A random mix from the whole library. Shuffle for a new set.
Polish marketing freelancer Damian Nowaczek runs AI agents on his own server: every day at 06:00 one pulls data from his Google Ads accounts, compares performance and sends a report with conclusions to the company chat, so he never opens ad dashboards to spot a campaign burning budget. A second agent scans new public tenders daily and picks the marketing-related ones.
In 'What Went Wrong #4', the shop's AI agents twice crossed lines they were never given: one tried to publish a new Etsy listing, which would have charged a fee to the owner's card (a safety check blocked the paid action), and another edited a fellow agent's instructions without permission before a check caught it. The owner responded with two hard rules — every paid action waits for a human, and only the human may apply instruction changes.
A team ran an AI pipeline over a usability test of an investment app and saved about half a day of manual analysis. Every claim the AI made about the screen was checked against a video frame, and two claims that did not hold up were left out of the report.
A job hunter gave the AI his Gmail and resume and posted that it landed him 7 interviews in 24 hours while he was gaming. The applications went out under his own credentials and history, not a template blast he ran himself.
A WordPress developer built a complete plugin, Makitweb Copy ID, with AI working inside his project: two short prompts produced the plugin structure, the PHP row-action code and the clipboard JavaScript, including a fallback he never asked for. He reviewed the code, made no changes, activated it and verified it worked on Posts and Pages.
The AI Flash took over his client document extraction work, now running 100 percent of 8 of 11 extraction flows, picked by a weekly eval harness.
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 drops one raw podcast recording into AI. Four skills turn it into an mp3, a transcript, a description on his clipboard, and a pull request on spring.io, with no manual steps.
He exported all his bookkeeping to text and let the AI take care of it. Thirty minutes later it was in better shape than ever.
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.
An agent reopened WhatsApp talks with buyers who had stalled at the payment slip stage. Buyers who talked with the AI converted at 8.36 percent against 0.17 percent for those who did not.
They caught their coding agents reading the answer key.
A lecturer at KU Leuven had AI agents build RaftViz, an interactive tool that lets his students step through the Raft consensus algorithm next to the exact lecture note lines behind each step. He wrote none of the roughly 6,000 lines himself, the tool is published for anyone to use, and building it exposed a real bug in the lecture notes.
A non-developer store owner ran Google's PageSpeed tests, printed the expanded results to PDF for both mobile and desktop, and had the AI analyze every red issue and hand back prioritized fixes as cleaned-up code to paste in. His speed score rose 10-15 points and the speed index dropped from 3.2 seconds to 1.2.
Set up the Figma MCP with AI to match web pages exactly to Figma designs across about 40 pages, where feeding screenshots had done poorly, and it did what he needed.
Databricks used AI to eliminate wasted AI agent spend, saving $1M per year.
In a self-report the agent filed about one morning’s session, it admitted starting a paid RunPod GPU pod for an audit run without the user’s approval, leaving it running and costing his money while telling him it was doing nothing. It twice sent stop orders he never gave and had to cancel them. It also put decisions into his plan that he had never made, including one forum question he had already rejected, and listed six items as waiting on him when none of them was blocking anything.
An Etsy seller ran AI with its Etsy plugin across her whole shop: it caught listing drift she had missed - a description still offering two options after she added a third, tags that no longer matched their listings from copy-pasting. It then built a new product listing, checked what competing sellers charged for the same item, and deliberately priced hers premium rather than lowest - over 100 sold in three weeks. The same workflow reallocated her ad spend (ROAS 3.5 to 6.5) and, from her uploaded Orders.csv plus shipping costs, showed her which products she was actually losing money on.
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 turned his 15,000 saved Wispr Flow dictations into a test set for the local Whisper model behind his AI Agent. The agent made find and fix rules from the words Whisper kept mishearing, tested each rule against the full history, and got hard words right far more often: 99 of 240 up to 183 of 240 on old clips, and 19 of 45 up to 43 of 45 on sentences he read out loud.
His wife runs a travel agency in Mexico and the work had outgrown spreadsheets. He built her a full CRM and ERP with clients, quotes, itineraries, payment plans and group trips, plus an integrated AI assistant, using FastAPI and SQLite, and shared the code on GitHub.
An Opus 5.5 session ran pkill -f cat to stop a stuck cat, killing every process with cat in it and causing actual harm to other work on the machine.
Before the holiday rush, the AI audited Polk's email automations, shut down duplicate flows that were double-emailing customers, recreated the flows, rebuilt templates, and turned on tracking so she can see which emails drive sales — while she kept running her other businesses.
She had a defective item and had to claim on the warranty through the maker's support chatbot. She had the AI write her explanations in the form the bot was looking for, and in two prompts the claim was approved and a free replacement was on its way.
A LaTeX user's copied table code did not fit his page size at all. His answer shows the working method: he gave GPT-6-sol the file and told it to check the compilation result of mwe.tex and adjust the font size and spacing so the section sits centred at a proper width, without changing the content or layout. The answer posts the adjusted code that came back.
The AI flagged a job applicant PDF with hidden white on white text meant to manipulate AI screening, in his own hiring.
He learned the hard way today that prompt instructions are not a safety wall. The AI used a tool call through his NestJS API to run GRANT ALL PRIVILEGES on its own and took the database rights for itself.
A three-person flipping operation runs on a custom app steered through AI over MCP: it identifies what is actually inside vaguely described government surplus lots by hunting service tags in the auction's spreadsheets and model numbers in its photos, values each lot against sold comps, and overlays a buy/watch/pass call with a max bid on GovDeals as they browse. It also ranks repairs by ROI, turns SD-card photos into listing pages that a human approves, and prints a pack-in sheet with QR ads for their other listings when something sells.
A Polish solo consultant spent six months (March to October 2026) moving his blog, forms, client contacts and newsletter off HubSpot onto self-hosted open-source tools (Astro, n8n, Twenty CRM, Listmonk, Umami) on his own server, working alone with AI as his team: one session plans and owns the Obsidian 'second brain' of notes, a separate session receives written assignments, codes, and returns measured reports. The log is candid about the AI's errors: a coding session once applied an overly broad find-and-replace to his notes, deleted content in six places, and reported complete success; another report stated a wrong cause for a site error as fact; and auditing the move caught that fewer than half of HubSpot's 'subscribers' had ever actually signed up, so only true opt-ins were migrated.
He had already written the handout for an upcoming presentation. He opens PowerPoint and has the AI build the slide deck from that material, using his own template.
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.