Ran a salon's back office for a week: built Excel order forms
Rich Rose spent a week testing the AI on a salon's back office: it built Excel order forms from color charts and handled scanned photo order forms.
A random mix from the whole library. Shuffle for a new set.
Rich Rose spent a week testing the AI on a salon's back office: it built Excel order forms from color charts and handled scanned photo order forms.
With the AI doing the grunt work he built a compiler for his own language that runs on Mac, Linux and Windows and cross-produces for those plus WASM, iOS, Android, Zynq, m68k and 6502, with a signed binary running on his phone.
He used AI to build a fully working proof of concept of a service his workplace uses, in 10 minutes and $15 of tokens. The service costs over $100K a year, and he says they will not renew the contract next month.
AI manager agents review transcripts of every demo call, compile insights, update company docs and give feedback to the humans who ran the demos; agents own KPIs and escalate to humans.
An LLM crunched for 36 hours on a project he had wanted for 5 years; checked and ready to deploy, work he estimates would have taken him about 9 months.
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.
Uses Sonnet 5.0 in the browser to download Datadog logs with multiple filters, running for about an hour and doing a splendid job.
Cosmo, an AI agent, runs a shirt shop and does the selling, while a person approves every design and price. Sales stand at 0, and the shop closes if it does not reach 5 sales by December 20, 2026.
The Zilliz team linked the AI to their Slack community in about 20 minutes of setup. The agent now answers user questions around the clock.
The solo maintainer of the karasu modeling language runs dependency updates through an AI skill that investigates each Dependabot PR before anyone merges: release notes, the diff between tags, publisher or ownership changes, install-time scripts, lockfile edges and known advisories, written up as merge, hold or reject recommendations in a design doc. In the week of Oct 10–17 three triage rounds fed 88 merged PRs (16 from Dependabot) and 12 architecture decision records, and the process caught a rebuilt lockfile silently moving a package off the reviewed version.
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.