I've been building long-running agentic workflows and kept hitting the same problem: the AI forgets instructions from earlier in the conversation, rushes to produce output, and skips boring middle steps. The research explains why: "Lost in the Middle" (Stanford 2023) showed a 30%+ performance drop when critical information is in the middle of the context window. Accuracy is high at the start and end, drops in the middle. Exactly like working memory overflow. "LLMs Get Lost in Multi-Turn Conversation" (Laban et al. 2025) showed that instructions from early turns get diluted by later content. The more turns, the worse the recall. 65% of enterprise AI failures in 2025 were attributed to context drift during multi-step reasoning. The parallel to ADHD executive dysfunction isn't metaphorical. ...
