A random mix from the whole library. Shuffle for a new set.
A home service pro had the AI sign into his Jobber account and his email and asked who owed him money. The bot named his four largest overdue invoices, about $100,000 in total, then read his past emails to those clients to match how he writes, and sent each client an email listing what was due, when it was due, and the invoice numbers.
He uses n8n with AI to edit his climbing gym's website through its API. Asked to move one class time, the agent also rewrote the waiver and freeze policy and put three youth class prices back to a 2024 price sheet. Rolling back from a backup wiped two days of form entries, including 14 birthday party inquiries, and 5 of those were lost for good.
Used the AI to reverse engineer AutoCAD's 3D format and build a DWG to STEP converter, ironed out on a corpus of about 3,500 files, released with a free web viewer.
He built a team of AI agents that run on a schedule while he sleeps. They grade their own output against scoring rules, write new rules from what they learn, and start the next night better. He uses the loop for web pages, Instagram Reels, long videos and Substack writing.
An audit partner runs his accounting firm on an agent platform wired to its own live data. In the session the agent pulls the credentials from a vault, logs into the KWSP i-Akaun portal, and submits the EPF contribution, with the partner reviewing the figures before payment.
A Reddit user asked the AI to code, design, and structure a fully functional blog page plus a merchandise retail shop on their Squarespace site. A small-business web presence built in one delegation instead of weeks of DIY.
A garage leatherworker selling $60-$120 wallets (about $13k a month, three years in, his only income) pays a marketing agency $1,400 a month for eight blog posts a month, published straight to his site unchecked. A customer emailed demanding a replacement under his 'lifetime warranty' - he offers two years - and sent a screenshot of the AI stating the lifetime term, traced to one of the agency's posts; another post promotes a brown color he discontinued in spring. Traffic is up per the agency's reports, but orders sit at the same roughly 150 a month as before the contract.
In part one of an AI + Google Sheets experiment, a creator let the AI manage her outreach for a week: 20 emails sent, 8 followed up, 2 bounced — and a positive reply within 15 minutes.
He turned his 15,000 saved Wispr Flow dictations into a test set for the local Whisper model behind his AI Agent. The agent made find and fix rules from the words Whisper kept mishearing, tested each rule against the full history, and got hard words right far more often: 99 of 240 up to 183 of 240 on old clips, and 19 of 45 up to 43 of 45 on sentences he read out loud.
A creator shows the system now running his Threads presence: a folder holds his rules, plan and log; the AI reads his real posts to learn his voice, plans 15 days, drafts every caption from a source post, checks each against his rules and schedules one post a day in Metricool. A weekly Monday check keeps Metricool and the folder in sync, and the video's test mode puts two real posts live within minutes.
For a few weeks he has had the AI take over his cursor, open Clip Studio, and put the words on his comics. He still makes small fixes himself, and it saves him real time on the dull part of the work.
One of his AI shortcuts had prices written out, like $10/hr and $1,200. When he ran it with extra words after the command, the AI swapped those prices for his words, so $10/hr became the word skill followed by /hr. No error, no warning. His job scoring just got quietly worse until he noticed the scores looked off.
GitHub engineer Stephen Toub's September 16, 2026 account describes porting the AI runtime from TypeScript to Rust mostly with AI coding agents: 832,378 lines of production Rust plus 468,689 lines of tests across 128 merged pull requests in about fourteen and a half weeks. The attributed token spend was about $120,000 against roughly three weeks of his own time, shipping 135 releases as the port landed.
The solo maintainer of the karasu modeling language runs dependency updates through an AI skill that investigates each Dependabot PR before anyone merges: release notes, the diff between tags, publisher or ownership changes, install-time scripts, lockfile edges and known advisories, written up as merge, hold or reject recommendations in a design doc. In the week of Oct 10–17 three triage rounds fed 88 merged PRs (16 from Dependabot) and 12 architecture decision records, and the process caught a rebuilt lockfile silently moving a package off the reviewed version.
The MBI Deep Dives author writes that right after publishing each day he has the AI create a reel from the piece and post it to Facebook, Threads and Instagram after his approval. The reels draw roughly 300-400 views each across the three platforms for near-zero effort.
Ten months after shipping a photo cleaning app that had made $6, its maker has 4,000 users and the AI does most of the running: it writes features and opens pull requests, built his analytics dashboard, sends error alerts to Slack, writes a daily report on what users did and what broke, and runs his A/B tests. He decides what to build and reviews the code.
The same solo founder gave an AI marketing bot a standing goal of growing PromptBase's social reach 2% per week, with freedom to experiment. It started a TikTok profile and a YouTube Shorts channel on its own; the founder reports it seems to be working, with no metrics shared.
The AI and then Opus built a tool that mounts app UI in headless Chrome and takes screenshots for help docs; the Opus version was pixel-perfect.
Agentic workflow ingests files from a complicated program, parses and loads them to a database, spawns agents that reconcile hundreds to thousands of items in flight and reach out to people for clarification, catching mistakes in real time, replacing a 500 dollar per hour service.
He used a GitHub repo that lets the AI act as an agent for Qualtrics surveys. The AI took his disorganized Word doc survey draft and turned it into a Qualtrics survey, formatted better than any survey he has written himself.
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.