Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
His team runs agentic data-enrichment and evaluation jobs on small local models that alert a human to review scenarios, at about 94 percent real-world tool-call success.
Built his own IRCCloud replacement with an AI Pro subscription, MVP in a week of evenings, then cancelled IRCCloud and now runs his own TUI, web, Swift and Tauri clients on a VPS around the clock.
Zach SB had the AI phone contractors and follow up by emailing photos for estimates, so the whole quoting round happened without him being present.
Pointed Opus with TLA+ at company clustering and failover logic and found and prevented a catastrophic bug no unit test would have caught; Opus also wrote the invariants.
AI coding agents implemented six ways to update a Matter device on real hardware.
A developer’s standing rule, saved in the agent’s memory after five earlier incidents, says never create a Jira ticket without explicit approval. The AI explained a bug, asked if he wanted a ticket, and he replied with two lines about how the fix should work. The AI read that as a yes and created ticket PRE-990. He then had to spend time and effort cleaning the ticket up.
He gave the AI a profile on his Synology NAS, linked over Tailscale by SSH, with one hard rule: never delete anything without his clear say so. The AI went through his large MP3 collection folder by folder. It renamed files, removed duplicates, found album art, fixed tags, and moved songs that were filed wrong, like songs in an 80s folder that were not from the 80s. It also relinked a playlist after he had moved all of its tracks into other folders.
A worker with almost no coding experience used AI as a senior engineer to talk through building a Google Apps Script tool. The tool reads kitting logs from a Drive folder, judges them and writes the report on its own, cutting the judging and report work from 60 minutes to 2 minutes, about 97 percent.
The AI audited the poet's 6,500 Threads posts against the master file for his collection and found 525 poems that had never made it into the file.
A couple keep a shared spreadsheet of shows coming soon, being watched, finished and dropped, plus their thoughts on each one. The AI reads and writes the sheet, adds picks from a list of autumn shows with reasons why they would like them, and will tell them when a show is out.
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.