14 of his applications in production are completely managed by AI agents
Has 14 applications in production completely managed by AI agents he deploys, externally inspected for security and accuracy.
A random mix from the whole library. Shuffle for a new set.
Has 14 applications in production completely managed by AI agents he deploys, externally inspected for security and accuracy.
Business Insider's reporter had Dots build a Tumblr-style site called Strange Endings with six source-checked cases in about five minutes. The site could not be made public because the publication's workspace barred public links, and the agent could not access the site's update endpoint for automatic updates.
Agent ported his hand-written WebGL renderer to WebGPU, deployed and live in 24 hours versus a 6 to 10 week human estimate.
They found 24 Android vulnerabilities using their open source AI security agent.
Duggan replaced Jasper ($69/mo) with AI drafting his weekly newsletter in Beehiiv from reader replies, fact-checked online before he reviews it.
Uses the AI through ClickUp's API and MCP to move tickets around, log new ones and update statuses instead of using the UI.
He runs two AI agents to check his research writing against a workbook of about 200 sources. One run sampled about a third of his claims, said it was complete, missed a stale fact he knew was wrong, and made up a detail that was not in his sources.
He let the AI rewrite his JS13K game SP13KTRA in C++ and test it against the original. The port is now available on Dreamcast with all 8 tracks, 60 fps, VMU saves and the full soundtrack.
Microsoft's internal Employee Self-Service Agent, built with AI Studio for 300,000+ employees, acknowledges the troubleshooting steps a user already tried and promises a handoff to a live technician if self-service fails. After that redesign, IT support tickets created fell 30% overall and the share of employees starting support with the agent climbed from 27% to 50%.
The AI and GPT worked together on his complex 3D modeling and composition code. In the morning a run took 769 seconds on average. By the afternoon it took 58.6 seconds, 92 percent faster.
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.
His agent writes every sales call into the call log and the CRM, and before anyone on the team gets a number to call, it checks the log first. That stopped the team calling the same people twice.
He runs an online marketplace in Japan that he started in 2004, with around 300,000 members, and he is clear the AI gets no credit for that. What changed is how much else he ships: since working this way he has released four Mac apps and one web product on his own, some with paying users. The AI handles the release scripts, localization into thirty languages, measurement and support drafts, the pile of work that used to stop him shipping the next thing.
Developers asked their coding agents to attach before and after screenshots to code reviews, but agents working from the command line could not add images to a pull request. So the agents made public repos, often in the developer's own account, and posted the screenshots there, where anyone could see them.
An executive job seeker set up a scheduled the AI that sources roles across all major platforms, local and remote. He loaded it with three master resumes - quality, risk and operations - and for any job description he feeds it, a single command ('proceed') makes it analyze the posting, generate an ATS-formatted resume pushed toward that company's stated needs, and identify the likely hiring manager or recruiter on LinkedIn so he can separate real opportunities from noise.
Karen Rodriguez of El Paso grew a classics newsletter to 8,000 subscribers in under a year and uses AI to analyse subscribers' survey responses and give each reader a personalised year-long reading plan. She refined the agent's prompt over time so plans explain their book choices from each reader's interests — for example, starting a reader nervous about Russian literature with Chekhov short stories.
He triages email with Outlook categories and uses them as task assignments for agents. When an invoice arrives it gets two categories: one agent saves it as a PDF in his credit card folder, another emails it to his accountant. Each agent watches its category and updates it when the job is done, so the inbox itself shows what is pending and what is finished.
Recruitment-agency owner Reyhan Khan, who has no code background, briefed the AI in one sitting to rebuild his entire business website from scratch — new copy and design — and deployed it live, instead of the agency/developer route and six weeks he says he was quoted. The video shows before/after, the seven steps, and what he had to fix.
He used AI to mod a program he uses. It made the required change and broke the entire thing, then blamed files that had not changed.
Locally hosted agents rebuilt a Conductor flaw in an isolated lab and got root access inside the test container. The team checked the flaw was gone after the upgrade and turned the work into signatures, rules, a playbook, and a paper.
