A random mix from the whole library. Shuffle for a new set.
He set up an agent called Cairn on a small rented server with about $90 in a wallet that needs both their signatures to move. The agent built its own website, keeps a public journal and ledger, wrote a manual on running agents like itself, and made over $2,600 in a month from paid questions, book sales, audit work for other agent owners and donations.
In AI Agents Library's structured 10-task business test (Sept 27, 2026, free plan, real business material), Diana gave the AI almost nothing for meeting prep: it found the correct email thread among several plausible candidates, located the calendar invitation, and prepared questions — including some she had not thought of. The task scored 10/10, the best result of the test day.
An agentic harness for Sonnet 3.5 converted a medium-large vue-class-component framework to Vue 3 composition API, rescuing a personal project from software rot.
Robert Brown of RB Electrical Services uses an AI receptionist that answers calls while he is out on jobs. In its first few days it answered six calls and four of them ended up as booked work.
Ben Robertson merged a fix for a feature a ColorBliss customer had asked for. His automated support agent saw the reopened ticket, checked the Linear updates, saw the feature had shipped, and sent the customer a note itself. He only found out when he logged into his help desk later.
The AI took over the user's Asana workspace during an 87-minute treadmill walk, working through tasks and organising projects while the user exercised.
Five days after Dhawal Shah switched his AI to a new model, a routine tidy up archived 57 of its 82 skills without asking, and his morning briefing and newsletter scan lost the link they needed to read his email and calendar. He restored every file from a daily backup and now requires his OK before the agent changes its own setup.
GTM consultant bryn describes the standing rule he runs for a small sales team: when a good-fit account keeps coming back to the pricing page, the agent posts to the sales Slack channel with the evidence attached and a yes-or-no decision to make. The point is that reading and assembling evidence is the agent's job, not the rep's.
Agentic workflow ingests files from a complicated program, parses and loads them to a database, spawns agents that reconcile hundreds to thousands of items in flight and reach out to people for clarification, catching mistakes in real time, replacing a 500 dollar per hour service.
He gives the AI collections of notes, links, and files and asks for the bigger patterns. The tool he built with AI stores everything in a graph database and returns four views: a brief on the pattern it found, an evidence page, a questions page, and the graph 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.