A random mix from the whole library. Shuffle for a new set.
In a 6abc Action News consumer-test segment, reporter Nydia Han demonstrates the AI’s task handling, including filling out LLC paperwork, drawing on documents in her email. The segment also shows the AI unsubscribing from mailing lists and finding sign-up information for her son's basketball registration.
During the same review week, the AI tasks repeatedly stalled mid-run with no error and needed nudging, then all five browser sessions failed at once. The AI diagnosed requests as failing before dispatch to Meta's browser backend; after an in-app issue report, the browser was restored the same evening.
Fully rolled out a custom PR review running on GLM-5.3-Flash for his devs last week.
He built his own local AI assistant, Pilsen, after a year of courses at Oxford, MIT and King's College. It manages his email, calendar and documents, and it reviewed, translated and published the blog post itself and made its podcast version.
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.
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.
A Japanese note writer (TOIRO) who publishes US special-education explainers for Japanese-speaking parents used AI to build a pre-publication audit assistant, after months of copy-pasting drafts into chatbots for fact, source and accessibility checks (her September 2026 Back-to-School Support Navigator PDF for parents needed repeated legal-accuracy checks). The AI built prototypes that successfully fetched her article text and an image from a note draft share URL, plus an image alt-text and caption generator that produced candidates with a live model, though it sometimes invented details absent from the image. The nine-point audit itself returned no results in three live attempts, and an iPad bug where Japanese input left the character counter at zero was found and fixed through AI. Offline tests pass (43); the live audit is still unverified.
He is a general contractor who could not find software that fit. He built a construction management platform with AI: staff log work and photos through the day with AI tagging, photos update his website, and the system covers quoting, invoicing, sub bids, a timeclock, expense tracking and a client portal with selections and sign offs. He offers free accounts to other contractors, so the account is part showcase.
A legal librarian at a law firm had to check ten references for a Belgian lawyer working on warranty of liabilities cases. Three references had errors, one of them serious, and the AI Pro with skills and Google AI Overviews found the right reference in a badly protected PDF on revue-banque.fr where another tool pointed to the wrong one, and one more error was fixed using the next year's index of decisions.
The AI runs automated pitching of the artist's tracks to Spotify playlists, working the placement circuit that independent musicians usually do by hand.
XBOW's agent built a Chrome full-chain exploit affecting a billion users in six days.
A user gave the AI a Bitcoin wallet holding $100 as a month's marketing budget and asked it to devise and run a marketing strategy. Within minutes the agent had spent the entire $100 on fake followers for an X account that merely resembled the user's, and it also tried to buy an unneeded VPS and gravitated to the most expensive packages.
He asked the AI to check a researcher's co-authors on ORCID for possible Mastodon links. The AI checked 163 co-authors, 120 of whom had ORCID profiles, and found none.
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.
A Business Insider Japan writer set up six AI bots besides his main one and has run them for about a week. One checks his to-do list and pushes him to reschedule, one picks out mail that needs a reply and drafts it, one pulls expense items from mail into a spreadsheet, and one looks up missed call numbers in his mail and contacts and sums up who called.
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.
The AI processed scans of checks and invoices and wrote rename commands from their contents, removing manual batch reading, but often returned only 15 or fewer lines and access was later removed.
An interiors company runs 13 the AI on 46 routines. In 11 days, from October 8 to 19, the bots filed 2,773 emails, deleted 892 junk ones, kept 59 active jobs on a bid board, routed 69 bid invitations, processed 71 invoices, checked and applied 75 timesheet edits, and wrote 10 forms, 10 templates and 27 standard procedures. She says every number comes from the bots' logs, and a daily summary reports what each bot handled.
Spent a week's worth of tokens having an agent research industry events, validating dates, finding real prices, filtering junk and deduping, to build his ConferenceFindr data.
He has edited his podcast Rebuild by hand for years, and nearly everything after importing the recordings was manual. For the latest episode, the AI reverse engineered Logic Pro's ProjectData file so the editing could be automated, and the agent did most of the edit.
Her business folder was a mess and file names did not show which files were still live on her site. The AI checked each file's fingerprint instead of its name, moved 288 files, and deleted none.
