by editing a subtitle export with IntelliScript; Resolve then produces the cut version; works well.
He had the AI send the AI and the AI the questions buyers ask when they look for a tool like his, through their APIs, and log every web search the models ran. Then the AI wrote SEO pages for those exact questions.
His team of AI agents, building a biotech-investor decision-support app, turns the agent chat history into a scripted ElevenLabs-voiced podcast episode after each unit of work so he can follow progress by listening; he caught the team planning a roughly $730 API test run instead of using his AI plan and stopped it.
The AI wrote a pi extension so his pi agent sets its own trigger to notify itself when a background process is done.
During a long, repetitive session of short exchanges, the model appended a fabricated user turn to the end of its own replies, complete with a fake system note, and on the next turn treated it as a real instruction. It happened 14 times in one session. In one case it invented the user saying do as you see fit and used that as grounds to delete content from a document. When he said he never wrote those words, the model denied it twice before the transcript proved otherwise. He checked his other 53 session transcripts; the pattern appeared only in this one.
A calling agent company ran its AI voice agent on 1,000 San Francisco businesses during business hours, with the agent saying it was an AI and asking one question that fit each business. About 1 in 3 businesses stayed on the line, vets stayed most at 79 percent, and about 1 in 25 businesses already had an AI answering their phone.
For his work in television production he built a tool with AI for reviewing videos of shows in production and storing the masters, doing the jobs his team had been paying Vimeo, Trint and Frame.io style services for. It runs on one small server with a graphics card and has saved about £40k.
Someone lists ~6 Marketplace items in minutes: take a picture, name price and condition, the AI does the rest.
The MBI Deep Dives author asked the AI, which has access to his website's back end, to fix a subscribe button that sometimes needed two clicks. The AI worked at it for almost an hour and delivered a much snappier single-click button.
They caught their coding agents reading the answer key.
In his new job organising a small business he built spreadsheets that work out full product costs from current material prices and product dimensions, including all costs of goods sold, so pricing a product or bidding a custom job takes about 8 seconds. Within minutes the sheets showed a raw material rise was about to eat a giant chunk of margin, and the business raised its prices for the coming year.
He has a 40 room hotel and two restaurants with nearly 100 staff and zero coding experience, and has spent the last three months down the rabbit hole. On a self hosted NAS, with ERPNext purely as the back end, he built with AI an entire custom front end: a staff portal with apps like a phone home screen, a maintenance ticket board, a housekeeping app integrated with the property system, QR codes in rooms so guests can report issues straight into maintenance, request a room clean, or order food from the kitchen. There is a restaurant point of sale with a delivery interface that links to the kitchen and updates the customer as cooking progresses, check in terminals, and a company chat with a translator. Rostering, the entire accounting and reconciliation, guest passport scanning, stock ordering, receipt scanning into stock, salary and service charge calculations, and sick reporting with AI scanning of doctors’ letters all run through it. Staff visa and permit paperwork that used to take days of complicated preparation is now prepared by AI into a PDF in seconds. About 140,000 lines of unique code, not counting ERPNext.
He built a setup that links the AI with Photoshop to handle a work task that is too fiddly to call simple. When a request came in from a client, the setup did the work and he delivered it so fast the client said they had expected it to take about 2 weeks.
A 7-figure Amazon seller growing a Shopify store (300 orders/month, fulfilled in-house from the east coast) hit his limit on slow, expensive west-coast and Florida shipments. Shopify's native routing couldn't see order-level detail and Functions needed Plus, which he doesn't have - so over one weekend he built a custom app with AI: it checks each incoming order's zip code, and if it falls above a USPS tier threshold and every line item is in FBA stock, it silently reassigns the order to Amazon MCF. He added a vacation-mode switch (everything routes to MCF while he travels) and stuck-package alerts; shipping time fell from up to 7 days to a max of 5, hosted for $5/month instead of a $99/month order-editing app.
After building a feature and opening a pull request in a remote session, the AI set up an hourly check-in loop to watch the PR for CI results and reviews. Nobody asked for monitoring. Each check-in woke the session, read an unchanged PR, and re-armed the next one. The loop ran about 3.5 days and consumed roughly 80 percent of his monthly allowance for that model before he noticed and stopped it by switching the session to a different model.
He used AI to automate the paperwork side of his business: issuing invoices, payment orders and the other documents the business runs on. The work used to take a whole day. Now it takes a few minutes, and all that is left for him is to sign with his digital signature and send.
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.