The AI built my test cases and test plan in Azure DevOps
He asked the AI to turn his requirements into test cases and build a test plan in Azure DevOps for his QA team to review. He says the job is done.
A random mix from the whole library. Shuffle for a new set.
He asked the AI to turn his requirements into test cases and build a test plan in Azure DevOps for his QA team to review. He says the job is done.
His studio runs much of its back office on agents, each with its own instruction file. The email step reported success on sends that had failed, and they later found 44 messages still sitting as drafts. Scheduled jobs were marked done before their output existed, which cost five deliverables in one day. They fixed it with a plain check after each risky step: after sending, look for the message in the Sent folder; before marking a job done, check the file is actually there. Now only a failed check needs a person's eyes.
Nari Media's test shows the AI making the initial setup of Facebook and Instagram ad campaigns fast and accessible for media buyers, handling the first build inside Meta's ad tools.
Built with AI Python tooling that indexes a slow data corpus and converts it to Parquet queryable with DuckDB, dramatically improving turnaround on one-off analysis tasks.
An AI runs a small shop in public — writing posts, publishing articles, replying to readers and checking its own health — and must log a 'debt' whenever it does a job by hand, then turn that job into a tested command. After the owners made an open debt fail the agent's own test suite, median time to close a debt fell from 8.2 days to about 6 minutes across 48 debts.
A non technical founder, who spent 25 years in banking, has six AI agents running his small business magazine: a CEO agent, trend scout, researcher, writer, SEO agent and publishing agent. He has caught real errors, including a sales agent that wrote a full report for a fake email address and a CEO agent that burned money by waking up too often.
Ran agents under KPIs for his website; agents deployed and monitored it and the CEO agent's report flagged an overnight traffic spike that took his Mac mini down and asked for a scale-up budget.
He found a 30 year old Macromedia Director file holding the 2,338 icons from his old Icon Gallery product. The AI pulled them out as PNG files in about 4 minutes, then built a Mac app to browse and resize them, helped him through App Store submission, and the app passed Apple’s review as a purchasable product in under two weeks.
Let Fable work overnight on llama.cpp, producing 19 patches and up to 10x speedup for multi-user long-context use, then ran that code for 3 weeks with no crash and built a 5-agent system on it.
Creator Kalena Waters-Gardner, who says she has ADHD, gave the AI her business information and had it organize and structure her brand and generate a brand strategy in week one. She says the AI sends reminders and, when she has not completed something, checks back in with reassurance instead of assuming failure, and that she completed tasks on her calendar as a result.
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.