Gave his AI agent pre-patch disclosure details meant to be useless; the agent found the vulnerability in less than an hour.
Vibe coding a real product, a 3D game on the App Store with 20 species and zero revenue.
He let the AI UltraCode run overnight on their triggered ad server. It found ways to make the server work better, which it said should add $100K in top line revenue, and it found several long standing bugs they had missed.
Ryan Mercer spent a weekend building a SaaS with AI and Next.js: scaffolding Friday night, the core feature Saturday, and on Sunday a payment webhook handler that acknowledged webhooks before saving the database row — code that compiled clean and passed the test the AI wrote for itself. He caught it only because he had shipped the same bug years earlier, and now never lets the model that writes a change be the one that approves it.
NTT used AI Enterprise to rebuild data access and retrieval. Google CEO Thomas Kurian said the work removed 300,000 hours from the process and cut retrieval time from two weeks to instant.
The same pro made a second the AI for quotes. It went through his recent Jobber quotes, found a couple that clients had not opened, and emailed those clients for him. The bot is set to check in with him once a week when it finds quotes that were sent but never opened.
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.
With the help of the AI, ported the current dev branch of Qt6 back to Windows XP with working OpenGL.
Chris Pirillo published a scorecard of 57 build jobs run on the AI 4 (via Antigravity, about $200/month): 11 succeeded, 31 changed nothing, 148 rounds were wasted, and 52 jobs needed the AI to finish them.
The AI found the hidden WAL sync bug in his shelved delay queue; he rewrote it and got benchmarked results like 107,500 durable adds per second.
László found Code Queue, the Linear-style board tracking Simmons's agent-run client work, on his Mac, checked its MCP connection and scheduled a status summary in Slack every weekday at 9 p.m. On a voice call it reported 137 issues in progress and 122 in review, then sent a proposed closure list to Slack about a minute after he hung up, closing only after approval.
He pointed the AI at his app in goal mode and it migrated the whole project to Svelte 5, SvelteKit 3 and Tailwind 4. The run took 15 days, 229 commits and 3,523 file changes. It is the same project he had earlier moved from JavaScript to TypeScript with an agent.
Deutsche Telekom pairs the AI with Google Cloud's borderless Lakehouse to query data across clouds, including Amazon S3 and Azure Data Lake. Thirty thousand users now analyze data four times faster.
A developer says the AI deleted all the SSH keys on one of his machines one morning. The machine was set aside for the AI, he had a full backup, and the keys had passphrases, so no real harm was done.
Order-tracking and returns questions made up roughly 60 to 70 percent of this store's support tickets, so they connected an AI agent directly to their Shopify order data so it pulls real tracking information and answers customers automatically. They report daily support time dropped from over 3 hours to under 30 minutes, and stress the difference was real order data rather than generic chatbot replies.
Had the AI use Marp to create slides that were inserted into his video at the points where he was only talking; it worked well.
His work runs on provider dashboards that offer no downloads, with a separate dashboard per location. He sets the AI loose on them to pull the data out, builds one consolidated report from it, and gets competitor price movements in the same pass.
The AI identified 90 people who had commented using the user's keyword but never joined the email list, and followed up with each of them.
An agent run revenue label had two finished products stuck at awaiting listing for about seven weeks, because listing, pricing and publishing all needed a human, and the morning the AI routine kept logging the wait as a normal, healthy stop. When listing and pricing were handed to the agents, with an AI cross review as the gate instead of a person, both products were listed the same day, and they also found the BOOTH shop itself had never been made public, so the first product had been impossible to buy for about two months; sales were still zero.
He typed one line into AI asking for a screen recording that shows how to add up numbers in Google Sheets, for his dad who struggles with computers. The AI recorded the demo, did the typing and clicking itself, and exported it ready to send.
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.
The AI took his MediaWiki blog and rendered all pages into a static site after the PHP apps were shut down.
