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.
Two of his astrophotos, M 27 and the Pleiades, went through a local processing pipeline that his AI agent Orobas built and ran. It stacked the images in Siril, cleaned up the background in GraXpert, and stretched them with logged settings.
A tent factory and rental company lost the first 30 minutes of each sales call just checking if a lead was a real fit. Its WhatsApp agent asked the technical questions, dropped poor leads, and handed ready leads to sellers, and buyers who spoke with the agent converted at 3.54 percent against 0.56 percent for others.
Commenting on the Top 20 post, he says he is in an office football pool where you rank games by how sure you are of the outcome, and he kept forgetting his picks and found it a chore. He gave the AI his login and they worked out rules together: The AI makes his picks each week based on Vegas point spreads and analyst information. The pool site has an awkward interface, and he says the AI handled it well.
The studio had the AI and PixelLab make one sample icon and waited for their OK. Then it made the other 24 in the same style, plus the gray locked versions Steam needs, for a demo at Next Fest in October.
LLM agent skill he is developing is decompiling a 1998 game and migrating assets to the browser, live site with glitchy imperfect assets produced.
Hibbett's Agentforce shopper agent handles 90 percent of core shopper journeys after a six-week rollout, per Salesforce's release.
The same studio's agent Timmy orchestrates more than 20 tools to turn blog posts into short videos: Veo generates scenes, ElevenLabs synthesises a custom voice, and automated captioning, lip sync and final assembly finish the piece. The pipeline runs inside the studio's normal the AI production setup.
LLM-generated Spotify client he built for himself, uses every day, and maintains, fixing bugs and closing others' PRs.
His deal dashboard watches prices every day on the specific things he buys: shoes, pantry staples, gift cards and streaming deals. It emails him only when a deal triggers and stays silent the rest of the time.
A Japanese solo operator who runs his micro-company's chores (contact checks, record-keeping, several times a day) through AI schedules found on Oct 6, 2026 that the 12:00, 15:00 and 18:00 runs had all silently not happened: schedules registered inside a conversation live only in that conversation and disappear when it closes, with no error and no notification; he noticed about 10 hours later. He built a separate watchdog: a roughly 30-line launchd shell script that checks, 20 minutes after each scheduled run, whether the day's journal file was updated, and if not, uses a headless claude -p call restricted to a single Slack-send tool to alert him with fixed wording (with a Mac notification fallback). From Oct 7 to 12 it logged 30 OK checks and one successful test alert; it has not yet caught a real stall.
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.