A random mix from the whole library. Shuffle for a new set.
He had the AI collect his will and trust documents and check them against state statutes. The review found missing signatures, an illegal clause, and outdated law references, and he fired his attorney the same day.
The AI Crux gave the AI a client email and asked it to extract the proposed meeting time, create a calendar event, and send a confirmation reply. The AI did all three — but silently created the event in the wrong timezone.
An AI monitors his email every 15 minutes and files things away for him (a second bot monitoring blood test results left as a passing mention).
Calling sellers about his orders was one of Josh's biggest pain points — so the AI took it over: it called a seller to correct his shipping address, and called a seller to resend his missing orders.
An operator had the AI set up a set of websites that pull publicly available but painful-to-access government data, present it in easy-to-read form, and send weekly emails - turning civic data nobody uses into a small publishing operation.
Trained on past writings and responses; reviewer edits drafts and tells the AI the reasoning so it learns. Drafts only - never sends autonomously.
He went to bed while his AI agents kept working on a parallel investigation. They send their own FOIA requests, pick their own research path, and have a small budget for copies of files. He set the web permissions for the night before letting them loose.
A local model helped build a self-hosted services wiki and dataset in an Obsidian vault so his partner could keep systems running if he died, set up in a few hours.
He built geo-v.eu, a live calendar of EU political and economic events that runs to 2028. The AI Haiku judges each candidate event against his written editorial standard, the pipeline hunts for the outcome for five days after each event, and the site rebuilds daily from static files.
A church volunteer runs a weekly hybrid workflow: The AI translates six Chinese daily spiritual messages (Monday–Saturday) into structured JSON under strict rules — Bible quotations in NASB 2020 rather than translated, hymns left untranslated, ministry terminology matched — then Python inserts the text into a PowerPoint template, merges a bilingual twelve-message deck, and converts it to HTML for the church website. He keeps theological review, visual checks and final publishing approval human on purpose.
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.