A random mix from the whole library. Shuffle for a new set.
With Notion, Canva and Instagram connected, her AI Poppy audited her content, surfaced her high-engagement 'vibe coding' posts and the questions her audience asks most, and now tracks performance daily with alerts.
He runs a freelance video editing studio and a coding studio, and his project folders were a mess across drives. He started a small folder making script with AI and kept adding to it daily for five months. It is now a 100,000 line Rust program with 1,390 tests that holds every project he has, gives each a permanent ID, and jumps him to any project on any drive or machine with one command.
He had an LLM write almost all the TypeScript for the new version of his consulting website, which is now live. Median first load fell from 1,817 KB to 222 KB, and Lighthouse accessibility scores rose to 100 on every page.
He had the AI build a 15 second showreel with music from a single prompt, using an animation skill and his own list of banned things. The AI checked its own images and fixed them before he saw anything, and he says After Effects is on his delete list.
Forum founder MJ DeMarco needed a text update across 12 pages of one of his websites, but the platform that built it demanded a new subscription just to edit. He gave the AI access to the site folder instead; it made all the changes in about 3 minutes, avoiding an estimated hour of manual editing and a $20/month subscription.
He spent $80 for the AI to read a proprietary file system from a piece of hardware from the early 90s. The AI extracted all the files intact.
Got the AI to build a focus app for his Mac; he uses it daily and says he does more good work with it.
A user running the AI in manual mode, where every edit needs approval, found the agent rewriting rule files and creating a script without confirming anything. The model had read the session's permission mode once at the start, when it still showed 'default', had no way to see it change, and when challenged answered from that stale reading and guesswork instead of checking.
The author asked the AI to scan his Gmail for founders he had spoken with a year earlier but not recently; the AI surfaced several not contacted since last fall, and he is now reviewing their companies for follow-up.
Ticket-driven agent setup: he adds a ticket, it makes a mockup and writeup, he approves, and it spins up a temporary webserver and iOS and Android builds to verify; review and testing loops run automatically.
A farm owner’s the AI logs into Paychex Flex, submits payroll, and then tells him what he owes after taxes. Payroll day is a bot run and a summary, not an afternoon in a portal.
He had always wanted a compact guide to probability distributions, what they are used for and how they relate to each other. The AI built the site he designed, with 15 core distributions and an extended map of 32, where clicking a distribution gives an interactive graph and clicking a link explains the relationship.
Web page build scored 5/10: built in ~40 seconds but read like a first-pass concept, noticeably less developed than the AI’s output for the same job — and the finished file was hard to locate (hunting through Goals and Files).
A job hunter's agent sends him a daily email of new postings, marking where he would be a fit and where he would be a stretch. He says it saved hours he used to spend going through job boards, but it does not write applications or resumes.
An LLM created his spec-driven development harness, iterated until it worked as wanted; it is now used with the spec as the source for code changes.
His miniature software factory runs unsupervised: he pressed Alt+N, typed make TTS streaming, and 5 minutes later his text-to-speech showed words at every pause instead of only at toggle.
An outdoor-gear store owner questions his campaign and sales data conversationally through AI, connected by MCP to his email platform - no prepared reports. Reviewing a full launch week, it showed shoes drove the most revenue, filter cartridges converted best, and the trail-shoe waitlist caused the first-24-hour sales burst; follow-ups held up after removing repeat customers, convincing him to build a VIP waitlist into future launches.
His Omeka exhibit died when the Neatline Text plugin stopped being developed. He scraped data from the old site, built a new framework with AI over a few days, and the beta rewrite is now live at the original address.
The AI added programmatic PowerPoint screenshot support to his markdown-pptx tool in under 5 minutes.
He runs a music school and cannot code. He talks to the AI and it built the school's app: people use it to open doors, book rooms, manage and cancel bookings, take payments and get refunds. He says it works pretty well and has had a couple of hundred downloads so far.
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.