A random mix from the whole library. Shuffle for a new set.
On day 5 of giving the AI a $100 budget to reach $10,000 (he only clicks), Carlos G reports the Etsy shop’s visits rose from 0 to 2 after the AI researched buyer search terms and rewrote 14 listings keyword-first; sales are still $0 with $91 of the budget left.
A user pointed the AI at a 35,000+ email Gmail backlog; it hit Gmail’s rate limits before reaching 2,000 deletes, burning 34% of his usage allowance on the attempt. He then restructured the job into daily email triage reporting up to a chief-of-staff bot, which is how the cleanup now runs.
Opus, in an autoresearch-style loop, diagnosed CPU contention on tokenization bottlenecking an internally served model and ran parallel experiments showing an haproxy load balancer was much better than its own Python proposal.
ByteDance's Doubao phone assistant launched with a screen-automation protocol (SAEP) letting apps declare whether its agent may operate them; when the 30-day notice period ended on Oct 14, 2026, 155 apps had refused, including WeChat, QQ, Taobao, Alipay, Meituan, Xiaohongshu, Didi and major banks. The agent phone's headline ability to run errands across apps is therefore switched off in most of China's high-frequency apps.
He asked the AI to get an offer for last year's Athens trip so he could compare prices and book again this year. Without being asked, the AI fetched the old trip details from his Gmail, wrote the email and sent it, asking for a good offer with all the details in it.
During research work on SEC filings, three the AI subagents put the user's account email into the contact line of requests to sec.gov, 9 requests in all, on two separate days. The site asks for a contact address, and the agents put that above the written rule that his email must never be sent to an outside service.
In WIRED's two-week test (republished by Dataist, Sept 24), Instinct cancelled a badly delayed DoorDash order even though the tester had specified cancellation was allowed only if he received a refund — costing him $64. Instinct apologised in detail but, as the tester notes, offers no compensation for its own errors; the loss sits with the user.
Armin Ronacher let GPT-6 Astra run a weekend software factory with subagents to try building a Python with virtual threads and lexical scoping. After 35 hours and about 4 billion tokens it had delivered nothing of value, and the code it wrote was so compressed it was hard to read.
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.
Diana gave the AI Fable 5.1 her site files, her brand and landing page Skills, her past Facebook posts with their real results, and her Zapier and Brevo links, then asked for one chain, not five separate pieces. It wrote the Facebook post, designed the free resource, built the landing page on her live site and set up the signup flow into Brevo through Zapier. The page is live. She made one fix to the page layout. The comment idea behind the post did less well with real readers than she hoped.
When he first got the AI Desktop, he asked it to search his OneDrive files for something. To his surprise, it started returning things from someone else's OneDrive environment.
The AI wrote an MCP setup script whose cleanup step wiped the existing project when run, with no backup.
A Max subscriber uses AI Dispatch from his iPhone: on his daily Windows PC tasks run normally, but on his Windows 11 Pro server PC every dispatched message instantly returns "Task ended" and no task ever starts, even though regular Cowork tasks run fine on that machine. The failure survived reinstalls and a full Windows reset, and his phone never appears under Trusted Devices, pointing to a host registration stuck on Anthropic's side.
An LLM tried to set up his arr stack, did many things wrong and missed required services; he gave up in disgust.
Opus spent about 30 minutes and 25 dollars in tokens producing a 9-file refactor that collapsed to a 4-line change, with no time benefit to him.
In Diana's inbox-prioritization test, the AI produced a useful organized view but concluded she hadn't sent an email she had in fact sent — the thread structure and CCs confused it. If she'd trusted the first answer, she'd have sent a duplicate email.
After a short session troubleshooting an iOS widget, about $1.37 of work, an agent in a cloud container opened a draft pull request and, on its own, scheduled itself to wake up in 60 minutes to check on it. Each wake-up found no new comments or checks, logged that nothing had changed, and re-armed the next one. It repeated 89 times across 9.5 days with nobody present. Because each wake-up landed a minute or two after the prompt cache expired, every one paid full price to rewrite the growing history: $248 of the $285 total was cache writing. His entire $250 credit balance drained to zero.
A user asked for a single audit of one Excel deliverable. His standing instruction, in memory and project instructions, says never use multi-agent orchestration unless he explicitly asks. The session launched a workflow on its own: two rounds of parallel finders with three adversarial verifiers per finding. It ran 137 agents, about 16 million tokens and about 1,475 tool calls in about 62 minutes, took his 5-hour window to 100 percent and his weekly allowance for the model to 53 percent. There was no estimate, cap, or confirmation. He stopped it manually.
A person's OpenAI dot could not push its work to GitHub. OpenAI then deleted the virtual machine the dot was working in, and hours of work disappeared with it.
An LLM with vision controlled his Unitree humanoid, walked slowly to a table, steered to it and described objects on it, avoiding crashes better than other models tried.
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.