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.
Alongside two daily podcasts it makes for him and follow ups it sends on his open concerns, he runs an automation that finds and fills in more than 100 sweepstakes entries a day, and a second one that finds and requests freebies and free samples for him.
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.
Every week the AI scans the market and picks out stocks that look like good deals and ones that look overheated. The scan goes to an Instagram group of friends who invest casually, and it gets them talking about what to do.
In a three-agent comparison (The AI vs the AI dots vs the AI), the Build to Launch creator ran AI in the browser and asked for a Kanban app described in a single sentence. The app rendered and worked: cards could be added and edited.
He wanted an Encased iPhone holster that Amazon sells. Amazon blocks the AI from shopping on its site, so his agent bought the holster from Encased directly. He says this has now happened with three purchases.
Kantar's People Team split HR data preparation into subtasks and gave each to an AI Studio agent: one located documents, another translated everything to English, a third found duplicate policies and drafted formatted versions. Ten agents cleaned, tagged and organized 4,000 artifacts into 400 policy documents in six weeks, grounding the firm's new HR advisory agent.
Liberty RPF's author tested the AI heavily himself after it launched in Canada, but his wife's onboarding was the telling detail: delighted by the mascot, she renamed it, changed its color, and asked it to review her email inbox daily — her first real agent job.
Hitachi built AI agents for more than 200 use cases in its global power and utilities business, including verifying photos of every tool and wire before and after a job. Frontline worker productivity rose 400 percent and safety improved.
Barron's reviewer Josh Schafer told his AI Josh Jr. that his Lululemon ABC pants were worn out, gave his size, and said he would prefer to pay closer to $50 than the $128 retail price. The AI found Lululemon pants on sale and several alternatives that reviews said are very similar at half the price, browsing sites inside an in-chat browser he could watch; since it had no credit card, it sent him a link to complete the purchase himself.
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.
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.