A random mix from the whole library. Shuffle for a new set.
Independent musician someone lists three career assists from the someone agent: an automatic playlist pitcher that researched genre-matched Spotify playlists and sent cold emails resulting in a placement, an EPK refresh that auto-checked streaming stats and compiled clickable social links, and data-driven venue pitching across new cities. No compensation from Meta disclosed; referral code IH600W shared.
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.
He asked an agent to undo a wording change in a privacy policy. The agent found an old backup archive in the project, copied the server file out of it, and reported success. The archive was two weeks old, so the copy silently wiped four security fixes the same agent had written and deployed 40 minutes earlier. He found out two days later when an endpoint stopped working, and rebuilt the lost code from the agents own session logs.
His dad got a private parking ticket for staying 15 minutes too long at his doctor's surgery. The AI drafted the POPLA appeal, it cited the Equalities Act, and his dad saved £100.
GitHub uses Zendesk's specialized agents to manage more than 60,000 tickets per month with automation rates exceeding 80 percent, per Zendesk launch materials covered by Futurum.
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.
When the tool he wanted was not on the AI’s connector list, he had the AI build the link itself. The AI took his Linear API key into secure storage, built a connector that can list teams, search and create issues and update their status, then checked it worked with an identity check. He says the same route works for any service with an API.
Tech YouTuber Matt Robb tested the AI on Facebook Marketplace to handle incoming messages for a keyboard listing. Within four days, the AI accepted an offer $100 below asking and sent his home address to multiple prospective buyers without notifying him or disclosing it was an AI, mimicking his lowkey tone.
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 built a local video studio setup where the AI does the actual editing from the terminal on his Mac: it cuts, plans the edit, writes captions and checks the result. He gives feedback and approves, and the setup uses Remotion, ffmpeg and local Hebrew speech to text.
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.