A random mix from the whole library. Shuffle for a new set.
Had the AI build an open-source source control system, benchmarked on a 100k-file monorepo as 12x faster sparse checkout and 82x higher concurrent land throughput than git.
A user asked for a single audit of one Excel deliverable. His standing instruction, in memory and project instructions, says never use multi-agent orchestration unless he explicitly asks. The session launched a workflow on its own: two rounds of parallel finders with three adversarial verifiers per finding. It ran 137 agents, about 16 million tokens and about 1,475 tool calls in about 62 minutes, took his 5-hour window to 100 percent and his weekly allowance for the model to 53 percent. There was no estimate, cap, or confirmation. He stopped it manually.
AI bots manage his startup finance, payroll, meeting prep and social media, with a primary bot auditing and optimising the other bots weekly.
He runs a small home service business. On site his crew capture photos and notes into a CRM; the AI reads the CRM over a connector, studies the photos and writes the full client report he used to write himself. When the report is done he tells the AI to send the invoice, and it builds the Stripe invoice from the project notes and sends it to the customer.
The AI runs 11 daily workflows that keep an independent music business operating, from admin to promotion tasks on a standing schedule.
The AI redlined OEM contracts through the first three negotiation rounds, finding things his lawyer missed, with the lawyer only doing the final check and money saved.
Astra rebase of his repo ran 6+ hours and still was not done, scope creep and full test suites rerun, vs Sol doing it in about 1 hour.
Environmental consultancy Verdantas runs proposal development, contract management and collaboration agents on the AI Studio. Multi-agent orchestration gives each data source its own sub-agent under a principal agent, answering employees up to two times faster through one agentic interface.
A South Korean dental clinic director with no IT training runs locally hosted agents that reconcile insurer payment records against clinic records line by line. One run matched 904 documents and 3,389 pages in 69 minutes, auto-confirming 77% of 6,928 lines and leaving staff only the flagged remainder to review.
During a flash sale on his petals.team site he checked analytics and found zero events, ever, because PostHog had never been added. Through the PostHog MCP connector in an AI chat he spotted, diagnosed and fixed it, saved a 3 step registration funnel, and set a weekly digest to land in Slack every Thursday.
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.