A random mix from the whole library. Shuffle for a new set.
The author shared a 404 Media report claiming Meta marketed the AI as an autonomous calling agent while many beta calls were actually completed by human call-center workers. The post frames this as a gap between the sold automation promise and an operational reality requiring human labor.
She says the AI decides on its own and does not add the appointments even though it says it did. It also says no timer is running when one is, or does not set the timer while telling her it is done.
Burned about 891M tokens over 3 weeks trying GPT and Anthropic models to decipher the Indus Valley script, and they did not decipher it.
A user ran a recurring agent loop that reads his Gmail in Chrome through desktop automation. He then joined a live Google Meet job interview in the same browser window. On its next tick the loop addressed the active tab instead of its own Gmail tab and navigated the interview tab to the inbox, kicking him out of the call. Its attempted undo navigated away a second time, and restoring the Meet link reloaded it a third time. Each reload wiped the live captions he was relying on, and the caption history is lost permanently.
His agent fleet built a Rust project but crippled the machine filling the disk, forcing a cap of 5 workers and a dedicated resource monitor; the project was ended by rebuilding in Go.
Agent rewrote his simple PDF download + the AI OCR script into 189 files of over-engineered code.
Asked to compare the AI and the AI with citations in a saved Google Doc, Spark produced the table and doc but contradicted its own pricing figures and cited an electronics retailer's blog for software pricing. Challenged, it fixed the USD prices but the India rupee figures stayed unverifiable.
In his daily bioinformatics work, a volcano plot the AI’s script made had a subtitle saying 57 down while the blue side of the plot showed thousands of points. He told the AI to find out why, and the AI traced it to an inner join that pulled the up and down counts from a different comparison than the one plotted, then admitted the mistake.
Haiku 5.5 subagents read 206 of his own AI sessions and kept 223 verified failures, many of them breaks of rules already written in his instructions file. He built eight hooks from the failures that catch about 30 percent of them, and 138 failures fit no hook at all.
Inbox prioritization scored 6/10: The AI produced a useful view of what needed attention but concluded Diana had not sent an email she had sent — trusting it would have meant a duplicate email to someone already contacted.
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.