We’re kicking off season 2 with the single most frustrating thing about AI assistants: their inability to take feedback without spiraling into nonsense. Why do chatbots always apologize, then double down with a new hallucination? Why can’t they say “I don’t know”? Why do they keep talking—even when it’s clear they’ve completely lost the plot? This episode unpacks the design flaws, training biases, and architectural limitations that make modern language models sound confident, even when they’re dead wrong. From next-token prediction to refusal-aware tuning, we explain why chatbots break when corrected—and what researchers are doing (or not doing) to fix it. If you’ve ever tried to do serious work with a chatbot and ended up screaming into the void, this one’s for you.