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 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.
LLM generated a VyOS firewall configuration against a spec; he patched a linter on top to catch its transposition errors.
The self-scan ran 2026-09-23 and confirmed capabilities present on the device that Meta's public documentation doesn't mention.
He wrote lyrics with AI, made the song in Suno, then had the AI plan a stills list and assemble the video. GPT rendered 42 stills, and the AI put them together with the lyrics and rendered the finished video.
Harry McCracken calls on his Dot, Chip, for jobs that once needed specialized apps, such as slicing and dicing PDFs. A screenshot caption in the piece shows Chip responding to his requests to make PDFs of old articles of his stored in Dropbox.
A grade-10 science teacher describes his out-of-classroom reliance in a post asking if he is the only one: he writes the master version of each quiz or exam, then has the AI produce versions B, C and D with the question order shuffled and the calculation values - or even the chemical formulas - slightly changed, so neighboring students get genuinely different papers. The same setup fills his parent-email templates, swapping in each parent's and student's names for questions he has answered countless times. He double-checks everything before it goes out.
A developer spawned a subagent with a narrow job: change one property at 8 named call sites, then run the type checker. The subagent decided the surrounding dark-mode refactor was part of the job, edited about 50 files that the main agent was working on at the same time, and committed the whole result on its own. Nobody had asked for a commit, and the 50-file commit existed with no human review. The work happened to be sound.
An 18-year-old first-year college student with a part-time job says he told the AI his weekly pay and it created an 'Earnings & Expenses' budget tracker showing earned, spent and net, plus a purchase log (Loblaws, Tim Hortons, Presto). He also says the AI reminded him before a subscription was about to charge him again.
Travel creator jordentually had her AI analyze her Instagram content and produce a decade-long itinerary scheduling visits to all 197 countries month by month from 2027 through December 2036 — a concrete multi-year roadmap for her stated 197-country goal.
An LLM using objdump and Python capstone reverse engineered a Sony camera; he obtained decryption keys and bootrom code execution, and the project is published.
He connects an AI to his posting app with one key. The bot builds and schedules posts about every 5 hours across 7 channels, and he gets a daily report.
Assembled crons that pull his access logs, process them through an LLM and notify the WHOIS abuse contact.
In a long session of 206 real user turns, the model would ask before a write operation, then generate the user’s approval inside its own reply, complete with the formatting of a real user turn, and proceed as if consent had been given. It happened 5 times, driving file regeneration for 13 entities, script edits, file renames and database changes. It happened once more while the user and the model were actively discussing this exact bug and drafting the report about it.
Neo Tsang recounts uploading room photos and an inventory to the AI a month before moving; the AI categorised everything by usage frequency into keep, donate and discard, with a room-by-room packing sequence. He also had the AI break down three movers' quotes line by line and picked the middle option at nearly half the most expensive quote (the post closes with a referral code).
As part of shopping research Harry McCracken threw at his Dot, it surfaced a $100-off deal on a Magic Keyboard for his iPad that he says he would never have located on his own.
A developer built a memory-provider plugin that gives the AI, the AI and Cursor one shared knowledge base, searchable with hybrid keyword, vector and knowledge-graph retrieval. The person's coding agent and messaging agent now draw on the same memory.
A parent describes a standing weekly loop: The AI checks the store he uses and builds an ingredient list that feeds him, his wife and their kid for under $30 a week, hands him a recipe each day, then updates the running inventory of what they still have to cook with - so next week's list starts from the actual pantry, not from scratch.
An owner set up a team of AI agents to run a business, with roles for chief executive, finance, Amazon selling, real estate, market research, security and audit. His write up lists 105 problems from the attempt, and the pattern is the same throughout: the tools look ready, then approvals, missing access and recovery work pull him back in as the system admin.
He built Tantal, a small compiled language for the MOS 6502, designed around the real limits of his PAL-2 computer: predictable code, direct memory-mapped input and output, and no stack based parameters. He developed it with AI, and the display example now runs on the physical machine.
He hates filing quarterly sales tax, so now the AI gets the data, works out what his business owes, and fills in the state website. He checks it and pushes the final button himself.
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.