The AI rewrote his laptop touchpad stack and cut the lag nearly in half
The AI rewrote the touchpad stack on his ThinkPad T14 running Linux and Hyprland. Touch to cursor time went from about 33 ms to about 18 ms.
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 AI rewrote the touchpad stack on his ThinkPad T14 running Linux and Hyprland. Touch to cursor time went from about 33 ms to about 18 ms.
An AppleVis user had the AI file missing American Airlines mileage-shopping claims for two Best Buy purchases made during a tax holiday, pulling receipt data from Gmail. The user got the confirmation email that the claims were filed.
A man built a chat copilot inside Blender in a day, at a total cost of $7.18, then gave it 5 sentences. In 15 minutes and 52 tool calls it built a spaceship with swept wings, a glass canopy, 4 sets of steering thrusters, and 22 exhaust flames, with a full flight animation. On its own it checked every thruster, found the rear ones firing into the side of the ship, moved them to the wingtips angled outward, and checked them again.
The AI and the AI re-created a Tesla data tool in Go from an existing codebase at his request; he has used the new tool for 5 months and it works well.
~500 real cases categorized: money 98 (20%), work 84, admin 60, travel 56, shopping 51; 12 agents joined the first morning. Quoted standouts: $3,500/yr car insurance switched in 5 minutes, $1,900 HOA refund, $44.99/yr forgotten subscription cancelled, PODS booked $576 under quote.
He wrote down what he is looking for in a criteria file and an AI on his VPS does the searching 3 to 5 times a week. It checks job board APIs and feeds, throws out anything it showed him in the last 90 days, and drops a report with notes on each posting into his Obsidian vault, where he reads it on his phone.
The AI and Antigravity took an existing STL and swapped a fan-shroud section for another design by directly manipulating the STL geometry in Python; it went perfectly.
She scans new papers as a science journalist. Keyword hits from her search are sent to the AI, which checks each one against markdown files where she keeps green flags and red flags for each topic, so only papers that fit what she cares about reach her.
On a standing schedule, his agent deletes stale node_modules folders across his projects, freeing about 50 gigabytes each run. He lists it first among the small automations that make his setup feel agent-run.
The AI researched the event, looked at the programme and speakers, and picked a style. In two prompts it made a wide advert video animated in code, then a square version for social media, and added sound when he realised he had not asked for it.
She fed the AI photos of her handwritten family recipe cards and links to her saved recipes, and had it build a five week rotating meal plan with weeknight dinners under 30 minutes. A scheduled the AI prompt now tells her each night what is cooking. The grocery list the AI made was wrong, so she fixed that part by hand.
His company cuts and sews shirts in America from materials bought from many vendors, shared across 10 to 20 shirt styles. Working out the true cost of a finished shirt by hand was a mess. Now an AI automation does the full calculation in about 10 minutes, exact, and publishes the cost to Shopify.
The AI organised a Google Drive holding 110,000 files in 9,700 folders and sent 2,409 junk files to trash.
Using his accounting background, he built a platform for his e-commerce side hustle that scans invoices and receipts, processes payables, pulls revenue in as sales happen, reconciles the daily ins and outs against his accounting software, drafts customer service replies for his approval, tracks stock and costs, and handles month end close and shipping pick lists. It is live, he uses it daily, and he pressure tested it with 30,000 test transactions and load tests up to two million stock entries.
The AI audited the author's family-tree project against documents, removed errors, added newly found documents, and added a generational link the author had missed.
In WIRED's two-week test (republished by Dataist, Sept 24), Instinct cancelled a badly delayed DoorDash order even though the tester had specified cancellation was allowed only if he received a refund — costing him $64. Instinct apologised in detail but, as the tester notes, offers no compensation for its own errors; the loss sits with the user.
Gave the AI a classification task he had been doing by hand and it raised accuracy from 81.3/89.9/92.1 to 90.9/99.3/99.6 in a little over 2 hours.
The Tremendous blogger asked the AI to watch Newark-to-Haneda fares for a January trip. It searched well and found a $2,000 United ticket.
Built a huge toolbox of tools with AI for converting and previewing G-code for his pen plotter, which he uses for plotter images.
Christopher Kokoski set up a fresh AI account as a made-up mystery-thriller author. From one paragraph about the series, the AI wrote its own goals, ideas, and feed, and built a writer dashboard.
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.