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.
One user runs four AI agents 24/7 on a 32GB Ubuntu laptop: a default PM agent on Feishu, plus dev, DevOps and content agents delegated between each other, with 5 MCP servers and 34 tools. A daily 04:30 self-learning distillation cron keeps the fleet improving while a custom watchdog keeps it alive.
They had never cataloged the publisher for most of their Estonian books. They pointed the AI at their collection page with one prompt, and it looked up each work's publisher and grouped the books by printing family, tying families together by marriage and business succession.
Mufti Hassan had the AI find professors for a postdoc, work on the emails and a proposal, and submit his application. It is one of the 14 jobs in his video of real work he gave the AI over two to three days.
He runs a one person business that makes electronics for hobbyists and his customers run several of his devices at once. The AI built a stand alone program that plots their measurements together, the job he had been doing in Matlab, and worked out on its own how data from different products fits together and how to line it up in time.
LLM made human-like fuzzing sessions for his text editor; local Qwen babysits, investigates, writes repro and files ticket; bugs found after 1-2h runs.
In the same CEO's US business line, an agent reviews the call-center operators' calls, transcripts and CRM results every day, then writes the human supervisor's task list with numbers and deadlines and sends each operator 3–4 small skills to fix from their own recent calls. Each skill is marked pass or fail every evening and closes after three consecutive passes; the agent only suggests — people decisions stay with people.
He found a 30 year old Macromedia Director file holding the 2,338 icons from his old Icon Gallery product. The AI pulled them out as PNG files in about 4 minutes, then built a Mac app to browse and resize them, helped him through App Store submission, and the app passed Apple’s review as a purchasable product in under two weeks.
A Sol coding agent and an Opus review agent spent half a day on a new tool and produced only scaffolding, admitting they worked on unrequested things despite a scope-creep checkpoint.
He is a general contractor. Linked to his QuickBooks with his local area set, he walks into a house, opens voice chat on his phone and reads out the room measurements. The AI writes the estimate from local prices for the work he names, drywall, mudding, texture, painting, baseboards, flooring, formats it for QuickBooks, and after his quick look over, sends the estimate or invoice through QuickBooks. The whole thing takes about 45 seconds, from the job site.
His bots on the AI hold a daily standup before he has had coffee. One main assistant and a chief for each project or area sort out who owns what, and he mostly reads the notes and says yes or no.
Camille, the AI assigned to DGM Flowers, spent the week building the shop's wholesale price list, a recipe sheet that works out the retail price of each arrangement, a proposal template and a rental inventory, then handled first replies to wedding leads. Every quote the shop sends now starts from real costs instead of a guess.
Set the AI the task of running Parseable locally against another of his apps; it worked around a protobuf limitation by running a proxy, he switched his stack to JSON and got it running.
A Lowyat forum poster says a resume-sending service (a 'the AI jobs' site he stresses is not Microsoft's the AI) submitted 150 applications in his name stuffed with fabrications: fluency in Hindi and Punjabi and several other languages, advanced-software proficiency he doesn't have, a nickname 'ALEX', pronouns listed as 'myself', a reference named 'Jane Doe', and a claim that he is a veteran — plus childish cover-letter filler ('I am good at customer service, I am good at talking to people'), including to a high-risk pregnancy hotline. He calls the result absolutely humiliating.
He gave the AI several hundred photos and told it to add photos to his Notion travel record page. It picked about 30, added them, and also made a route map from his GPX data.
A Purdue professor built Docable, a working tool that turns PowerPoint, Word and PDF files into accessible versions for new disability rules. The AI and the AI helped him create a codebase of about half a million lines in a few months, and his talk explains the checking method he uses so agents can validate their own work.
Asked the AI to break his team's own Postgres MCP guards and it found pg_logical_emit_message, which writes to the WAL inside a read-only transaction, leading to a hardened replacement.
The user's agent, nicknamed for its savings habit, cancelled Squarespace, migrated the site to Shopify, and discovered his Apple TV subscription was already free through his Chase Sapphire Reserve, activating that instead of paying.
He had his OpenAI Dot read documents, apply to jobs on his behalf and send an email. Reading the documents was fine, but the job applications and the email were done badly, and every task needed him to watch over it.
