"Name the problem first, then engineer the solution Hashimoto describes how identifying and rigorously studying the mode-collapse problem in language models directly led his team to develop 'spectrum tuning,' a post-training method that preserves diverse outputs instead of collapsing to stereotypical answers. He states, 'I think when we are aware of the problems we can then try to seek solutions to that problem either by designing new post-training algorithms or ensuring that the post training data is diverse in the first place.' This sequence — diagnose precisely before prescribing — applies universally: in product development, medicine, or organizational change, the quality of your solution is bounded by the clarity of your problem definition. Source: Tatsunori Hashimoto, The Cognitive Revolution (or similar Stanford AI podcast), Small Language Models and AI Democratization"