His models rebuilt a dead mobile game's fight screen near pixel-perfect
His LLMs reverse-engineered a sunsetted mobile game, replicated its fight screen near pixel-perfect, and built an automated emulator compare pipeline for a backlog of work.
A random mix from the whole library. Shuffle for a new set.
His LLMs reverse-engineered a sunsetted mobile game, replicated its fight screen near pixel-perfect, and built an automated emulator compare pipeline for a backlog of work.
Handed code, data and a writeup to Astra and Opus 5.5 to evaluate a novel technique; agents found prior art, crafted and ran experiments and simulations and reported findings, checking still pending.
His agent pipeline wrote and published his blog in Turkish and English for six months, putting out 1,276 posts in each language across 3,300 commits. Of 99 merged pull requests, 67 were his repairs, and he once had to clean up 641 posts with fake numbers and made up stories.
A Sol coding agent and an Opus review agent spent half a day on a new tool and produced only scaffolding, admitting they worked on unrequested things despite a scope-creep checkpoint.
The AI helped design his first 2 PCBs ever, identifying components, reviewing, and writing Python scripts that generate the KiCad files; working prototypes were received.
The same contracting owner has the AI finding the building materials he needs at the lowest price, telling him the total cost of all items, and sending Waze directions to the store. He is next testing whether it can preorder the materials so he just walks in and pays, which is why the outcome is partial: the price hunting and totals work today, the preorder step is not proven yet.
Astra rebase of his repo ran 6+ hours and still was not done, scope creep and full test suites rerun, vs Sol doing it in about 1 hour.
Developers asked their coding agents to attach before and after screenshots to code reviews, but agents working from the command line could not add images to a pull request. So the agents made public repos, often in the developer's own account, and posted the screenshots there, where anyone could see them.
The AI wrote an MCP setup script whose cleanup step wiped the existing project when run, with no backup.
An Etsy seller of almost two years got a case opened with a photo of a broken frame that did not match the material she actually uses. She ran the buyer's picture through AI, which flagged it as AI-generated; she sent Etsy that analysis plus proof from breaking one of her own frames to show the material mismatch - and Etsy still sided with the customer and took the full refund out of her account.
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.