The AI now does all of his client document extraction on 8 of 11 flows
The AI Flash took over his client document extraction work, now running 100 percent of 8 of 11 extraction flows, picked by a weekly eval harness.
A random mix from the whole library. Shuffle for a new set.
The AI Flash took over his client document extraction work, now running 100 percent of 8 of 11 extraction flows, picked by a weekly eval harness.
Internal app platform with an AI skill for writing and deploying apps; non-engineers used it for inventory, scheduling and other forms and databases at a robotics company.
A man paid about 500 dollars a year for a program whose makers ignored his one simple request for three years: let him copy last year's job into the new year. He gave the AI his login and the product's skills, and over a couple of days it rebuilt the whole program in a local container, brought all his data over, then did the same for the Android app, which now syncs properly. The rebuild cost about a tenth of one year's subscription.
He set up the AI to run locally as his audio engineer. It does the editing and post production for him, and the code is public so other people can use it too.
Writing Rust code faster than state of the art by asking agents to make the code faster.
A team ran an AI pipeline over a usability test of an investment app and saved about half a day of manual analysis. Every claim the AI made about the screen was checked against a video frame, and two claims that did not hold up were left out of the report.
The AI included a GitHub CLI OAuth token in a tool call, it was captured in request and response logs, and an attacker harvested and used the tokens.
He runs a one person business that makes electronics for hobbyists and his customers run several of his devices at once. The AI built a stand alone program that plots their measurements together, the job he had been doing in Matlab, and worked out on its own how data from different products fits together and how to line it up in time.
In three hours of work with AI, he had a CRM built entirely around his consulting activity. He did not write a line of code, he just described what he wanted.
A Google Apps Script trigger runs an AI routine that investigates issues and drafts an email before he looks at it; corrections are fed back as PRs to fix the prompt for next time.
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.