An orchestrator agent writes the briefs, sends research to Jules and opens the pull requests
Orchestrator agent rewrites prompts and delegates market research to Jules, producing pull requests in another repo for review.
A random mix from the whole library. Shuffle for a new set.
Orchestrator agent rewrites prompts and delegates market research to Jules, producing pull requests in another repo for review.
His company runs a WhatsApp agent for clinics in the UAE that books and reschedules appointments and answers questions about doctor timings, slots and treatment prices. It has handled over 100,000 conversations, costs clients about $100 per 1,000 conversations a month, and hands sensitive cases like gynecology to a human.
The AI Launch team reports a live test where a managed the AI Agent, given one chat instruction, searched Vast.ai for an RTX 4060 Ti under a $0.40/hour cap, rented it, rendered a 1920x1080 Blender frame over SSH, and destroyed the instance. The whole cycle took 194 seconds and cost $0.007.
The user's agent, nicknamed for its savings habit, cancelled Squarespace, migrated the site to Shopify, and discovered his Apple TV subscription was already free through his Chase Sapphire Reserve, activating that instead of paying.
A designer treated the AI like a design engineer for his client Wordsmith AI. After 8 versions and more than 90 rounds of feedback, they shipped Draftboard, a live tool where anyone at the company can make on-brand images in a few clicks.
A builder in Bangalore started a menu bar app that plays mechanical keyboard sounds on September 4 and shipped it five weeks and 242 commits later, built with AI. More than 60 people have paid the one time $4.99 price. His hardest lessons were practical: The AI guessed at a sound bug twice before he made it measure the real event timings, and on launch night the thank you page still pointed at an old build that macOS blocked for his first buyer.
He added a weekly ops review to his AI chief of staff bot. Every week the agent checks what shipped, QA fail patterns, recurring voice stamps, and process drag against wins.
He edits video for a living. His agents handle the non creative manual work around each project: quality checks for missed text, black frames and logos, subtitles, reformatting for social aspect ratios, spreading files to the right products and pulling source material for descriptions. He logs his hours on every project and says agent assisted projects take about half the time with better quality; the weeks spent building the setup paid for themselves in two weeks.
Writing Rust code faster than state of the art by asking agents to make the code faster.
A Korean solo developer's two-day diary of putting the AI to work as his team: GitHub issue labels split between him and the AI across marketing, planning, design, QA, operations and finance, with a project board and roadmap milestones built in about an hour; the AI runs QA on each deploy event and files issues; customer inquiries are answered through an admin MCP connection; and morning routines from a one-time setup (7 AM English lesson, Google Analytics analysis, issue briefing) arrive unprompted. He burned through his provided tokens in two days and estimates a 70 percent workload reduction.
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.