A random mix from the whole library. Shuffle for a new set.
Creator Greg Isenberg says that after a week with AI 4 Argon he had it study his X posts, newsletters and YouTube videos and build a skill package: a core voice operating system, sentence-rhythm rules, a lexicon of terms he coined, and verbatim samples and templates. A post it then wrote on marketing engineers was self-scored 9.2/10 by him.
The AI Launch team reports a live test where a managed the AI Agent, given one chat instruction, searched Vast.ai for an RTX 4060 Ti under a $0.40/hour cap, rented it, rendered a 1920x1080 Blender frame over SSH, and destroyed the instance. The whole cycle took 194 seconds and cost $0.007.
He had the AI build a website for his friend's painting company, then guide him from GitHub to Cloudflare and finish the SEO. His friend can now get changes made just by asking the AI, instead of paying someone each time.
He added a weekly ops review to his AI chief of staff bot. Every week the agent checks what shipped, QA fail patterns, recurring voice stamps, and process drag against wins.
Used GPT-6 to develop a new barcode scanner library, built a labelled real-world test suite, and published it for JS, Python and Rust.
In Tye Gordon's Lauderhill businesses, the agent roster includes Hope, whose whole lane is the gap after the AI receptionist takes a call: Hope follows up on those calls and sends the customer update texts and thank-you emails, each one approved by Tye first. The design point is that an answered call is not a finished job — somebody still has to close the loop with the customer, and that somebody is an agent working from the call record.
Mailing thousands of people brought hundreds of auto replies that nobody read. The AI scanned them read only, flagged who had left or changed roles, and updated Mailchimp, leaving a cleaner list and better deliverability.
The AI ported CADO-NFS to GPUs and orchestrated a fleet on scavenged idle capacity, running about 30 GPU-years over 10 days to factor RSA-260.
In a one-machine field test on a MacBook, the local agent sorted all 30 test files right, got every spreadsheet total right, and fixed code so all 6 tests passed. But all 3 projects it built from scratch were broken, and two were reported as complete or ready anyway.
A Business Insider Japan writer set up six AI bots besides his main one and has run them for about a week. One checks his to-do list and pushes him to reschedule, one picks out mail that needs a reply and drafts it, one pulls expense items from mail into a spreadsheet, and one looks up missed call numbers in his mail and contacts and sums up who called.
Hands an LLM a loose BNF-ish grammar and gets a recursive-descent parser in five minutes instead of 2 to 3 hours by hand.
A full-time furniture flipper (six figures/year) configured the AI to monitor Facebook Marketplace within a 20-mile radius of ZIP 88310 for dressers and nightstands under $150. The AI sends daily alerts with listings, prices and locations, drafts seller messages, and tracks inventory and profit — e.g.
He runs a print shop full time and is not a designer. The AI designed about 35 formal disinvitation cards with him, drove the browser to set the products up on Fourthwall with prices and descriptions, built the website, and synced the catalog to Etsy with new main photos.
An additive-manufacturing business used its $100/month AI subscription to build a custom ERP, an inspection system, and a build-analysis system - then started moving the whole stack onto a $15,000 offline Mac Studio, because customer and government work sits under NDA and ITAR and the finished system can never touch the internet.
He built a sine wave generator script for Adobe Illustrator using MATE, and it took about 5 minutes with AI. The script is now free for everyone in Astute Manager Pro.
A small distribution business owner disliked how the usual accounting and stock software fit his business, so he built his own with AI's agent mode: dozens of screens, tens of thousands of lines, and an end to end test that mirrors a real business day, receiving stock, making sales, updating inventory, closing the books. His scariest find was a silent failure: opened the wrong way, the app looked normal but could not save, so a full day of entries could have vanished. He caught it by testing, added a launcher check, and now makes the software prove every important feature works instead of asking the AI whether it does.
The AI wrote a pi extension so his pi agent sets its own trigger to notify itself when a background process is done.
Team Data Platform Agent, evolved over 2 years, is widely used for SQL questions, on-call alert triage, lag monitoring, and scheduled workflows fixing bad data.
Ryan Mercer spent a weekend building a SaaS with AI and Next.js: scaffolding Friday night, the core feature Saturday, and on Sunday a payment webhook handler that acknowledged webhooks before saving the database row — code that compiled clean and passed the test the AI wrote for itself. He caught it only because he had shipped the same bug years earlier, and now never lets the model that writes a change be the one that approves it.
A solo founder runs his game key store with about a dozen AI sessions, one each for code, pricing, copy, bookkeeping and suppliers. They stay in sync through a shared record where facts are only ever added, each fact says whether a session confirmed it or just read it somewhere, and his decisions go into a numbered ledger the sessions look up instead of asking him again.
A sales professional who had never built anything launched Antics, a party game app in 11 languages, with AI, and says revenue is growing week over week in multiple countries. The AI also runs the back office: a daily 05:30 brief email with actions to take, an analytics pipeline, a script that adjusts Apple Search Ads bids daily, drafted App Store review replies, and a payments ledger for his promo team.
Fable helped find and fix a Motor OS race he had debugged for 3 months; since July most roadmap items are fixed in about a week instead of 3 months supervised.
He has a mobile app with crash reporting through Sentry. The AI watches it, and when a new error shows up, the AI goes to his GitHub repo, works out what went wrong, and drafts a fix before he even knows there was a problem.
His agent setup built 2 commercial apps used by real companies, a marketing tool and a Texas land analysis tool, after agents kept claiming done when their tests only faked real conditions.
A call center replaced its press a number menu with a system that listens to what the caller says in the first 10 seconds and routes the call. Wrong transfers fell by almost 40%.
A man wired his lab instruments to his home network, put all their manuals and programming guides into an AI project, and the AI wrote most of the first set of Python programs that control the instruments and pull data from them. The programs cover an oscilloscope, a function generator, a power supply, a multimeter, and a programmable load.
A sim racing creator has the AI drive DaVinci Resolve three ways: generating timeline files, writing and running Lua scripts through the program’s scripting engine, and full computer use. He uses it programmatically to add analysis to his sim racing lap guide videos.
His meetings are recorded with Fireflies. On a set routine, the AI takes each transcript and posts a Slack recap to everyone who was in the meeting, with the action items and who owns each one. A second routine scans his meetings for tasks that fall to him and works out which ones the AI could do instead, then offers to run them in separate sessions.
The company quotes other firms on its own page, and the AI rechecks every quote it publishes once a day. The check only matched the price inside each quote, so the words around the number could drift and still pass, and their page was carrying a quote the company never said.
Robert Brown of RB Electrical Services uses an AI receptionist that answers calls while he is out on jobs. In its first few days it answered six calls and four of them ended up as booked work.
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.