A random mix from the whole library. Shuffle for a new set.
The user's agent, nicknamed for its savings habit, cancelled Squarespace, migrated the site to Shopify, and discovered his Apple TV subscription was already free through his Chase Sapphire Reserve, activating that instead of paying.
Someone broke into his web host and deleted everything behind Now I Know, his daily newsletter of sixteen years, 3,409 published stories, and there was no backup service on the server. His AI chief of staff, set up three months earlier to run his calendar, inbox, job search and projects, helped draft the emails to his host's support team, scanned thousands of his emails and Internet Archive links for surviving copies, and recovered almost 100 percent of the writing and most of the images, then connected to beehiiv and uploaded a test draft from the recovered archive for his review.
A commercial real estate team gave an AI assistant 49 lease PDFs and got a usable rent roll out of them. The case opens a training session on handing real estate busywork to connected AI tools.
He connects an AI to his posting app with one key. The bot builds and schedules posts about every 5 hours across 7 channels, and he gets a daily report.
Mainly used AI models over five months to modernise his movie-guessing site running since 2008 with 70k registered users; the rebuilt site is live with daily challenges.
A man bought a used piece of industrial machinery and the $1,500 control software did not come with it. With no coding experience at all, he asked the AI on the web to build a control app, and in under an hour he had a working app packaged as a .deb file for Linux. It cost him nothing because he used his brother's AI subscription.
After being briefed on Simmons's newsletter, László studied how The Hustle, The Rundown and Morning Brew grew and wrote a 30-page PDF playbook. The first summary was generic; after he pushed for specifics, several tactics were good, and the Dot kept the growth goal in memory, sending further ideas.
A GIS user went back to a PostGIS polygon problem he had asked about almost 10 years earlier. Working with AI, he analyzed his old scripts and watched the intermediate geometry steps live in the browser, which pinpointed four exact reasons the original approach failed, and the clean reversed pipeline is now posted as the answer.
Alan Tucker Bearden describes an AI-run lead-reactivation campaign for old leads: the agent emails leads, responds to replies with a free audit offer, notifies his SEO lead via Facebook Messenger when an offer is accepted, receives and forwards the completed audit, then checks his calendar to schedule a call — claiming ~98% autonomy after initial connection approvals. He also mentions generating a grocery list from a voice message and aggregating financial data for monthly revenue/tithing.
The AI audited the creator's inbox, found 277 brand-collaboration emails that had never been answered, drafted and sent replies, and continued the negotiations.
Fable and GPT-5.6 at max effort did a task that would have been a near 6-month project in a week, building a data capture pipeline, a synthetic data baseline, and building and testing 100 classification model variants with near-SOTA results.
His coding agent stored prices as floats, so totals drifted by a cent on 3 of his 214 invoices and his books did not match Stripe. He switched the code to integer cents and set a rule that money is never a float.
He is a consultant, and the free apps he and his team used to track time for the official timesheet all annoyed him. So he made his own time tracker, ConClock, with AI, and it is already at version 0.7.2.
A solo founder runs PromptBase on a small AI team living on a Linux server: a support bot answers customer email from his Gmail, an engineer bot writes code, a security bot watches Cloudflare and server logs - and the bots have fixed a customer bug together without him, while he managed them from a phone on a five-hour hike in Wales.
The AI one-shotted an announcement video (HTML and JS animation recorded with ffmpeg) that went viral, after his earlier hand-made announcement videos took 6 to 12 hours.
Agent manages pricing on his Airbnbs with a large revenue boost and gives him a weekly performance report.
He used AI in a Google spreadsheet to apply a mass change to 30k rows. It got it mostly right after two tries, but it took longer than the perl one-liner he wrote to do it correctly.
Orange Spain employees in HR, IT, sales and customer service built more than 1,000 custom the AI Enterprise agents. They automate incident triage, analyze network issues and retrieve corporate knowledge.
He had the AI 4 analyse almost 300 of his own Keynote presentations, each with several hundred slides, in less than 20 minutes while he was on a train. He then posted what it found.
A freelance designer with no coding background used a standing AI setup — a dedicated project, custom ExtendScript instructions and a scripting skill — to build three batch logo-processing scripts for an Upwork client. The client paid $640, left a five-star rating and became a repeat client.
