A random mix from the whole library. Shuffle for a new set.
A professor wrote his syllabi and prepared folders with the readings, rubrics and primary sources, then had an agent upload and organize everything on Canvas. Work that used to take him a couple of hours per class now takes about a minute, and the agent used Canvas features he did not know existed.
Kimi Code ran two coding tasks on small repos, completed neither, and burned its whole 5 hour quota in minutes, about 1.37 dollars of API-rate usage across 1.59M tokens in the logs.
He has the AI edit his YouTube videos end to end. It transcribes them, cuts the dead air, zooms the jump cuts, adds lower thirds, sound effects and music, and hands back a Premiere timeline.
A swarm of AI agents ran 4,654 searches to catalogue AI product names and trends, published as a public page.
Ported a legacy .NET WebForms app to Blazor with GPT-5.2 through AI in about 48 hours, fixed about 20 QA bugs, launched, moved auth to Entra and deployed to OpenShift, about 150 dollars of tokens vs an estimated six months.
Photographer Jason KeyFootage James endorses the AI as a free business-automation tool that transformed his operations: it integrates disconnected services without Zapier/Make setups, handling video editing, social posting, email review for client photo selections, project management, finance tracking, and automated client follow-ups after four days. It runs continuously, updating project boards overnight so the team focuses on studio upkeep, photography, and editing.
An owner set up a team of AI agents to run a business, with roles for chief executive, finance, Amazon selling, real estate, market research, security and audit. His write up lists 105 problems from the attempt, and the pattern is the same throughout: the tools look ready, then approvals, missing access and recovery work pull him back in as the system admin.
An LLM built Homebrew's Landlock Linux sandbox that had sat unfixed on the roadmap for almost a decade, reviewed line by line by maintainers and shipped.
He has a mobile app with crash reporting through Sentry. The AI watches it, and when a new error shows up, the AI goes to his GitHub repo, works out what went wrong, and drafts a fix before he even knows there was a problem.
He moved his reading history from Goodreads to BookHive, onto his own AT Protocol data, and pulled in Audible data too. The AI cleaned up 389 books along the way.
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.