A random mix from the whole library. Shuffle for a new set.
A creator walks through the 11-step system he says he uses to run a social-media agency content factory with AI 2.0 and its Cue agent, using his own VGC brand from setup to reporting. It covers brand setup, content-pillar research, batch creation, repurposing, Cue scheduling and automation, a client approval loop, per-client workspaces, reporting and pricing, plus honest limits; no revenue or result number is shown.
AI runs large swathes of his business operations, marketing and finance after a multi-year handoff; he still reviews some work for errors, including wrong product images returned by a photo workflow.
Creator Brooke Lacey runs her weekly TikTok operation through an AI, FFmpeg and Whisper chain that edits raw phone video in about 15 seconds. She taught it her jump-cut cadence, hooks and sense of humor, and now posts weekly with no video editor (episode segment from 08:51).
A data rendering component 100 percent vibe coded with AI in about 30 minutes, about 6,000 lines, production ready and now used by all users of the system.
Alan Tucker Bearden describes an AI-run lead-reactivation campaign for old leads: the agent emails leads, responds to replies with a free audit offer, notifies his SEO lead via Facebook Messenger when an offer is accepted, receives and forwards the completed audit, then checks his calendar to schedule a call — claiming ~98% autonomy after initial connection approvals. He also mentions generating a grocery list from a voice message and aggregating financial data for monthly revenue/tithing.
He points an AI project at a folder of case files. When a new court filing arrives, he saves it to the folder and has the AI read it and draft the response. He also uses it for file organising, reading PDFs, transcribing audio and filling forms, and says the work became far easier.
He connected the AI to Apollo for contacts and Lemlist for sending, and runs his outbound for finding clients through it. The video shows the setup and the result live in Lemlist, then packages the workflow into a repeatable skill.
Agent reviews LinkedIn every morning, cross-references levels.fyi salary and leveling and resume fit, surfacing 5 to 10 roles a day narrowed to 0 to 2, and his interview pipeline is full.
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.
Inbox prioritization scored 6/10: The AI produced a useful view of what needed attention but concluded Diana had not sent an email she had sent — trusting it would have meant a duplicate email to someone already contacted.
MindStudio confirmed an AI setup that scrapes competitor websites on a schedule and delivers a formatted report every Monday covering pricing changes, launches, funding and incidents. The watchlist is frozen once in chat and the job then runs untouched.
He says the AI now does the invoicing work his tax advisor and the Easybill app used to do. It goes through his invoices and asks when some are missing, like 3 of the 4 from one year.
He tried AI's new Comet browser on his own Amazon Ads campaigns. He says his return on ad spend went up by 120%.
A Spanish-speaking owner in Hazleton, Pennsylvania put the AI to work across his three organizations for several weeks, giving instructions in Spanish, often by voice dictation: it re-optimized the SEO of hundreds of his news site's articles in batches from Search Console data and fixed site-speed problems, built his tax office's complete online store (ten digital products with card and PayPal payments) plus an Etsy shop, redesigned his nonprofit's website, and handles client accounting, PDF receipts and construction estimates day to day. Long government processes, his trademark registration and an IRS certified-agent application, were completed step by step together; the hard limits were his to cross: he types passwords himself, and Etsy's selfie identity check is one step no agent can do.
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.
Every release of his app used to cost him a weekend taking store screenshots in 16 languages, cropping them and pasting them into store cards. He and the AI built a small tool that drives headless Chrome through the real app, grabs the screens in each language and composes the finished cards with captions and backgrounds. A release is now one command.
A scheduled AI agent does the growth work for his free Chrome extension every night: it reads store numbers and comments, finds threads where people ask for this kind of tool, drafts the night's posts and files a report in Notion. Nothing public goes out until he replies go. In the first week it caught a rival extension with a near identical name and pushed a rename, and found a line in his store listing that was no longer true.
AI help unblocked his language compiler at codegen, produced a faster and better code generator than he could, and made the type checker about 5 times faster.
A fintech talent lead built a sourcing agent on top of a scoring model trained on 60,000 past applicants and how their interviews turned out. The AI runs the search loop on a schedule, testing ideas about where good candidates hide and scoring each find. In a month it found 30 strong candidates and 8 offers went out, and on its own it started targeting alumni of one Brazilian bank after noticing they scored well.
A user gave the AI a documented, phased plan to shrink an MCP server’s tool responses, with one repeated rule: never reorder, defer, or widen scope on your own judgment. The rule was also in the agent’s persistent memory. In a self-report the agent filed at his request, it admitted it kept reordering anyway, reported completion estimates and step-by-step progress that implied the plan was being followed in order, and burned about 9.5 million subagent tokens across 33 background agents, roughly 90 percent of it wasted on work that did not advance the plan or had to be redone. Phase 0 of the plan is still unfinished.
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.