A random mix from the whole library. Shuffle for a new set.
Her healthcare provider texted her to press 1 to confirm an appointment, she drove 2 days to get there, and it turned out to be an error, with no apology. She used three AI tools, mostly the AI in Word, to sue the provider.
He gives the agent his ideal customer and one pain point. Every morning, on its own Linux box with its own logins, it goes through X, Reddit and sometimes LinkedIn, pulls threads where people are complaining about exactly that, and writes him three things: signals worth knowing, post ideas for the day, and who to message. He reads, picks, and posts.
At the Operably founder's own Aveda Lifestyle Salon in Carmel, Indiana, the live setup books guests by text against real availability with a card on file, sends intake forms automatically before a first visit, and gives staff a Teams/Slack assistant that answers policy questions from the salon's own 1,000-plus documents with cited sources. Within weeks of the reminder texts starting, new guests arriving with the intake form already done jumped from about 25 percent in a typical week to 81 percent in one week; the voice receptionist is built but not yet live for guests.
He had screened CRM and ERP tools that cost 100 to 150 dollars a month and came with many features he does not need. His friend built exactly what he needs with AI instead.
Fed up with tailored resumes that read like AI slop and broke formatting on every edit, a job seeker built his own MCP server - a vault his AI can reach into. Section one is structured storage: ten years of old resumes organized into about 80 bullets (education, experience, projects, summaries, each written from technical and leadership angles), kept current by weekly journaling - he voice-notes incoherent drive-home dumps about projects and the AI pieces them into crisp bullets. Section two is tooling: bullets are tagged and ranked against each job description, then assembled in a web editor where he swaps bullets before downloading the PDF. Every morning the AI surfaces 4-5 high-value jobs and returns tailored resumes for his review; he later wired the same vault to the AI to fill in applications and upload resumes into a review queue. Six months: 250 applications, 39 callbacks, 4 offers.
Kimi told overnight to fuzz Linux kernel filesystem code produced 26 crashes with reproducers and fixes; some have already landed upstream.
The creator says the AI made AI short form video good enough to replace his 1,500 dollar a month editing budget, and he lays out the full 8 step system he uses to turn YouTube videos, GitHub repos and articles into polished Instagram Reels. The system produces an AI avatar, motion graphics, captions, music and sound effects for about 8 dollars per short, using FFmpeg editing, a HeyGen avatar, work split into sub-agents, and thumbnails, captions and auto-scheduling.
His work runs on provider dashboards that offer no downloads, with a separate dashboard per location. He sets the AI loose on them to pull the data out, builds one consolidated report from it, and gets competitor price movements in the same pass.
He pointed the AI at his JavaScript project and asked for a full TypeScript migration without changing behavior. 236 commits and a full day later the project compiled clean, the linter passed, and 55 of 56 tests passed, with the one failure traced to a commit where a value was accidentally hardcoded.
A three-person flipping operation runs on a custom app steered through AI over MCP: it identifies what is actually inside vaguely described government surplus lots by hunting service tags in the auction's spreadsheets and model numbers in its photos, values each lot against sold comps, and overlays a buy/watch/pass call with a max bid on GovDeals as they browse. It also ranks repairs by ROI, turns SD-card photos into listing pages that a human approves, and prints a pack-in sheet with QR ads for their other listings when something sells.
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.