This is exactly why I'm building persistent memory for AI coding tools. LLMs hallucinate facts partly because they lose context between sessions. When they "remember" your project structure, past decisions, and error patterns, accuracy improves dramatically. Still not perfect, but context retention helps a lot. Curious what others are seeing - is it mainly hallucination or context loss that causes wrong answers?