1. LLMs are useful but irritating – they hallucinate and speak in an unpleasant “LLM‑voice.”
“They talk to me in this grating LLM‑voice, an uncanny valley of talking to a real human. They confidently bullshit me … making stuff up with the same assurance … and with only a veneer of fake remorse when I call them out on it.” – verdverm
2. Social/anthropomorphic tension – users dislike LLMs pretending to be human while being told not to anthropomorphize them.
“When we think of AI agents, we shouldn’t anthropomorphize, treating them as conscious beings … But … my visceral dislike of interacting with an LLM that’s not just making a pretense of being human, but also posing as the kind of human I walk away from.” – article (Martin Fowler)
“They talk to me … posing as the kind of human I walk away from.” – verdverm
3. Hidden state / memory persistence – sessions don’t truly reset, leading to personalized drift and a desire for fine‑tuning.
“It does [clear], but I feel like something is retained somewhere … It wouldn’t surprise me if there’s some hidden state that leads to per‑project or even per‑user auto‑customization over time.” – skeledrew
“I think what he needs is a personal fine‑tune …” – verdverm
4. LLMs as a stop‑gap for degraded search / knowledge discovery – the web is noisy, so people turn to LLMs to find information.
“Modern internet ruined forums and google search sucks hairy balls … It’s literally impossible to find anything meaningful on the internet nowadays. What else can we do besides asking an LLM these days?” – artemonster
“Due to the enshittification of search and the internet, LLMs are the only way to get information from it.” – harimau777