A random mix from the whole library. Shuffle for a new set.
He built one skill that does his company credit card expenses and another that files his email in Outlook. Both were manual jobs he hated. Now he mostly watches, answers the odd question and finds an invoice when asked.
An agent account run by the AI in an AI app makes videos and posts them across four platforms, picks its own topics and reads its comments. Since October 13 its main account's followers went from 455 to 456, and its first TikTok uploads got 3 views and 0 views.
He made an Easy Chores list on his Trello board and a skill that teaches the AI to find more of them in his backlog. The AI fixes them in pull requests, and the chores get done instead of sitting in the backlog.
Reporting Anthropic's September 23 engineering post, this analysis describes the AI running a two-week performance sprint from a Slack channel: 150-plus threads, benchmarks built for each bottleneck, and more than 3,000 merged changes with no customer-facing incident. Time to a typeable page at the 75th percentile fell from 3.1 seconds to 0.55, with a human approving every pull request.
Agent ported his hand-written WebGL renderer to WebGPU, deployed and live in 24 hours versus a 6 to 10 week human estimate.
A small affiliate business says its AI assistant starts every morning by reading click logs by source and checking journalist requests, then it publishes the next social posts. A person still handles identity checks, payments and signups.
He gave the AI a challenge: make $100 in 30 days with no budget, armed only with a subdomain, Cloudflare access and a payments integration. The AI landed on Loot Radar, a game deals and freebies alert service that tracks price drops and free game drops across Steam, Epic and GOG and fires Telegram alerts within about 20 minutes, with a pro tier at $4 a month or $39 a year. The site is live and taking sign ups, payments wired. It monitors itself every two hours, writes its own copy, ships its own fixes and handles customer emails; he only approves or vetoes. The $100 itself had not landed yet on day one, so the outcome is partial.
He builds the visual overlays used in car inspections in Blender. The AI creates and maintains the Blender files with him, renders them, and pushes the output to the iOS and Android repos.
A mathematician with more than a dozen finished but never submitted papers pulled out four of them and shared them with AI. The AI caught errors, built a spreadsheet comparing his new concepts against related papers, converted plain TeX to LaTeX, wrote abstracts he adopted almost word for word, and fixed bibliography entries unprompted. All four papers improved to the point where he submitted them.
A man built a service that sits on his company’s GitHub repos. For each area of code you set the bar, and an AI agent with a fixed prompt has to bless a change before it can merge, so people can merge their own changes without waiting for a human review. About 30% of the company’s pull requests now merge this way.
For his half yearly performance review, he pointed the AI at his emails and Teams chats, loaded in his goals and objectives, and let it run. The review it produced made him look brilliant.
Kuli Kuli founder Lisa Curtis had the AI evaluate 250 applicants for a director role against her job description while applications kept arriving, and her assistant booked everyone who cleared the screen. She ended up with more than 30 interviews booked, reread the candidates herself, cut the list roughly in half and sent 14 cancellation emails to people who had already blocked time and started preparing — several wrote back angry.
He and the AI analysed 144 of his CoWork sessions and 14,640 turns, found a turn past turn 141 costs 2.1x an early turn, and stopped batching sessions as a result.
Used the AI on the 20 dollar tier in a weekend to build good enough coverage on Floci features to make it useful to him; others then continued the work.
Magan (someone, 140K followers, 'Building in Public') created a custom AI agent called 'Piggy Bank' connected to Messenger, Instagram, email, and credit-card transactions. It scans sources to find all subscriptions (which she can cancel), reads Instagram DM chat history to track brand-deal payments, and generates a ledger showing how much she's owed, plus spending insights and payment reminders.
A creator who could not afford an editor paid for the AI Max and built his own post production studio, about 31,000 lines of code. Its smart cutting takes his raw filming and builds a DaVinci Resolve timeline for him, saving about 95% of the cutting time, and it also generates shorts and uploads with titles, descriptions, chapters and tags.
The AI wrote a Windows batch helper as a UTF-8 file with LF line endings. On this Japanese locale machine the last byte of a Japanese full stop swallowed a line break, a variable stayed empty, and a delete meant for one file deleted every file in the project folder, 1,068 files in one second. 123 files could not be recovered.
After every client call he drops the Google Meet transcript into his note system unread. The agent pulls out the decision, the reasoning and the next actions, and files them with the right project. He has built up more than 450 linked notes this way since April, and keeps the raw transcript beside each note because names sometimes come out scrambled.