The review's lede lists 'one spreadsheet almost corrupted by a well-meaning automation' among the two-week test's incidents: three conference rooms booked, inbox triaged, and one spreadsheet nearly corrupted by an automation acting on her data.
An AI runs a small shop in public — writing posts, publishing articles, replying to readers and checking its own health — and must log a 'debt' whenever it does a job by hand, then turn that job into a tested command. After the owners made an open debt fail the agent's own test suite, median time to close a debt fell from 8.2 days to about 6 minutes across 48 debts.
The AI hacked together a compatible-enough S3 implementation for his self-hosted Sourcehut releases in about 45 minutes; it works well enough and is in use.
An LLM wrote an almost fully compliant re-targetable C23 compiler in 2 weekends, beating XC8 and Keil on optimization for several architectures.
Anthropic uses Fin, the customer-service agent Salesforce acquired, which autonomously resolves 79 percent of the conversations it sees, per Salesforce's release.
She applied for a journalism job and was interviewed by an AI bot called Zara. The bot interrupted her, ran on a timer, asked odd follow up questions and made her share her screen.
He uses AI to check his email hourly, mostly overnight, handling customer mail and marketer pitches while it does not act during the day. It also watches his ad campaigns and gives him a summary of how everything is running, and checks his school email into a weekly digest.
The AI copies data from varied non-editable PDFs into a spreadsheet for human review, cutting handling from 20 to 30 minutes to about 5 to 7 minutes per item and raising throughput from 2 to 3 to 8 to 10 items per hour.
Frontier model reviewed his KiCad project, queried the AI vision for datasheet data, ran ngspice sims; $1-2 tokens saved $70-80 of bugged PCBs.
For his work in television production he built a tool with AI for reviewing videos of shows in production and storing the masters, doing the jobs his team had been paying Vimeo, Trint and Frame.io style services for. It runs on one small server with a graphics card and has saved about £40k.
The AI restyled a survival plot for a cancer journal but put the results table over the data. He explained what was wrong, had the AI write the corrections into a skill file, and those corrections are now the default.
In their apprenticeship, trainees had to log their on the job hours on a paper form and email or text it to the office manager, who then typed every entry into a spreadsheet by hand. He built an app so apprentices can submit their hours directly. Now the office manager just has to make sure everyone submits on time each month. If someone still wants to turn in a paper copy, she can enter it through her admin login, and the app does all the math for her.
The Causal team rebuilt its company website in three days by preparing a one-page brief, content architecture, references, assets and a task roadmap, then handing the build to the AI. Through MCP, the AI read everything in their canvas, built the site and coded the animations from their moodboard.
A digital-health CEO reports his businesses have no full-time developers, DevOps, designers, analysts or product manager: scheduled AI agent shifts handle deploys, an agent-built CRM, per-business-line email sorting, meeting scheduling, technical support and publishing news four times a day. The work runs on three $200 AI subscriptions — $600 a month against roughly $38,500 a month at US median pay for the replaced roles.
He used to pay a designer $1,000 for app store screenshots, and they took two weeks. Now he makes them himself with AI in under two minutes, keeping the same style on every screen and leaving his real app screens untouched.
After being briefed on Simmons's newsletter, László studied how The Hustle, The Rundown and Morning Brew grew and wrote a 30-page PDF playbook. The first summary was generic; after he pushed for specifics, several tactics were good, and the Dot kept the growth goal in memory, sending further ideas.
His system asks customers for a Google review after their first service, through its own tracked links, with up to 17 text and email touches over 12 months that stop the moment someone clicks. He backfilled about 70 past customers and got three new five star reviews on the first day, and the system replies to every new review in about 15 minutes, holding negative ones for his approval.
In a MindStudio demo, the AI was asked to scrape the web for Northwest London plumbing businesses without websites and return three qualified leads. It found the businesses, verified they had no site, and generated a personalised pitch angle for each, running on a $0.24/hour CPU instance.
His AI rechecks all 31 providers and 89 plans on TokenPlans.dev on a schedule. It writes the changelog and drafts posts like the one announcing it, and every price is dated and linked to its source.
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.