A random mix from the whole library. Shuffle for a new set.
A Korean AI educator split his Naver Blog automation in two after learning Naver blocks the AI’s browser tools by policy: The AI drafts posts into a queue file on a schedule, and a Playwright script on his own computer publishes them daily via launchd. Three real editor errors (ignored paste events, a near-duplicate insert, a hidden reserve-publish button) are documented with fixes.
Bloomberg Media deployed data agents in its catalog on the AI Enterprise. Query accuracy improved by 63 percent.
Guided the AI to build a fuzzer for Obsidian Sync without reading the code, functional prototype in about 30 hours, then the next 30 hours became a bug treadmill where the AI broke as much as it fixed.
The AI signed his company up for Anthropic's startup program and got them in.
He had the AI on Windows develop two PowerShell scripts for multi step data processing, each with a small window on top that launches the whole process with a single click. Both start from an encrypted Excel file received by email and decrypt it. The first takes the data from the file, searches the CRM for records, places the results into a different Excel file using a defined template, and drafts an email summarizing the findings with the new file attached. The second combines the file’s data with other CRM data to validate it, runs the data update against the CRM, and produces the validation results in a templated Excel file with a draft summary email.
Luke Davies runs Davies Construction with a team of the AI set up like a company org chart, with bots for estimating, admin, books, sales and project work. Day to day the bots sort the inbox and draft replies, pull tasks out of meeting notes into a list a person approves, and create and update the job tasks in ClickUp as work moves on the Wunderbuild board.
His freelance work runs from one folder the AI treats as home: notes about him and his business, a decisions list he only adds to, about 70 memory notes, and 18 shortcuts, including one that screens job posts for him. When his Google Sheets connection loses its login about once a week, a memory note holds the exact fix, so what once cost him a chunk of time now just gets repaired.
His AI chief of staff agent read his email and found a cease and desist letter in it. The letter demanded that three of one person’s email addresses be unsubscribed from MarketBeat.
He exported 10 hours of his AI usage (8,915 model calls, about 1.15 billion tokens) and had the bot study it. Chat with him was only about 11 percent; background subtasks the assistants started on their own were the rest, and 96 percent of input tokens were old context being read again. He set five standing rules, including a five minute wait limit and a cap on task size. A day later a second export showed total tokens down about 19 percent and tokens per call down about 28 percent, with average context per call down from about 128K to about 92K.
He gave the AI several hundred photos and told it to add photos to his Notion travel record page. It picked about 30, added them, and also made a route map from his GPX data.
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.