An LLM reverse engineered a camera with disassembly tools and got its keys and boot code
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.
429 new ideas this week
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Real things everyday people got it to do, and how to try them yourself.
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The AI recommended a textbook his own project record had already ruled out, after restating why in the same document
In a long-running verification project, the model recommended buying a reference textbook, about $60 to $100, to fill a gap. The project record already contained a finding, written two weeks earlier, that the book could not answer the question that mattered. The model had even restated that disqualifying fact two paragraphs earlier in the same document before recommending the purchase anyway. It was one of four times in a single session that the model asserted or recommended without checking the record sitting in its own working folder. The user had already spent $100 that day on reference material.
This one went wrong. See what happened before you try it.
The AI checked my blogs overnight for the PHP flaw and staged a backup
Worried by the day's PHP security news, he told the AI before bed to look into it and report in the morning. The AI read up on the flaw, checked what his hosting provider was saying, then logged into his WordPress blogs and checked them herself instead of taking the provider's word for it, with a backup already staged and ready in case a fix was needed.
The AI checked eBay GPU sellers for him, flagged a scammer and steered him to the right card
Before he bought a used graphics card, the AI went through eBay listings and seller histories, flagged a scammer quoting $1,450, and steered him to the right 24GB card at $770 instead. He says he would have bought the wrong card, and possibly from the scammer, without the check.
The AI researched Etsy's best-selling Wix templates to plan a resellable product line
In 'Using the AI for Business' Ep. 1, the AI researched Etsy's best-selling Wix website templates using real sales numbers, identified the winning niche and delivery method, and planned a resellable template product line for Jackie (the build itself is Part 2).
Found 4-day beach trip options under $2,000 (Cancun and cruises) via 'Booked
After quitting her job, creator Brittani asked her AI 'Booked & Busy Betty' for a 4-day beach trip under $2,000; Betty returned options including Cancun and cruises, and also helped plan the itinerary, find clothing, and order travel items — with approval required at each step.
$2,000
Agents run his website under targets and flagged the traffic spike that took it down
Ran agents under KPIs for his website; agents deployed and monitored it and the CEO agent's report flagged an overnight traffic spike that took his Mac mini down and asked for a scale-up budget.
This only partly worked. Worth knowing before you try it.
Extracted cinema-ticket details from a forwarded WhatsApp screenshot and added the event
Juan Lombana (verified, 670K followers), reviewing the AI in Spanish, demonstrated two capabilities via screen recordings: a personal-assistant goal tracker (college move-in, golf tee times, movie tickets, trip planning, school-supply shopping, IMAX booking) and WhatsApp integration — forwarding a cinema-ticket screenshot, from which the AI extracted the details, added them to his calendar, and scheduled the event. He compared its assistant-like proactivity favorably to the AI and noted secure payme
Run an $800k resale business with no CPA and the AI reading the ad data
The owner of a roughly $800k-a-year buy-and-resell business describes having almost none: no CPA, no accounting software - the entire P&L is done by hand in one January evening from bank and credit-card CSVs. The one analytic step is periodic: he pulls the ad campaign data, feeds it to the AI, and from its read decides which products to remove and where to increase or decrease spend.
An agent migrated his whole setup to a declarative system, backups included
Migrated a fairly complex setup to NixOS 1 to 1 with an LLM agent and gained declarative services, backups and redeploy tooling.
A marketing chief who cannot code runs a 130 agent system that tripled her blog traffic
A CMO at a business software company designed a marketing system of about 130 AI agents, one per job: researcher, writer, fact checker, critic, publisher. It runs her blog in three languages, LinkedIn for five executives, outbound and SEO, ticking every five minutes and starting work only when something is due. After a year in production it has published more than 630 articles and blog traffic from search is up 3.9 times. Her worst failure was a scheduled job that failed silently for a month; now a weekly audit checks the scheduler itself.
The AI runs my side of my home insurance claim
A pipe burst in his house two months ago. He now has the AI run his side of the claim. It reads the policy, files his living expense receipt scans, watches messages from the insurer, calls out delays, fights coverage decisions, and keeps logs of letters, estimates and invoices.
This only partly worked. Worth knowing before you try it.
An AI coworker handles his mom's wedding venue inquiries and cut the reply time to five minutes
His mom runs a wedding venue in southern Italy and got 15 to 20 inquiry emails a day, each taking 20 to 30 minutes, which was 70 to 80% of her week. The AI coworker he built now works the inquiries inside her 10 year old booking system, which has no API, and she approves only special quotes. After three weeks the typical inquiry is processed within 5 minutes and the system saves her over 120 hours a month for about $350 a month.
Tracked when tickets go on sale for events like the US Grand
Austin Evans, a verified tech creator (510K followers), showed his AI 'Lotus' tracking when tickets go live for events such as the United States Grand Prix in Austin, alongside a Collectibles Tracker database and morning tech-news briefs. The AI asks permission before big actions, remembers his routine, and proactively offers help.
A product manager agent watches his other agent sessions and fixes the problems they report
A dedicated product manager agent session running locally automatically prioritizes and fixes harness issues reported by other sessions and coordinates fix deployment, no regressions so far.
The AI packaged software for Slackware and the package ran
As a test he had an AI harness package GNU Bison for Slackware. The harness built it under QEMU following the distro's packaging philosophy, and the resulting package installed and ran.
My weekly the AI routine failed three weeks in a row and I lost the numbers for good
His weekly the AI routine was meant to pull Search Console data and check whether a big content change worked. It needed a Google service account key that only he could create, so it failed three weeks running in exactly the same way, and the three week comparison it was meant to take can never be taken now.
This one went wrong. See what happened before you try it.
Laid off on Tuesday. The AI built my game and it was live by Wednesday breakfast.
His role was eliminated on Tuesday morning. That evening he asked the AI for something fun, and by 9 PM there was a 3 stage 16 bit co-op game where the hiring process is the final boss. By 6:37 the next morning it was live on the internet, with 38 commits and 325 tests in a public repo.
The AI ran a scavenged GPU fleet for 10 days to factor a record-size number
The AI ported CADO-NFS to GPUs and orchestrated a fleet on scavenged idle capacity, running about 30 GPU-years over 10 days to factor RSA-260.
Switched phone plans from $115/month to $50/month after a usage audit, saving
The creator of the 'TRICK #29 - MUSE TRICKS' reel was paying $115/month for an old unlimited plan with 20GB data he had not changed in three years. The AI analyzed six months of real usage (averaging 4GB, no hotspot, zero international calls) and recommended a $50/month plan on the same network with the same coverage.
$115
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.