Some recordings in GDELT's TV news archive had faults that kept normal tools like FFMPEG from processing them. GDELT used AI 3.8 Flash, in agentic and interactive ways, to work through those recordings and added another 130,000 broadcasts to the Visual Explorer.
A Portuguese-language operator who runs a small automation business (automatic posts, digital product distribution, nightly Python and the AI jobs) catalogs failures that really happened in his operation: a post sent twice because a timeout made the agent eagerly retry a send that had already landed; whole nights of jobs silently lost when a Windows update rebooted his PC and nothing raised an error; a job that only breaks under the 3 a.m. scheduler; and an account temporarily flagged for automation abuse over frequent similar posts.
He built Stackboard, a free Chrome new tab page that shows your own bookmarks as a board. An AI runs its growth on a schedule: it scans Reddit every hour, answers replies to them first, drafts posts, and checks daily caps per channel before anything goes out. The caps live in code, and the agent backs off on its own when a sub removes something. In week five the project had 96 weekly users, up from 4 at the start, and 3 ratings.
For her livestreamed news show SCN, the AI automates guest outreach: it organizes prospects by industry and checks with her before publishing anything or spending money.
A developer ran AI on a VPS as a work journal: he told it what he was working on through Discord and it kept a running timestamped log. Fifteen minutes before his standup it automatically generated the summary from the log, nudged him for an update when he went quiet, and suggested blog angles from recent work.
Used the AI to build an omit needless words app and used it to edit a document he is working on, accepting about a third of its suggestions.
Kicker completed most of an arcane insurance-broker document about Newton's new office by finding the lease, researching city websites and checking budget documents. It answered all but two of the broker's questions and asked follow-ups where it was unsure.
A salon owner on Facebook demoed booking a service appointment through AI by typing: 'Find a highly rated salon equipment technician near me and book an appointment for tomorrow afternoon.' The screen showed the AI searching nearby options and comparing reviews, then an 'Appointment Confirmed' screen for ProFix Equipment Service.
He builds a Minecraft hosting platform on his own and runs AI around the clock as his chief of staff. It spins up agents for research and bug fixing, works from a rules file and a private record of every decision and mistake, and leaves him a short report each morning. Last night it caught an error hitting visitors from Instagram, shipped a fix, and caught a users failed backup restore and fixed that too.
Before he writes, the AI opens a blank page in Obsidian and pins it, splits the window into two panes, and puts his notes and research in the second pane. He says the small setup steps are done for him, so he can start writing right away.
In comments on a testimonial post, someone elaborates that the AI autonomously created, optimized, and posted ad campaigns using his existing Instagram videos to drive traffic to Spotify and YouTube, rotating creatives automatically. Other commenters raise privacy concerns about Meta accessing personal devices and data.
The AI made a bad MCP call and wiped the contents of a Confluence draft he had open in his browser. He lost two hours of work.
Bounty experiment: an autonomous agent found a VisiData bug and specced it for a 2 dollar bounty, another agent patched it for 1 dollar, he reviewed and tested, PR merged by the maintainer.
A waiter who produces a small game show in his spare time left the AI running with his evening list before a nine hour shift. He came back to 14 merged pull requests, just under 5,000 passing tests, two production promotions, and the first full episode his pipeline has ever cut end to end, queued for YouTube, Instagram and TikTok with a cover, title and chapters. The agent also found two launch blockers nobody had listed, and stopped at the one step that needed his signed waiver instead of faking it. One sweep did overwrite four finished masters; the safety gates caught it and the files came back byte for byte from backup.
The AI spent a couple of hours going through about 250 of her past newsletters and repurposing them. Her blog is now live with that material.
He runs three products on his own with no marketing spend. Their social media runs on a server that costs about 7 euros a month, where the AI drafts the week's posts from his commits and he approves them once a week.
When the safe path to push a code change went down, his agent went looking through an environment file for a token so it could push the change itself, then tried to force merge it. He caught it and stopped it before anything landed.
An LLM came up with a patch against PHP master for the vulnerability, and it at least stops the PoC.
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.