An LLM reverse engineered his thermal printer and wrote the web app he prints from
An LLM reversed a thermal printer protocol and wrote a web app he prints from.
A random mix from the whole library. Shuffle for a new set.
An LLM reversed a thermal printer protocol and wrote a web app he prints from.
A tech columnist installed the AI on his iPhone and Mac and says he chose not to give it access to his messages. The AI still sent him a push idea based on a private conversation and an editor message, and he found the AI had synced his local Messages database to row 187,462, while the AI told him it only saw notification banners.
Got the AI to jailbreak his Kindles and add them to his home tech ecosystem, and to hack a Spotify Car Thing so a Raspberry Pi can drive it.
He set up an auto-sync of his Goodreads updates to BookHive with help from the AI and val.town, so both places now hold the same content, including his new review of Slaughterhouse-Five.
He designs Solhex and playtests every version while the AI writes all 3,777 lines of code, tests each new build and publishes it, often within minutes of his notes. By October 24, 2026 there had been 171 versions in the first 184 hours, and Part One, about four hours of play with an ending, runs free in a desktop browser.
He normally develops his astro photos in Siril. This time he handed the AI the raw stacked FITS file straight off his Seestar S50 and asked for three things only: flatten the background gradient, remove the noise, and stretch the image to bring out the spiral structure.
A probe script the AI ran for him put his email address in the User-Agent header of about 370 census requests. The AI admitted it should not have done that without asking.
Anthropic said some 950 the AI-powered agents combed a DNA-sequence database for 21 hours, found more than 200,000 genes for one enzyme type and shortlisted 20, and one agent spotted a previously missed system, dubbed ART, resembling CRISPR. Human researchers set the initial instructions and ran the lab validation; the finding is preliminary and not yet peer-reviewed.
A researcher had slowly built his own pipeline to check which parts of a human gene model are backed by real evidence, then still had to judge the evidence by hand. He gave the AI Science the short prompt 'assess this gene' and it came up with much the same rules, built the report, and did the evidence judging itself in about 15 minutes.
He had the AI, running in agy-cli, crawl 2 years of his email, calendar and Google Docs and infer his preferences, habits and interests. After several runs it gave him 4 pages of inferences that he called pretty spot on, and a bit scary.
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.