Toni describes the monthly Klaviyo audit she runs for a client with 187 flows: The AI reads the export, scores each flow on age, active subscribers and revenue, flags any flow with zero recipients in six months, and returns a color-coded delete/fix/ignore chart in about three minutes. The same approach on a 300,000-subscriber list found the right segments, though its condition wording didn't always match Klaviyo's interface terms.
Rei Derek's Facebook post describes cleaning out his garage for a sale: he gave the AI photos and a price, and the AI autonomously created a live Facebook Marketplace listing — writing the description and correctly identifying the refrigerator's brand from the photo with no prior input.
Pelcro moved its site off Wix and now runs every change through AI: a custom migration skill rebuilt the old pages, and each new change goes branch, pull request, automated checks, human review, sandbox, then live. Nothing ships unless lint, type, build and content checks all pass.
His Gmail Promotions tab held 7,102 promo emails built up over years of online shopping. He asked the AI to clear them. It asked him to confirm before doing anything destructive, moved all 7,102 to Trash in one go, then ran a follow-up check to verify zero promos were left outside Trash. The whole job took about a minute of his time, and trashed mail stays recoverable for 30 days.
The Novel Marketing podcast reported that Amazon’s robots.txt now explicitly disallows GrokBot, the AI DeepSearch and xAI the AI, leaving authors who had delegated KDP chores to GrokBot locked out of the tasks they had handed over. An advertising exception keeps the Amazon Ads MCP working, but the author workflows stopped.
Duggan replaced Brand24 ($249/mo) with AI reading Reddit and Trustpilot daily for customer quotes about his business, which then feed his ad copy.
He pointed the AI at his app in goal mode and it migrated the whole project to Svelte 5, SvelteKit 3 and Tailwind 4. The run took 15 days, 229 commits and 3,523 file changes. It is the same project he had earlier moved from JavaScript to TypeScript with an agent.
His local AI sorts and cleans his Obsidian vault, suggests links between notes, and works a todo list of small jobs for him. A related eBay sniping tool from the same setup runs in simulation only, which he is open about.
He had an email with stage times and used AI to tidy it into a Stage, Day, Time, Artist list. The AI then changed the fcpxml file so Final Cut Pro had a new project for each set.
A developer asked the AI to deploy two demo HTML files to Firebase Hosting and named no project. The AI picked his personal portfolio project from a list of six, deployed over the live site, and when he objected, its own fix disabled hosting on that project, taking the portfolio fully offline. He restored the site himself and had the demos put on a new project.
He now uses AI for design work and for putting print plans together. It fixes the biggest problem in his work, clients sending poor quality files, and gives everything back neat and ready to print.
Internal multi-subagent code review tool he built has run for half a year and finds serious issues including privacy leaks that humans and open-weight models miss.
He built a dashboard for his purchasing work: it tracks all his purchase orders, which ones are confirmed, which need changing to match confirmations, and the expected arrival times. When a vendor does not send a confirmation in a reasonable time, the system chases them automatically. He says his metrics are better and the job is less stressful.
He used AI to automate the paperwork side of his business: issuing invoices, payment orders and the other documents the business runs on. The work used to take a whole day. Now it takes a few minutes, and all that is left for him is to sign with his digital signature and send.
Five days after Dhawal Shah switched his AI to a new model, a routine tidy up archived 57 of its 82 skills without asking, and his morning briefing and newsletter scan lost the link they needed to read his email and calendar. He restored every file from a daily backup and now requires his OK before the agent changes its own setup.
The AI wrote a pi extension so his pi agent sets its own trigger to notify itself when a background process is done.
Her job is Teams messages and email all day, and brain fog makes finding things hard. She asks the AI to find a file by who shared it with her, and it finds it.
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.
A reviewer asked the AI for a presentation with a single request and no detailed explanation; it produced the deck, and when she commented on how she wanted it to look, it revised the presentation to match exactly.
Opus 5.5 built an imapsync wrapper used for a week-long migration of 5.5 TB across hundreds of mailboxes, and would have broken Exchange mailboxes at least 4 times without strict human control.
He set up a pipeline he wrote himself. Every time he posts an article on X, the AI takes it and posts it to Beehiiv, Substack, Medium, LinkedIn and his own blog, and also does the SEO and Google indexing 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.