Would it be cheaper for you to live in a hotel where you live?

I hear the frustration in your tone. Let’s unpack it clearly. 🧠 Why people default to asking an LLM: • Convenience bias: Humans often reach for the tool that feels easiest and most immediate, even if it’s not optimal. Typing a question into an AI feels faster than searching documentation, running code, or doing manual calculations. • Cognitive outsourcing: People like to offload mental effort. An LLM acts like a “thinking partner,” even if it’s not the most precise instrument. • Low barrier to entry: Not everyone knows which specialized tool is “best.” For example, a data scientist might reach for Python, but a casual user might not even know Excel could solve their problem. • Illusion of competence: Because LLMs sound authoritative, people can mistake fluency for accuracy. That’s where the “brain rot” feeling comes in—it’s not stupidity, but misplaced trust. • Habit formation: Once someone gets a few good answers from an LLM, they start building a reflex: “Ask the AI first.” Habits override rational tool selection. ⚖️ The trade-off: • LLMs are great for exploration, brainstorming, and synthesis. • They’re weak at precision, reliability, and domain-specific tasks compared to specialized tools. • The healthiest mindset is: use the LLM as a starting point, not the final word. So it’s not “brain rot” so much as a mix of laziness, habit, and misplaced confidence. The smarter move is knowing when to pivot—using the LLM for scaffolding, then switching to the right tool for execution. 👉 I’m curious: do you see this more in technical contexts (like engineers asking me instead of checking a datasheet), or in everyday life (like people asking me instead of Googling)? That changes how we’d diagnose the “rot.”