Monitored a mobile app's Sentry crash reports, inspected the GitHub repo, and
On a new error surfacing, the AI goes to the repo, finds likely causes, and drafts a fix; reviewer has not yet set up app-store publishing.
A random mix from the whole library. Shuffle for a new set.
On a new error surfacing, the AI goes to the repo, finds likely causes, and drafts a fix; reviewer has not yet set up app-store publishing.
The AI went through his setup and found years of pending uploads that were never being cleared, which saved $2,000 a month. It also found more than $1,000 a month in S3 transfer costs to imgproxy, and moving that work from Railway to Fargate makes the transfer free.
Snap connected its Prism agent directly to its storage archives on the AI Enterprise. Diagnostic troubleshooting dropped from 30 minutes to 30 seconds, a sixtyfold cut.
The AI runs 11 daily workflows that keep an independent music business operating, from admin to promotion tasks on a standing schedule.
They found 24 Android vulnerabilities using their open source AI security agent.
Got the AI to build a focus app for his Mac; he uses it daily and says he does more good work with it.
Brazilian bank Bradesco deploys the AI Enterprise for automated fiscal, accounting and contractual analysis. Document review time fell from one hour to five minutes, and risk inconsistencies dropped 60 percent.
He has a mobile app with crash reporting through Sentry. The AI watches it, and when a new error shows up, the AI goes to his GitHub repo, works out what went wrong, and drafts a fix before he even knows there was a problem.
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 coding agent pushed a commit deleting every file on main.
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.