A random mix from the whole library. Shuffle for a new set.
A business owner's lead profile runs every Monday on its own. It formats his warm leads, finds cold leads that match his criteria across a rotating list of cities and niches, then digs into each business to find what he is missing, owner names and exact contacts, checked against business registries. He gets one standard weekly report: best fit clients, outreach details and the facts to judge each lead.
Reporting Anthropic's September 23 engineering post, this analysis describes the AI running a two-week performance sprint from a Slack channel: 150-plus threads, benchmarks built for each bottleneck, and more than 3,000 merged changes with no customer-facing incident. Time to a typeable page at the 75th percentile fell from 3.1 seconds to 0.55, with a human approving every pull request.
A German business consultant stopped keeping her time spreadsheet by hand in October 2026: since the AI does much of the work with her, it also keeps the log, writing into her running 'current state' document after every work block what was finished, where it lives and what she decided, tagged with one of four categories (revenue, acquisition, building, admin), a duration, and who actually worked, her or the AI. On Sundays she types one word, 'Wochenbilanz', and gets hours per category plus the loops nobody notices (items resurfacing a second or third time); the monthly version confronts her with last month's goal quoted verbatim, which at her first review she no longer remembered word for word.
He runs all the steel on a large construction job. The AI builds him a packet for each item from the project document database, and reads the specs and codes to work out which one takes precedence when they conflict. He says it saves him at least 15 hours a week.
His Pi agent uses a Clojure nREPL extension to modify and reload code and rerun tests, organized the subsystems in his repo into Integrant systems, and compiles, watches and serves CLJS apps when instructed.
A local LLM helped him build a sub-1500-line memory-safe baremetal Rust init system with a test suite in about a week, work that would have taken months by hand.
He gave an AI one job: earn a first real payment from an open source bounty. In three days it sent two pull requests and spent about one weekly quota of compute, but maintainers closed its work unread and most listed bounties were not really open, so it earned nothing.
His team built their own task tracker in three weeks and moved 1,630 tasks out of ClickUp. The tracker ships with an MCP server, so the AI reads and writes tasks directly, and each card shows where the agent is in its work.
In their apprenticeship, trainees had to log their on the job hours on a paper form and email or text it to the office manager, who then typed every entry into a spreadsheet by hand. He built an app so apprentices can submit their hours directly. Now the office manager just has to make sure everyone submits on time each month. If someone still wants to turn in a paper copy, she can enter it through her admin login, and the app does all the math for her.
He says his business got serious about Power BI reporting about twelve months ago, then three months ago threw it out and replaced it with AI licences. A third party warehouse tidies the data with an MCP on top, and the finance team now builds its own reports quickly instead of waiting on a reporting team.
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.