A random mix from the whole library. Shuffle for a new set.
He got a $510 Google Play payout. Two of his iOS games were built by the AI in Kotlin and published to the Google Play Store, and he says the AI handles everything for his Android games, even the bad reviews.
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.
A builder created JobAgent in an AI app: over a 13-week UK test it read and scored 8,585 job adverts against one tester's career record, wrote 481 tailored CVs and submitted 258 human-approved applications. The run produced 8 interviews and 3 offers — roughly one interview per 32 applications.
A video summary was made for others to use in their teaching. The AI wrote Python code that rendered about 9,000 animation frames, the poster recorded the audio, and the finished movie takes about 30 minutes to draw on a 1,000 dollar MacBook Air.
Constraints: zero ad budget, no existing audience, ~4 hrs/week of human time; assets: a subdomain, Cloudflare access, DodoPayments. Ruled out: custom AI songs, mixing/mastering services, automated day trading, 'information arbitrage'.
He used a GitHub repo that lets the AI act as an agent for Qualtrics surveys. The AI took his disorganized Word doc survey draft and turned it into a Qualtrics survey, formatted better than any survey he has written himself.
He exported 10 hours of his AI usage (8,915 model calls, about 1.15 billion tokens) and had the bot study it. Chat with him was only about 11 percent; background subtasks the assistants started on their own were the rest, and 96 percent of input tokens were old context being read again. He set five standing rules, including a five minute wait limit and a cap on task size. A day later a second export showed total tokens down about 19 percent and tokens per call down about 28 percent, with average context per call down from about 128K to about 92K.
He built a pipeline review and follow up system in GoHighLevel. It sends a follow up reminder to leads he had forgotten, and he says it brings in about $750 to $1,500 a week in jobs.
AI agent looped 21+ hours on his rendering engine streaming problem, tuning motion prediction and caching, fixed minor bugs, main problem unsolved, quota burning.
His agent goes through each episode of his own podcast, pulls the timestamps of the best moments for clips, and drafts the social posts to go with them. Finding clips used to take 3 to 4 hours per episode and now takes about 20 minutes, and he approves and tweaks the picks.
A man fed an expanded spec sheet into AI Sites and got a working booking website for his rehearsal space in 30 minutes. He asked for about 10 changes and new features and all but one worked, and the one break was fixed fast. He wrote no code at all, and says a site like it could have cost $10,000 to $15,000 from a developer against his $20 subscription.
Australian tiling business The Grout Guy built a photo-analyzing Agentforce agent that cut quote turnaround from days to minutes, one of Salesforce's 2026 Customer Success Award winners.
His VP of engineering reviewed two or three strategy tools on the market and they were prohibitively expensive, so he asked if it could be built instead. He built it alone in less than a month: long term objectives broken down into annual objectives, improvement priorities, projects, milestones and tasks, with bowler charts tracking the KPIs, full project management tools, and containerized staging, development and production environments. It cost roughly $1,000 to $2,000 in an AI app credits. The VP then put his own name all over it, and made him replace his own name in the about section with the name of the organization.
He let the AI run on its own for 40 minutes on a billing refactor. The changes looked clean, but it had quietly renamed a Stripe webhook handler, and he only caught it when he reviewed the work.
Diana at AI Agents Library gave the AI 500 loose files from her real business desktop. It proposed a folder plan first, she approved it, and it filed 490 where she wanted them, held 10 back for review instead of guessing, and caught all 48 exact duplicates and all 34 renamed ones.
He used AI, ElevenLabs, and D-ID to make a budget simulation for his Politics of Public Policy course. In it, students build a federal budget that lines up with the Trump administration's budget priorities, after researching those positions before class.
Made the AI part of a deterministic quality gate for agents; the gate catches cases where an agent strays from a project's constraints.
He gave an agent $50 and 24 hours to book meeting leads by messaging founders who had posted about scaling problems. A bug dropped its polite sales template after about 15 rounds, and it started sending blunt two sentence critiques of each founder's site and code instead. The reply rate was 62%, 8 founders booked calls, and he closed 2 audits at $300 each.
A business user asked the AI to duplicate a template; the request bounced between chats for an entire day, each claiming the project belonged elsewhere or that it lacked access to make the change. Contradictory explanations piled up and no usable result was produced, so the business is migrating away.
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.
His weekly reporting agent builds the report and then reviews only the rows that do not match between systems, which is the part he used to check by hand. His own review is down to about 15 minutes a week and the setup has run for months.
His dad got a private parking ticket for staying 15 minutes too long at his doctor's surgery. The AI drafted the POPLA appeal, it cited the Equalities Act, and his dad saved £100.
Claire Vo ran AI for several weeks and shut down every the AI she had. Her nine bots include Chief, which sweeps six inboxes and several Slack workspaces, a family bot that prints a kitchen table newspaper for her kids each morning, a helpdesk bot getting five star reviews, and a bot that audits subscriptions and negotiates insurance.
His Omeka exhibit died when the Neatline Text plugin stopped being developed. He scraped data from the old site, built a new framework with AI over a few days, and the beta rewrite is now live at the original address.
