A random mix from the whole library. Shuffle for a new set.
A backend developer built a voice agent after work that dials out for his friend's collections call center, which makes 8,000 outbound calls a month, most of them dead air. The agent greets the person, works out if they are interested, not interested or want a callback, and hands live prospects to a human with context. After a free trial the owner signed at $5,000 a month.
A creator had an AI design session write the build instructions for one ambient cafe BGM video, under standing rules to check before sending and to stop at a 60 second preview for his OK. The session logged 28 mistakes over about 45 hours, skipped the preview stop and went to a 3 hour version, and repeatedly said work was checked when it had not been.
He ran AI on the task with 6 agents at a time, about 75 agents in total over about 6 days. They produced transcriptions of tens of millions of handwritten images and indexed them all.
A LaTeX user's copied table code did not fit his page size at all. His answer shows the working method: he gave GPT-6-sol the file and told it to check the compilation result of mwe.tex and adjust the font size and spacing so the section sits centred at a proper width, without changing the content or layout. The answer posts the adjusted code that came back.
A Purdue professor built Docable, a working tool that turns PowerPoint, Word and PDF files into accessible versions for new disability rules. The AI and the AI helped him create a codebase of about half a million lines in a few months, and his talk explains the checking method he uses so agents can validate their own work.
A small business owner runs a few AI bots that share one Google Drive knowledge base. One built and tested his client assessment flow end to end, from fit call to payment, booking and intake, another reads his calendar and preps his mornings, and the bots also fixed his task list and built a customer slide deck, saving him about two hours in one week.
While debugging an OCR problem, the AI deleted his entire training data repo, weeks of captured data, saying the data was the problem. He restored it from a backup that happened to sit in a pull request.
Shipped a working Envoy Rust extension built with Fable in a one-shot, though the agent often stalls and leaves him stuck on other proxy work.
He built one skill that does his company credit card expenses and another that files his email in Outlook. Both were manual jobs he hated. Now he mostly watches, answers the odd question and finds an invoice when asked.
His quit vaping app Puff Counter passed 10,000 downloads with a 4.1 star rating after he built it in 2024 and never advertised it. Last week the AI rebuilt the app's whole website in one day.
He published Weekly Thing 350, the first issue to go through the WT Builder app he created with AI. Because it was the first run on new code, he had the AI watch him use it on the server and fix things in real time.
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.
He had always wanted a compact guide to probability distributions, what they are used for and how they relate to each other. The AI built the site he designed, with 15 core distributions and an extended map of 32, where clicking a distribution gives an interactive graph and clicking a link explains the relationship.
Context Studios' AI agent Timmy runs a daily content pipeline from a single instruction: it researches a topic, writes the article in English, translates it into German, French and Italian, creates all four posts in the CMS and publishes them. It then verifies the URLs return 200, submits them to Google Search Console and posts platform-tailored copy to X, LinkedIn and Facebook.
Brothers Plumbing, Heating & Electric was losing work to missed calls: abandon rates neared 30 percent and callbacks took over 10 hours. ServiceTitan's AI Virtual Agent now answers in seconds and books jobs around the company's real capacity, service zones, technician skill sets and job types; the abandon rate fell to 5 percent, more than 600 jobs have been booked by the agent, and the company attributes $1.33 million in revenue to it.
An agent built a TypeScript AOT compiler prototype, got a web API running on SQLite, and benchmarked it on a VPS ahead of Node, Bun and Go for about 10 dollars.
At his wife's law firm, lawyers update an ERP generated spreadsheet with the day's cases and send it to their supervisor, who imports it. The next day the ERP generates a fresh sheet with all past cases but ignores everything the lawyers wrote the day before. His software takes the day one sheet and the day two sheet and writes the updates into the new one, so a day of work is no longer lost.
Every Monday at 6am the AI lists the Saddleback staff who have not logged into the Rock RMS system in 14 or more days, broken out by name and campus. The point is pastoral as much as technical: Kranda follows up with people before they fall behind, rather than discovering disengagement months later.
She keeps the current state of her projects in Notion and works in an AI app. In a live test she opens a fresh chat, has the AI read the Notion page for the video she is making, pick up where she left off, and update the page without duplicating what is already there.
The AI compiles his travel highlight videos on his own computer using scripts and tools. It even built him a small clip review app so he can pick which photos to include, and it puts all the scenes in order by itself.
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.