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A widely shared Hacker News gist claims Qwen 3.8 reproduces GPT-5.5 Pro's reasoning prefill behavior.
A gist circulating on Hacker News claims the Qwen 3.8 model follows the same reasoning-prefill patterns observed in GPT-5.5 Pro. The post drew 41 points and 8 comments, but no technical details are included in the available text.
AI researcher Nathan Lambert argues LLMs remain weak at long-form technical writing, questioning whether models can autonomously organize scientific knowledge for breakthroughs.
Nathan Lambert describes writing a post-training textbook, