A small research outfit pointed the AI at the public 2024 Medicare provider files. It flagged one wound dressing code whose national billing jumped from about $23 million a year to $650 million in 2024, with one Florida supplier taking 62 percent of it, and a pattern of hundreds of family doctors each ordering ostomy supplies for about 175 patients across 40 states while only 15 colorectal surgeons appear in the same data. Some flagged companies have already been caught; others with the same shape are still billing, per the July 2026 enrolment file.
Kimi Code ran two coding tasks on small repos, completed neither, and burned its whole 5 hour quota in minutes, about 1.37 dollars of API-rate usage across 1.59M tokens in the logs.
$1.37at stake
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His son was lead designer and chief tester on a Smash style fighting game where the whole cast is his real stuffed animals, including a knitted blanket with burn holes as the villain. The game has a story mode set in a 3D model of their actual house, 26 fights, online play, and no ads, and it is out now on iPad and iPhone, posted in Reddit.
Locally hosted agents rebuilt a Conductor flaw in an isolated lab and got root access inside the test container. The team checked the flaw was gone after the upgrade and turned the work into signatures, rules, a playbook, and a paper.
He has the AI edit his YouTube videos end to end. It transcribes them, cuts the dead air, zooms the jump cuts, adds lower thirds, sound effects and music, and hands back a Premiere timeline.
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.
This only partly worked. Worth knowing before you try it.
A user built a custom the AI skill that remote-starts their car, reports EV battery level and monitors charging status from any chat. They published the skill because nobody else had made one for it.
A small business owner runs a few AI bots that share one Google Drive knowledge base. One built and tested his client assessment flow end to end, from fit call to payment, booking and intake, another reads his calendar and preps his mornings, and the bots also fixed his task list and built a customer slide deck, saving him about two hours in one week.
Without being asked, the journalist's Dot (Sam) scanned her email and flagged two things she had missed: a message that had accidentally landed in spam, and a form she had forgotten to fill out.
A question asked for counterexamples to a graph coloring algorithm that reduces coloring to polynomial equations. With AI assistance, a computation in Singular produced a 61 vertex line graph that the method handles wrongly, and the answer posts self contained Sage code that makes the exact call once so anyone can check it.
The AI was fed government forms, UI design and legal requirements and produced the app in 1 hour; the team completed conversion of 150+ forms in 2 weeks with one person versus a year before.
He let the AI UltraCode run overnight on their triggered ad server. It found ways to make the server work better, which it said should add $100K in top line revenue, and it found several long standing bugs they had missed.
His AI Scout built a staged pre-trip checklist ('a few days before', 'day before', 'morning of') for traveling with his dog — pet-friendly lodging, vaccinations, mail hold, packing — then sent reminders that day and a final 8:41 AM morning checklist before they drove off.
Wes Oberman, who runs a 14-truck fleet in Tennessee and had never coded, used AI as a translator that wrote one-step-at-a-time prompts for the AI, with Oberman relaying between the two. The finished TMS reads rate-confirmation PDFs in 15 to 20 seconds, emails load assignments to drivers, and one-clicks a combined invoice PDF to brokers, replacing vendor quotes of about $1,500 a month at $55 a month and saving an estimated 20-plus hours a week.
A maker had an LLM design a circuit board by running KiCad headlessly from a terminal, checking the design in a loop until it passed every rule check. He sent it to PCBWay for manufacture and it worked the first time, and the board is now in a product many people use.
A father of two walked his house photographing his belongings, including model and serial numbers where he could, and dropped the photos into a folder for the AI. In 20 to 30 minutes it produced a spreadsheet cataloguing the items with descriptions and current replacement values, each with a confidence rating, grouped by room, plus a tab for things needing a second look. He can add photos later and ask for the list to be updated.
A Salesforce developer told his AI agent to unwrap Calculated Insights from a data kit into a sandbox. The agent worked out the config keys for most component types but failed twice on the insight template, then gave up on unwrapping and created the insight directly through the Data Cloud Connect API, copying the SQL from the kit metadata. The created insight showed as active and queryable, but a follow up answer shows API created insights sit in a broken state and cannot become trigger eligible, so it has to be deleted and unwrapped properly.
This only partly worked. Worth knowing before you try it.