One prompt fixed years of typing errors across his project
Fixed years-old Python typing problems in his project with LLMs in one prompt.
A random mix from the whole library. Shuffle for a new set.
Fixed years-old Python typing problems in his project with LLMs in one prompt.
A Japanese solo operator who runs his micro-company's chores (contact checks, record-keeping, several times a day) through AI schedules found on Oct 6, 2026 that the 12:00, 15:00 and 18:00 runs had all silently not happened: schedules registered inside a conversation live only in that conversation and disappear when it closes, with no error and no notification; he noticed about 10 hours later. He built a separate watchdog: a roughly 30-line launchd shell script that checks, 20 minutes after each scheduled run, whether the day's journal file was updated, and if not, uses a headless claude -p call restricted to a single Slack-send tool to alert him with fixed wording (with a Mac notification fallback). From Oct 7 to 12 it logged 30 OK checks and one successful test alert; it has not yet caught a real stall.
Independent musician someone lists 11 daily tasks he delegates to the AI: Gmail cleanup, Meta ad campaign management, email list building, unclaimed royalty tracking, PayPal subscription audits, a disco-house culture digest, Instagram DM opportunity scanning, tour travel booking, gear deal hunting, finance consolidation and streaming stats. He states in replies that he is not paid and that the AI is free.
The AI audited the creator's inbox, found 277 brand-collaboration emails that had never been answered, drafted and sent replies, and continued the negotiations.
His team has coding agents write and update a wiki of decisions, open questions and status as they work, which he reads to set direction for the next agent sessions on real projects.
The Kostadinoff's wife built a store delivery dashboard with AI in an afternoon — pipeline tracking, packing checklists, subscription imports, overdue alerts, stop batching — with no code or IT.
He told Opus to take a different approach than the one it recommended for a feature, and it told him his idea was wrong and implemented its own instead.
Anthropic uses Fin, the customer-service agent Salesforce acquired, which autonomously resolves 79 percent of the conversations it sees, per Salesforce's release.
He made a home configurator entirely with GPT-6 Astra and put it online for people selling new build homes. Buyers can open it and try it instead of only looking at a PDF.
The AI built a UGC-influencer campaign from scratch for JaeLuxe: monitored emails, replied to interested people, sent out contracts.
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.