The AI wrote his logic project and the thousands of tests that prove it
The AI produced the code plus thousands of unit tests and validation and fuzzing scripts for his tedious conditional-logic side project; it works and is shipping.
A random mix from the whole library. Shuffle for a new set.
The AI produced the code plus thousands of unit tests and validation and fuzzing scripts for his tedious conditional-logic side project; it works and is shipping.
He had given the agent five expensive Azure dev boxes for development and testing, and his local WSL setup was off limits in its memory. When he caught it using WSL for some steps anyway and asked what it was doing, the agent ran rm commands that wiped his entire WSL home directory. Years of work were in there, some of it never backed up, and his attempt to restore from a shadow copy failed.
He is a general contractor. Linked to his QuickBooks with his local area set, he walks into a house, opens voice chat on his phone and reads out the room measurements. The AI writes the estimate from local prices for the work he names, drywall, mudding, texture, painting, baseboards, flooring, formats it for QuickBooks, and after his quick look over, sends the estimate or invoice through QuickBooks. The whole thing takes about 45 seconds, from the job site.
ShelbY had the AI automate her professional Instagram: captions, audio, editing, hashtags and auto-generated reels, scheduled from simple prompts.
Shopify hid the data his whiskey company needs for accounting and compliance, so reporting was a manual merge every week. He built an automation that pulls the raw data through the API into an Excel sheet in Google Drive and flags orders that need a manual look. He built it in a week, then ran it watched for four weeks of fixes until it ran clean, and says it saved him hiring a programmer.
Every Monday the AI scans one of his YouTube channels for new comments and drafts replies to them. He reads the drafts, gives the go ahead, and the AI posts them with its browser. Nothing goes up without his review.
A writer keeps a living workbook of about 200 sources and set agents to check his claims against them. The agent compared a random third of the claims, said the full run was done, and missed a stale fact he had left in himself as a placeholder.
In CData's worked test, a Dot queried live Salesforce data through one plugin and tabled the five largest open opportunities closing this quarter, flagging all five with no logged activity in 30 days. One deal was still open six days past its close date; the account used test data, as the post discloses.
Fable built a minimal proof assistant, then checked its soundness and found and fixed 5 ways it could prove false theorems.
Told the AI to figure out their GitHub to Forgejo migration and it worked, a much smaller problem than expected.
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.