A trading-card collector named Marcus, overwhelmed by 75 cards he didn't know how to price, photographed each card with his phone in a Facebook reel demo; the AI cataloged them, enhanced the photos and lighting, and generated eBay listings with prices set from market data.
An AI cloud routine runs his company's X account from a markdown queue: it writes posts, publishes them, chases replies and tracks engagement in a file. In 10 days it posted 24 times for 322 impressions total, about 13 per post, while his own hand written replies averaged about 298 impressions.
This only partly worked. Worth knowing before you try it.
The solo maintainer of the karasu modeling language runs dependency updates through an AI skill that investigates each Dependabot PR before anyone merges: release notes, the diff between tags, publisher or ownership changes, install-time scripts, lockfile edges and known advisories, written up as merge, hold or reject recommendations in a design doc. In the week of Oct 10–17 three triage rounds fed 88 merged PRs (16 from Dependabot) and 12 architecture decision records, and the process caught a rebuilt lockfile silently moving a package off the reviewed version.
A consultant runs 21 the AI jobs, all switched on. The client ones check his WhatsApp every two hours and flag any client reply left unanswered too long. Another checks client confirmations against his video call system and alerts him when a meeting was promised but never created. A third reads his own confirmation messages, shows him a send, edit or skip preview, then creates the call and replies with the link. Draft replies are prepared the same way and only go out after his tap.
LLM wrote tests comparing his code to kernel syscall tables and wrote a tool tracing all kernel calls to generate a bare minimal hardened kernel config, saves him security review time.
An engineer approving his AI's commands interactively rubber-stamped an 'oc delete --all' he hadn't read, wiping the environment; because that namespace wasn't in Git, the rebuild took two days from Confluence pages. Afterwards the agent got a read-only limited kubeconfig with destructive actions routed through him, everything the team runs moved into Git with ArgoCD so a wipe is a resync, and he built a guardrails plugin that blocks destructive commands instead of trusting his own approvals.
This one went wrong. See what happened before you try it.
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.
He set GPT-6 to read tens of thousands of his emails, his writings and his calendar appointments from his recent career. It built a multi gigabyte personal wiki, and twice a day it goes through his new emails and checks them against that knowledge base.
Stuck on a small plane with no Wi-Fi, he wrote a post for Friday on his phone. Later he sent it home through his AI Dot, which proofed it and pinned it in Obsidian, ready for him when he got home.