Agents tuned his database queries for 60 to 80 percent gains
LLMs optimized SQLite querying with better indexes for 60 to 80 percent performance gains.
A random mix from the whole library. Shuffle for a new set.
LLMs optimized SQLite querying with better indexes for 60 to 80 percent performance gains.
His energy company used AI to build and deploy a better internal tool instead of buying specialist software and consultants, about 4,000 euros of credits with a handful of people.
Agency owner Nick Saraev documented handing his business's work to the AI for a week: auditing every task, having the AI plan the automation systems, building evals, and turning the winners into reusable skills. The tasks that scored well were scheduled to run without him; he kept judgement calls for himself.
Smarsh's customer support agent built on Salesforce Agentforce, named Archie, now resolves more than 7 in 10 sessions without a human.
He works in environmental health. One tool he built writes housing inspection reports and the correction orders that go with them. Another reviews septic system plans by arguing against his own review. A third takes a photo and returns the food code citations for the violations it finds.
An engineer used AI to plan and write an expand/contract migration moving a 180M-row events table from int4 to bigint over 9 days: backfill peaked at 4.1 seconds of replica lag and the final swap locked for 1.4 seconds, with zero downtime. The agent wrote about 90% of the scripts but twice suggested steps that would have taken production down, both caught in staging rehearsals.
At the Operably founder's own Aveda Lifestyle Salon in Carmel, Indiana, the live setup books guests by text against real availability with a card on file, sends intake forms automatically before a first visit, and gives staff a Teams/Slack assistant that answers policy questions from the salon's own 1,000-plus documents with cited sources. Within weeks of the reminder texts starting, new guests arriving with the intake form already done jumped from about 25 percent in a typical week to 81 percent in one week; the voice receptionist is built but not yet live for guests.
He runs AI against real client bookkeeping, sorting thousands of PDFs into folders for about 40 companies. Before any file moves, the system writes a log line with the current path, the destination, a sha256 hash of the contents and the path to put it back. Nothing is deleted; files go to a dated quarantine folder, and a file can only be cleared when its hash already exists elsewhere.
For four months, the AI has handled the faxes that come into his company. He says it now spots junk faxes every time, and the ones from real estate firms, investment firms, and staffing agencies no longer get through.
A partner in a seven year old service business built an app for managing jobs, clients and billing, then connected the AI to its data read only through an MCP connector. Within ten minutes the AI found a margin problem on certain jobs that the owners had once known and forgotten, and proposed a fix they say will save $2,000 a year. It also flagged bigger changes to how they manage work and take payments.
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.