The 'CARE' benchmark reveals that top-tier LLMs like GPT-5.5 and Opus-4.7 consistently lose up to 20% of user intent during planning phases. Even when models successfully include requested features, they frequently strip away the nuanced emotional context and specific operational requirements that define the user's ultimate goal.
Topics: Artificial Intelligence, Prompt Engineering, LLM Benchmarking, Software Development, Agentic Workflows
