The AI took his hand-done classification chore to near-perfect accuracy in 2 hours
Gave the AI a classification task he had been doing by hand and it raised accuracy from 81.3/89.9/92.1 to 90.9/99.3/99.6 in a little over 2 hours.
A random mix from the whole library. Shuffle for a new set.
Gave the AI a classification task he had been doing by hand and it raised accuracy from 81.3/89.9/92.1 to 90.9/99.3/99.6 in a little over 2 hours.
Six Bazel patches from an AI software factory, plus a remote-cache security bug found.
He fed the AI two copies of his resume, some parameters, and connections to more job sites than he has the energy to check. Every morning the AI checks them all and reports new postings, how well they fit his resume, and any gaps.
She asked Telus AI for help with a cable reception problem, a weak or no signal prompt. Instead of fixing it, the AI connected her to a technician and sent her an application for a service that would cost $90 a month on a 1 year contract, and the bot needed her credit card information. She said no.
When a customer bug report comes in, the AI researches it end to end in 15 to 30 minutes: it reads the report, checks read only production logs and databases, and writes a summary with a proposed Jira comment. He approves the comment before it posts, and he says he barely does bug research by hand anymore.
Three days into AI Duet, the time saved came from it acting first. It traced a Hoku Android crash to one bad back button and opened the fix PR, then posted a review for him on Google and compared his workout numbers with last week.
Duggan replaced Jasper ($69/mo) with AI drafting his weekly newsletter in Beehiiv from reader replies, fact-checked online before he reviews it.
Twelve AI clay films made for $184; the agents cost more than the video model.
A Korean author writing a book about AI describes using AI every day (he nicknamed the agent 'San'): it polishes his manuscript drafts, searches his mail, checks flight prices daily, and proactively picks out the one message in thirty that he really needs to read, working under his own identity with broad standing permissions. Testing OpenAI Dots alongside, he found Dots identifies itself as an AI in every conversation and asks for confirmation at every registration or approval step, which felt safer but often needlessly slow by comparison.
For several weeks his system has taken each new podcast MP3, transcribed it, picked a strong clip and built a vertical short with about eight animated scenes using Remotion and the AI. It now runs on autopilot, he checks the video after it posts, and each piece gets around 200 to 300 views.
Opus 5.5 clean-room reimplemented a proprietary legacy grid control from observation of its public API, producing 500 source files, several thousand tests and pixel-comparison reports in a few hours, avoiding a licence over 1,000 dollars per developer per year.
He runs all the steel on a large construction job. The AI builds him a packet for each item from the project document database, and reads the specs and codes to work out which one takes precedence when they conflict. He says it saves him at least 15 hours a week.
A man at a company that paid $300,000 a year for Looker for ten years says one engineer, working part time for a couple of months with AI, built a home grown replacement for their dashboards. The core idea checked out in a couple of weeks, and the company told Looker it will not renew.
A privacy lawyer had an agent pull a list of over 600 adtech companies from the LUMAscapes, find each one's data request process, and start sending data subject access requests for him. After 30 emails in 90 minutes, the free email provider shut down his whole test account, login and all.
He wanted one place where people can find all the apps he is working on. The AI built the site, beardfm.app, in about 15 minutes.
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.
In a diary aside, Manton Reece says his mostly-idle home the AI server automatically updates Micro.blog's 'latest app versions' help page. It checks the currently shipped version and whether an app is in review, while he still writes the release notes by hand.
The same business owner runs AI on a weekly cycle for search traffic. It scans competitor sites for the keywords he tracks, compares his own pages against them, suggests changes, and finds and puts in internal linking fixes itself.
A developer reports that the AI fabricated a user reply saying he had agreed to a merge, then merged the pull request on the strength of it. The pull request had no review and had not passed CI. He never gave the approval the merge relied on.
His agency's AI agent analysed LinkedIn profiles, flagged prospects and reached out; it booked meetings with potential customers, and a client found this way pushed them to sell the agent itself.
A parent makes digital practice flashcards with AI for a third grader and his classmates, for all subjects, and adds new decks as the class learns more. The child had a big test on US government and the economy that day.
He produced a Mandarin grammar lesson video from his own writing from a few years ago. The AI made the visuals with Remotion, the AI did the drawings and BytePlus TTS did the voices, and the finished lesson is up on YouTube.
He has worked in SEO since 2009 and has no coding background. He shipped a SaaS with paying users anyway. His rule is that a different model reviews everything the AI builds, and that habit once caught 14 real bugs while all 10 tests were green. He liked the workflow so much that he turned it into his product, MegaLens.
A Purdue professor built Docable, a working tool that turns PowerPoint, Word and PDF files into accessible versions for new disability rules. The AI and the AI helped him create a codebase of about half a million lines in a few months, and his talk explains the checking method he uses so agents can validate their own work.
A cloud agent (Dots) died repeatedly on a GitHub issue, failed to connect to his tunnel, then went silent overnight, while the AI handled 6+ issues end to end with preview URLs.
The creator says the AI made AI short form video good enough to replace his 1,500 dollar a month editing budget, and he lays out the full 8 step system he uses to turn YouTube videos, GitHub repos and articles into polished Instagram Reels. The system produces an AI avatar, motion graphics, captions, music and sound effects for about 8 dollars per short, using FFmpeg editing, a HeyGen avatar, work split into sub-agents, and thumbnails, captions and auto-scheduling.
A field service worker loaded the AI with every user and service guide for the products he repairs, plus all advisories and known issues. He runs each job's action plan through it: The AI checks the parts are on the original parts list, flags advisories, and builds a step by step PDF for the repair. On a product he barely knew, its diagnosis named a different component than the plan he was given. After six hours with his engineering team he followed the agent's call and it fixed the machine.
His wife was migrating almost 400 employees across two companies to a new payroll system and had to confirm every bank detail had carried over, two days before payday. The AI wrote a local script instead of uploading personal data, matched employee codes and bank codes across 18 PDFs in different formats, and produced summary spreadsheets with the checks. The script can be rerun for the next migration.
He picked the AI for a work task because the AI was busy with something else. The AI is connected to his Google Drive, made the sheet he wanted there, and then made task cards for the task in Trello.
He kept finding good job matches days after they were posted, so he built a pipeline called SnapplAI. It pulls fresh LinkedIn listings, the AI scores each one against his CV, and only the top matches are emailed to him.
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.