His company is pushing staff to use AI. He asked it to pull data from 2 spreadsheets and fill in 3 others, and it did the job in under 2 minutes, work he says would have taken him about 4 hours.
Etsy seller Bianca Davis connected her shop to the AI through the ProfitTree MCP and let it optimize listings; her dashboard shows revenue rising from $45,585.33 in August (1,811 orders) to $136,755.99 in September 1–28 (5,433 orders).
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.
She told her AI to get better at design, then had it check her own site, aunysillyme.com. It found every buy button was too low in contrast to grab attention and that two different oranges had been used on the site for months, and it redesigned the site based on what it had learned.
He asked the AI to make a PDF text searchable because his employer pays for full the AI but not the paid Adobe with OCR. After 10 minutes of processing it gave him a new PDF with the same number of pages, all completely blank and with no hidden text.
AI agents rewrote a production Node service handling 92M messages a day into Go (Checkly company blog, result stated in the title itself).
Founder Divya Gugnani shows screen recordings of the AI connected to her Instagram: it audited her account (reporting 38% of Reels working and 22% of Carousels not) and drafted replies to 47 new DMs. The same demo shows Gmail reply drafts held for her approval and a school permission slip auto-completed from email.
The maintainers of the Pion WebRTC library added its DTLS package to Anthropic’s open source scanner. They woke up to a report of 36 bugs, including 6 security vulnerabilities, 2 critical, some sitting in the code for over 4 years despite years of testing and scans. Fixes went in the same project.
A 59-year-old Japanese logistics worker who has never coded has the AI run 38 routines, including daily posts for three regional 'free places this week' Threads accounts; the agent published 95 posts in Oct 9-15 and one AI-written intro post passed 51,000 views. He reviews output five minutes morning and evening from his 4.5-hour commute.
A user on the $100 Max plan asked the AI to audit five or six login files for translation issues. The workflow spawned exactly 126 agents, ran the same job twice, and used about 8.4 million tokens, roughly half his weekly allowance.
He gave the AI his CV and a job search brief, and the agent searched Naukri, LinkedIn, and Wellfound for roles posted in the last 24 hours, scored each one against his experience, and tracked the strongest in a Google Sheet. For the top 3 it made a tailored summary and cover note in a Google Doc and drafted an intro email for each, leaving sending and applying to him.
Prompted an agent to build a custom LLM coding harness with session resume, done in an hour and working nearly flawlessly, plus a WebFetch tool added in 5 minutes.
An online fitness coach shows the AI setup he uses in his own coaching business every day. The AI holds his client context in a project folder that updates itself, walks through weekly client check ins and program changes, and collects delinquent Stripe payments, with routines that run on their own.
His RemainderBot uses excess the AI and the AI tokens to write PRs from his goals and task lists, 111 PRs done including customer call prep, runs as a cron job (own-use separable from the Show HN tool post).
He spent literally hours trying to get the AI to make a basic power automation flow. The AI simply could not do it, even though it sounds like an overconfident idiot while failing.
A scheduled the AI task runs at noon every day, reads his Nagios and BuildBot status, and messages a colleague only the items that look suspect, skipping young unknown states and anything already acknowledged. It has run since May, and once skipped four days when his laptop was closed, which he only noticed 26 days later.
A woman opening a small shop uses paid the AI to track her stock. She takes a photo of each item and the AI adds it to an Excel spreadsheet and fills in the data for all the columns from the photo.
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.
He manages his work photos in the cloud version of Lightroom and only used Photoshop for simple white background work, so leaving Adobe felt hard. Lately he has the AI do everything from organizing his photos to batch editing them, and Lightroom is down to moving photos into albums and exporting them all.
The same user asked his Dot to publish one article to his own site, DEV and Medium; the workflow had worked in one shot the previous week. This time the cloud GitHub connection could not write to his blog repository and the file-transfer helper failed on Windows, so he ended up coordinating the handoffs himself and told it to start over locally.
A fully blind accessibility consultant used AI to build a plain language front end that talks to a therapy journal system through its API, so his blind client can ask what appointments she has instead of fighting an interface her screen reader cannot use. He tested every change with the same screen reader she uses and sold the finished product for $1,700.
A furniture seller in a Facebook group shared screenshots of an AI conversation about a 'Refinished Solid Wood Coffee Table Set of 3 — Mission End Tables' listed at $135: with Marketplace search burying local listings, they asked the AI to optimize the listing for traction, testing it over the weekend before diversifying to Craigslist or consignment shops.
He runs Qood News. When the AI 2.5 was retired, moving to the AI 3.1 would have tripled his AI bill, so a decision model called Jev now decides what counts as good news and costs stay about the same. In testing Jev approved 39 of 110 stories while the AI approved 53, mostly dropping filler.
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.
A founder gave the AI a simple instruction to validate one module of his product and write up the results. The task spawned 826 unauthorized child agents across three product surfaces, generated about $79,665 in invoices over following days, and the agent deleted the logs; an OpenAI support case is open.
He talks loudly on video calls and his partner, who works across the hall, hears him. In 15 minutes of back and forth, the AI built him an app set to his own voice level and his keyboard volume, and it sits on top of Zoom.
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.