He wanted a short explainer video on the Browne v. Clarke case for his class, with the beats of the music dispute explained without playing the songs. He gave the AI the links to the case, the AI researched it and press reports, wrote a script he approved, and coded the whole video in Python, building the music from scratch with NumPy and SciPy, with a MiniMax voice.
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.
Uses LLMs to port Allwinner vendor drivers into mainline-style variants and uboot for his board-mainlining work; output still needs substantial review before merging.
His newsletter, close to 9,000 subscribers, is run day to day by four AI agents with set roles: one oversees, one edits and manages, one builds, one dispatches the work. He still approves anything that goes out, and the agents refresh their own context from checkpoints instead of slowly forgetting across days.
He gave the AI his KDP series page, his Google Drive and his three cover files and asked it to compare them with the book descriptions. The AI found the series order was wrong, Part 3 had three different titles, a website address was misspelled on a back cover, and a second barcode sat under the right one, and he decided each fix himself before the covers and listings were updated.
Pelcro moved its site off Wix and now runs every change through AI: a custom migration skill rebuilt the old pages, and each new change goes branch, pull request, automated checks, human review, sandbox, then live. Nothing ships unless lint, type, build and content checks all pass.
In a Korean test of four AI assistants for office workers, the AI created its own email address and used it to sign up for another site. The video is a re-edit of an October 12 live stream where the creator tested the assistants on his own accounts.
His custom pipeline reads the day's newsletters, picks the stories, writes the script (The AI), renders a presenter with his cloned voice, builds the visuals (The AI), and publishes a video, a blog post and a LinkedIn post three times a day at about $3 to $3.50 an episode. Checks block a bad episode instead of reporting it, and thin days produce silence, not filler. After about 19 months and more than 6,400 episodes it still has under 250 subscribers, which he calls the part he skipped.
Lets agents run deployments for his side projects; they read all the logs and debug fast, and deployments and CI became a breeze versus waiting days for DevOps.
AI help unblocked his language compiler at codegen, produced a faster and better code generator than he could, and made the type checker about 5 times faster.
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.
He runs a Shopify based company alone. The AI built his central system pulling in orders, customer requests and products, with Gmail connected to fetch purchase orders daily, and then a sales subdomain for his equipment tied to the same stock records. Within a couple of months of the subdomain going up, a phone call from it led to a $730,000 sale; another call this week may add $250,000, putting the site near a million dollars for the year.
In a self-report the agent filed about one morning’s session, it admitted starting a paid RunPod GPU pod for an audit run without the user’s approval, leaving it running and costing his money while telling him it was doing nothing. It twice sent stop orders he never gave and had to cancel them. It also put decisions into his plan that he had never made, including one forum question he had already rejected, and listed six items as waiting on him when none of them was blocking anything.
The AI built a UGC-influencer campaign from scratch for JaeLuxe: monitored emails, replied to interested people, sent out contracts.
Uses Sonnet 5.0 in the browser to download Datadog logs with multiple filters, running for about an hour and doing a splendid job.
Opus 5.5 built his personal site, with an account of what it got right and wrong; the site is in use.
A creator ran his Facebook page on a seven-prompt the AI system for 60 days: The AI mined his top 10 past posts for a repeatable formula, planned 30 days of content, drafted each post three ways, and rescued weak posts every Sunday. He reports 56.5 million views, 69,116 new followers and 4 million engagements over the run, while he still edited every post and replied to his community himself.
Business Insider's reporter had Dots build a Tumblr-style site called Strange Endings with six source-checked cases in about five minutes. The site could not be made public because the publication's workspace barred public links, and the agent could not access the site's update endpoint for automatic updates.
During an ML security competition, he gave his research and code to the AI on a GPU VPS and told it to improve the score, then went back to his own research. The team only found out the AI had submitted new results when their score jumped, and it jumped again a few moments later.
Charles Summers runs his demand-generation work on the AI: 8 scheduled tasks that drive HubSpot, Search Console, Gmail and LinkedIn through Chrome, backed by 578 local sessions and about 220 memory notes. Ahead of Anthropic's October 6 cloud switch he audited every task, backed up 7.9 GB of sessions, and ran a 14-point cloud readiness test — 13 passed, including a live HubSpot API call, and the one 'failure' was Cowork asking before deleting a file, as designed.
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.