Chase my unpaid invoices like a head of accounts receivable
The user made the AI the business's head of accounts receivable: it emailed every partner with a pending invoice and got weeks of stuck payments moving.
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.
The user made the AI the business's head of accounts receivable: it emailed every partner with a pending invoice and got weeks of stuck payments moving.
Composer 2.5 created an uninstall.sh doing rm -rf on the home variable and actually ran it on a real home folder.
AI agent Rosey in a family iMessage chat does meal planning and Walmart grocery shopping via BrowserMCP.
Answering a what are you using it for thread, he lists what the AI does for him and puts this first: it just negotiated his AT&T bill down $50 a month. The same comment lists a weekly fantasy football newsletter, a running coach role and constant email organizing, which are separate uses and are not part of this record.
After years of spreadsheets and a vibe-coded app, a parent built an AI system (reported on X, via WhatAgentsCanDo, Oct 7) that maintains the family recipe library in Markdown, prints a weekly plan of about 15 meals, and produces a section-grouped shopping list. The list is pasted into AI to fill Instacart, with checkout still human; the bot template is shared for reuse.
Spencer Hakimian had the AI search for money owed to him and file the claim start to finish. The post shows the New York State unclaimed funds letter confirming $2,202.00.
During a long pull-request review session, the AI wrote a Python script to replace one function in a large test file, bounding the replacement at the next top-level 'def' instead of the function's real end. The span swallowed 17 unrelated test functions, which were deleted silently; the model noticed only afterwards and rebuilt the file from git.
Creator Eric Siu had the AI build a 'Japan in Bloom' itinerary for March 27–April 7, 2027 covering Tokyo, Hakone, Kyoto, Nara, and Osaka, generated from his saved Instagram posts for cherry-blossom season.
An LLM created his spec-driven development harness, iterated until it worked as wanted; it is now used with the spec as the source for code changes.
The AI ran a protein-design pipeline at home on a 5090, chose similar tooling, and generated about 100 trajectories running 24 hours.
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.