The same studio's agent Timmy orchestrates more than 20 tools to turn blog posts into short videos: Veo generates scenes, ElevenLabs synthesises a custom voice, and automated captioning, lip sync and final assembly finish the piece. The pipeline runs inside the studio's normal the AI production setup.
A business owner runs a six-bot the AI back office for $200 a month, compared in his post with a $58,000 hire; the desk works his inbox finds and holds a veto on any money leaving. The setup is specced like a small office: named seats, a shared brief, and one bot whose job is to say no to spending.
Over a few days he used an LLM to create a complete court document bundle for a Judicial Review at the Manchester High Court. He filed the documents today and the court issued them within 5.5 hours, something he says he had no chance of doing on his own.
An agent built a TypeScript AOT compiler prototype, got a web API running on SQLite, and benchmarked it on a VPS ahead of Node, Bun and Go for about 10 dollars.
A user had the AI apply TurboQuant skills to optimise a Qwen3.5-9B model running locally via MLX on Apple Silicon. The agent applied, tested, documented and packaged the optimisation path itself, making the ML workflow repeatable.
A freelance designer with no coding background used a standing AI setup — a dedicated project, custom ExtendScript instructions and a scripting skill — to build three batch logo-processing scripts for an Upwork client. The client paid $640, left a five-star rating and became a repeat client.
He set up the AI with five helpers for his YouTube work. One scouts what is new every Monday, one helps write scripts, one makes all his thumbnails, one updates his personal brand GitHub repo, and one helps him engage on X.
He feeds the AI Notebook a transcript of the meeting recording plus scans of the printed handouts with his notes on them. It writes the minutes as bullet points grouped by topic, and the technical terms and names come out right more often than with apps that only use the audio.
Reviewers tasked the AI with researching the top five competitors in the freelance project-management space across 12+ websites including G2, Capterra and Reddit, extracting pricing, audiences, features and common complaints. It delivered a structured report with tables in about 15 minutes at roughly 800–900 credits, with accuracy estimated at 70–80% and some pricing tiers outdated.
Gave the AI a Java RISC-V emulator and a partial libc bridge, and in under an hour it could run bash and sqlite from Debian.
Going through five years of his team's JIRA bugs looking for patterns would have taken him about two weeks. The AI did the analysis and collation in under 30 minutes.
The company asked the AI for a video showing how easy it is to program with their API and gave it four instructions. The AI put the rest together itself, and made and published the post.
A one-person game studio in Japan runs fourteen the AI with routines and connectors; when a player left four questions on his game’s itch.io page, the Amiga Research bot split them into eight labelled GitHub issues in under a minute, and the resulting fixes were merged about nineteen hours later with the owner only making yes-or-no calls. The same bot team runs his Monday social roundup through Buffer, watches his NAS and Steam numbers, and briefs him twice a day, all on one roughly $40/month X Premium+ subscription.
Spent about 10,000 dollars running autoresearch agent loops over the top 200 GitHub repos for frontend speedups and distilled the wins into a public leaderboard and wrapper tool; no per-repo numbers stated.
A construction-company owner runs the business through AI agents based in a single Obsidian folder: any scratch-pad note he drops in gets automatically sorted and wiki-linked, API jobs run on their own, and deep-dive audits happen most weeks. His home screen arranges tasks radially - today in the center, then days, weeks and months outward - so he can spot at a glance what he has been neglecting.
He and a colleague used AI to transcribe over 28,000 documents for the Papers of the War Department project. They wrote up how they did it on the RRCHNM blog.
Asked the AI to figure out, create and execute an AWS S3 batch copy job and report its state, and it did so without hesitation.
He carries a small voice recorder. When he records a thought, the audio goes to his agent Rick as a message, and Rick carries out whatever the note asks, which he says beats the reminder apps and note widgets he tried before.
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.
Used the AI with his own APK analysis tool to analyze phones from 3 brands and found 2 RCEs and 5 root bugs in a few days.
A services co-op connected the AI to its Salesforce. The finance director drops in a bank statement and the AI matches each payment to the invoice it pays, to the cent, sorted into certain, split across invoices, or to check. Once she approves the list, it records the payments and marks the invoices as paid.
An agentic harness for Sonnet 3.5 converted a medium-large vue-class-component framework to Vue 3 composition API, rescuing a personal project from software rot.
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.