The AI checked 5 years of our JIRA bugs in under 30 minutes
Going through five years of his team's JIRA bugs looking for patterns would have taken him about two weeks. The AI did the analysis and collation in under 30 minutes.
A random mix from the whole library. Shuffle for a new set.
Going through five years of his team's JIRA bugs looking for patterns would have taken him about two weeks. The AI did the analysis and collation in under 30 minutes.
A university worker used AI to build a web version of a transcription program that used to need a special Windows machine reached by remote desktop. The new tool pairs a speech model with speaker detection on the university's own systems. Twenty minutes of interview audio now transcribes in 40 seconds with the speaker changes right, and students and staff can use it from a browser.
The AI built him a set of local jobs on a Mac mini, and no model runs inside them. New Todoist tasks print as small tickets within half a minute, and at 7:30 each morning a brief prints and arrives by email with the day's calendar, overdue tasks, weather for two towns, and two clients' numbers from the day before, each set against its seven day average.
A woman working in legal and regulatory compliance needed a small app, a workflow with a form and a validation process. Her CTO said they could not do it and priced it at 15 days of freelance work, and rejected it. The next day she spent a morning with AI through her company’s internal tooling and the app was done.
Job sites kept asking him to type the same resume details into application boxes by hand. He used AI to move the information from his resume into the boxes for him.
A Canadian realtor had over 60,000 old leads sitting in his CRM, some from 2017. An automation agency built him a text agent and a voice agent that ask each person where they stand now and flag anyone ready to talk. Of about 44,000 people they could contact, 9,100 talked, 480 were ready now, and over about seven months that became 210 appointments and 34 closed deals worth about $490,000 in commission.
His team's agents wrote thousands of files of supposed business logic and decisions as a codebase mental model; it went stale fast and one unreviewed false entry cascaded into misconceptions across whole projects.
A field service worker loaded the AI with every user and service guide for the products he repairs, plus all advisories and known issues. He runs each job's action plan through it: The AI checks the parts are on the original parts list, flags advisories, and builds a step by step PDF for the repair. On a product he barely knew, its diagnosis named a different component than the plan he was given. After six hours with his engineering team he followed the agent's call and it fixed the machine.
Got the AI to build a focus app for his Mac; he uses it daily and says he does more good work with it.
The creator was paying over $1,300 a year to SiteGround and GoDaddy to keep 8 websites and apps online. The AI moved all 8 to free or near-free hosting, his whole Google bill is now about $1 a month, and the AI stays on as his site manager.
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.