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.
A 29-year-old on Facebook demoed the AI inside a Messenger chat two days after his birthday: he typed requests to create a Facebook Marketplace listing and verified that the AI remembered his standing preference to keep his home address out of listings.
Every day the AI checks Club Studio's FiDi listing, the building site for 59 Maiden Lane, and local opening news. The gym is still shown as presale, so the AI stays quiet and will tell him as soon as a date is announced or the location opens.
A reseller describes his valuation stack in a thread mocking casual the AI pricing: the AI identifies an item, its condition and model numbers; that feeds a sold-comps subscription and his internal database through Python to build a comp list; then a second classifier AI judges how closely each comp actually matches before the system takes the low end of the surviving comps and calls buy, watch or pass. He is blunt that naive copy-paste pricing pulls stale comps - the pipeline exists to fix exactly that.
A software engineer delegated job-search operations to his personal AI agent running the career-ops system as a command center, under a hard visa-sponsorship deadline. Over eight weeks it evaluated roles, tailored CVs, tracked 21 serious applications and prepared interviews, ending in 7 interview processes, 2 offers and an accepted role in Amsterdam.
He needed a book converted from epub to PDF so his annotation workflow could handle it. After 20 minutes failing with websites, the free the AI did the conversion in 10 seconds.
His morning agent reads his email and builds a prioritized to do list with time blocks for the day. It also checks the weather and warns him to leave earlier when rain would slow his trip, which has twice saved him from showing up soaked.
Astra failed for 2 days building an AI skill to control a robot tank arm, wrong servo, gripper and gimbal calculations, could not lift socks, about 50 pounds in credits burned.
ESPM professor Wilson Silva had his AI agent research ten auto repair shops, send them photos and videos of his car, request quotes and rank the options while he worked. The chosen shop's owner later testified on video that the agent even tried to negotiate the price down.
Her healthcare provider texted her to press 1 to confirm an appointment, she drove 2 days to get there, and it turned out to be an error, with no apology. She used three AI tools, mostly the AI in Word, to sue the provider.
He had it sign in to his Costco account and work out how often they buy each thing and which items they stock up on when they are on sale, so it now writes the family shopping list and sends it to his wife for edits. At Vons it signs in and loads the cart itself; he only checks out and picks a pickup time.
A builder created an agent skill that files a user's saved Instagram reels into topic collections. It was battle-tested against a real backlog of roughly 3,280 saved reels, which it sorted into 13 collections.
A user was filing a housing co-op’s HPD property registration with AI’s help. Asked whether the $13 registration fee had been paid, the AI said it had been or was not required, based only on a generic billing disclaimer, with no payment record behind it. Asked why a mailed form arrived after the deadline, the AI stated as fact that the deadline runs from the postmark, a rule it had not checked. Both claims were corrected only after he challenged them. A late filing for a building can draw a civil penalty in the $500 to $5,000 range.
He had the AI build a website for his friend's painting company, then guide him from GitHub to Cloudflare and finish the SEO. His friend can now get changes made just by asking the AI, instead of paying someone each time.
Creator Derek Cheung used AI in one sitting to build and deploy a shopping agent, then gave it a goal and a budget: a home studio under $2,500. The agent shopped live prices, buyer reviews and photos across stores and returned a sourced parts list under budget, with an AI review summarizer on top.
He had the AI answer a Slack notification from a Datadog monitor. The AI checked the issue through Datadog MCP, found the right Slack group to ping, and sent a summary of what needed fixing.
Creator Arlicia Jones describes the AI automating her grocery shopping, saving money, cleaning up her email, identifying refund-eligible items, and building a working automated bot. She promotes the service with a referral code (ND6YC6).
His bookkeeping for a full calendar year was a trainwreck, and he needed to move accounting platforms, tidy the previous year up and prepare for an admittedly late tax return. Fable built a proof of concept migration in less than two days: it set up hosting, automated the spend categorization and got the new platform displaying his previous year’s books. When Opus 5.5 came out, it reviewed the work, caught several discrepancies in the data and corrected them, and also stood up two other self hosted accounting tools for him to try. He still hated the platform he had chosen, because it was over complicated for his needs.
A three-person flipping operation runs on a custom app steered through AI over MCP: it identifies what is actually inside vaguely described government surplus lots by hunting service tags in the auction's spreadsheets and model numbers in its photos, values each lot against sold comps, and overlays a buy/watch/pass call with a max bid on GovDeals as they browse. It also ranks repairs by ROI, turns SD-card photos into listing pages that a human approves, and prints a pack-in sheet with QR ads for their other listings when something sells.
Her AI logs meals from photos, tracks workouts, and produced a Week 1 report with average calories, protein, activity days, deficit and pace; it pings her three times a day for water and generates weekly and monthly reports.
He was about to pay about $700 for a Mac mini at Micro Center on his usual card, which gives 1.5% back. The AI reminded him that his US Bank card was paying 5% back at electronics stores that quarter, so he got $35 back instead of $10.50. The AI also logs into his card portal and turns on all the store offers for him, and pings him before good offers expire.
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.