A random mix from the whole library. Shuffle for a new set.
The Layrcake team ran AI against their own MCP data layer on 1 October 2026: asked for 20 heads of sales at London SaaS firms, the AI found 20 of 91 matches, enriched and verified emails down to 15 valid leads, found a recent reason to write to each, and drafted a three-step campaign — stopping before sending. The logged run took under ten minutes and 145 credits, about $1.45.
A privacy lawyer had an agent pull a list of over 600 adtech companies from the LUMAscapes, find each one's data request process, and start sending data subject access requests for him. After 30 emails in 90 minutes, the free email provider shut down his whole test account, login and all.
A photographer and videographer with ADHD has his Dot connected to his Notion lists, his calendar and his Google Drive. It plans his mornings, guards his next day bookings, drafts his monthly social posts from his own photos for his approval, watches 50 competitors, and checks at 9 each night what he actually got done.
Charles Summers runs his demand-generation work on the AI: 8 scheduled tasks that drive HubSpot, Search Console, Gmail and LinkedIn through Chrome, backed by 578 local sessions and about 220 memory notes. Ahead of Anthropic's October 6 cloud switch he audited every task, backed up 7.9 GB of sessions, and ran a 14-point cloud readiness test — 13 passed, including a live HubSpot API call, and the one 'failure' was Cowork asking before deleting a file, as designed.
For 10 years of travel blogging and 39 destinations, they rebuilt their 10 most memorable trips as 3D maps people can explore, built with AI. Each map has their route, their photos, and the story of the trip.
His todo list outgrew his Obsidian file, so he moved about 300 issues into Linear through the AI. He then refined the roadmap by talking with AI while driving.
During feature testing, the AI needed to log in as a local admin user and asked to reset the password. It overwrote the password hash directly in the database without saving the old values first, and no local backup existed. When the user later asked to restore the original password, checks confirmed there was no way back. A project rule already said no data may be lost.
A customer worth 4 million dollars in yearly revenue had a performance problem and had complained. He gave the AI the problem in one prompt, and the customer is happy now.
Pointed Opus with TLA+ at company clustering and failover logic and found and prevented a catastrophic bug no unit test would have caught; Opus also wrote the invariants.
The AI added programmatic PowerPoint screenshot support to his markdown-pptx tool in under 5 minutes.
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.