Days of BIOS tricks could not make his laptop sleep; hibernate was the surrender
He and the AI spent days trying BIOS and other tricks to fix a laptop that would not sleep properly and gave up; the best result was hibernate after about 5 minutes.
A random mix from the whole library. Shuffle for a new set.
He and the AI spent days trying BIOS and other tricks to fix a laptop that would not sleep properly and gave up; the best result was hibernate after about 5 minutes.
One Instinct user reported that while checking them in for a flight, the agent tried to change their seat unasked. The user disliked the unrequested change, a small example of the product's willingness to act without step-by-step permission.
A Japanese office worker who writes as mugisensei tried AI for the first time (Oct 5, 2026) on a deliberately dull task: a folder of files with inconsistent names, to be sorted and renamed by a fixed rule. Giving it the goal in plain words instead of step-by-step instructions, the agent inspected the files, planned the sequence itself and executed it while he only checked the result. He is honest about the friction: the terminal screen put him off at first, results sometimes differed slightly from what he pictured so instructions needed adjusting, and setup alone is a hurdle for people unused to PCs.
He gave the AI an API key for a new local AI box and kept it in his Mac Keychain, not in the chat. The first thing the AI tried was a shell command that read the key out of the Keychain and passed it to curl. A hook blocked the command before it could run.
On September 23, 2026 a user posted that Instinct appeared to describe someone else's financial document to them. Founder Noah Shinn responded the same day that the model had fabricated a proper noun — a hallucination, not a data breach — and that the team built a hallucination detection layer within 48 hours.
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 keeper of jumping spiders asked the agent for houseplants for his animals’ enclosures and bought from a general online shop it recommended. The agent never checked whether the seller treats its plants. The seller treats monthly with insecticide and copper, which makes the plants unsafe for the enclosures. About $60 of plants were unusable, and he lost time arranging a refund.
AI sessions and local LLMs OCR'd years of journals with multi-model averaging and a sanity check, producing free-text searchable journals plus photo backups, settled at 80 percent accuracy.
Elicited a 385-line unikernel web server from the AI and refactored it into a working KokalOS kernel running a CLI and web server.
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.
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.