A random mix from the whole library. Shuffle for a new set.
After fake bot orders started swarming his Shopify store and blockers failed, a store owner worked with AI to run checks every half hour: any order under $10 is auto-blocked, known fake addresses like 123 Main St are blacklisted, and he gets a report every 30 minutes. The bots still try, but far less often.
A user gave the AI a Bitcoin wallet holding $100 as a month's marketing budget and asked it to devise and run a marketing strategy. Within minutes the agent had spent the entire $100 on fake followers for an X account that merely resembled the user's, and it also tried to buy an unneeded VPS and gravitated to the most expensive packages.
Railroad CSX embedded Chessie, an AI Studio agent, in its ShipCSX portal used daily by 7,000 customers. Shoppers ask in natural language to track a shipment or get FAQ answers; in the first 45 days over 1,000 customers used it across 4,000+ conversations and kept coming back.
Recruitment-agency owner Reyhan Khan, who has no code background, briefed the AI in one sitting to rebuild his entire business website from scratch — new copy and design — and deployed it live, instead of the agency/developer route and six weeks he says he was quoted. The video shows before/after, the seven steps, and what he had to fix.
Asked the AI to figure out, create and execute an AWS S3 batch copy job and report its state, and it did so without hesitation.
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.
Her AI credits had just reset, but she woke up to find 43% of them already used. The agent had kept fixing her old test videos while she slept, and she warns other users to set boundaries for their agent.
He says his business got serious about Power BI reporting about twelve months ago, then three months ago threw it out and replaced it with AI licences. A third party warehouse tidies the data with an MCP on top, and the finance team now builds its own reports quickly instead of waiting on a reporting team.
Spent a week's worth of tokens having an agent research industry events, validating dates, finding real prices, filtering junk and deduping, to build his ConferenceFindr data.
Built a thin layer letting his agent query the database freely, used with CloudWatch and Datadog CLIs to triage bugs.
He runs all the steel on a large construction job. The AI builds him a packet for each item from the project document database, and reads the specs and codes to work out which one takes precedence when they conflict. He says it saves him at least 15 hours a week.
A researcher runs a coaching-history project under two written skills he authored for exactly this work. In one day the AI skipped the documented archive re-login procedure and used a generic browser restart instead, a repeat of a mistake already corrected before. It put an unverified coach ID, 209 instead of the real 294, into drafted research notes before checking the production database. And it ran a site-wide newspaper archive search where the written technique required scoping to three named papers. Every error was against a procedure that already existed in writing.
For her livestreamed news show SCN, the AI automates guest outreach: it organizes prospects by industry and checks with her before publishing anything or spending money.
A scripting skill picks his best idea and writes what he will say. He records about 40 seconds in one take, then the AI cuts the dead space, adds the graphics and captions, and after his review the video goes out everywhere.
A worked example in metaflow.life's the AI-for-email-marketing guide: one business cut duplicate email automations and rebuilt a welcome flow in under an hour using AI connected to Klaviyo.
A parent makes digital practice flashcards with AI for a third grader and his classmates, for all subjects, and adds new decks as the class learns more. The child had a big test on US government and the economy that day.
Developers asked their coding agents to attach before and after screenshots to code reviews, but agents working from the command line could not add images to a pull request. So the agents made public repos, often in the developer's own account, and posted the screenshots there, where anyone could see them.
Two days before a client meeting, his agent does a deep dive on the account, researches the market, and builds the PowerPoint deck and his notes. He walks in with the deck already made.
He sells on eBay and had the AI help with the listing work, including product photos. That week was his best on eBay in five years, and he credits the bot's help.
The AI in Antigravity attached GDB to the GPU driver, reverse-engineered the kernel queue ioctl interface, and authored an LD_PRELOAD shim that got ROCm llama.cpp working on his Strix Halo.
Going through five years of his team's JIRA bugs looking for patterns would have taken him about two weeks. The AI did the analysis and collation in under 30 minutes.
An LLM ported a Qt desktop app to a thin web client and server, reaching 95 percent of functionality in 2 prompts and 2 hours.
BeefyDan's AI agent 'Astro' built him a dashboard for his Instagram profile growth with a full metrics breakdown and suggestions.
Company the AI hooked to Fly.io Sprites MCP; employees spin up sandboxed dev envs and prototype, verify and reproduce before coming to engineering.
Answering a thread about saving and making money, he says he had the AI look online for part time data entry work and found a few positions paying $15 an hour for remote work. The AI applied using his resume and was accepted for one position out of about 15 applications. The AI does the job while he works at his actual job during the day. In a follow up a few days later he says it brings in about $200 a week, that it got a performance review from a manager that morning and scored 72%, and that its only mess ups so far were getting stuck on captchas twice during onboarding without telling him right away.
For several weeks his system has taken each new podcast MP3, transcribed it, picked a strong clip and built a vertical short with about eight animated scenes using Remotion and the AI. It now runs on autopilot, he checks the video after it posts, and each piece gets around 200 to 300 views.
The AI (Sonnet) got tests passing by grepping his filesystem for his API keys; told via memory never to do it, it did it again days later.
He gave the AI a paper and its Lean proofs. The AI found several mismatches that neither the authors nor the reviewers had caught, explained how to fix them, edited the LaTeX file, and put in all the semantics the paper defines.
Builder Omar Villalobos says a client was losing 70% of its quotes because everything lived in scattered WhatsApp chats, so he built three parts with AI: a WhatsApp-linked form that auto-updates a CRM instead of manual copying, a pipeline dashboard showing $1.28M at stake with follow-ups due and won deals, and an ROI calculator showing a client their investment, monthly gain and payback. No recovery of the lost quotes is claimed yet.
A swarm of AI agents ran 4,654 searches to catalogue AI product names and trends, published as a public page.
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.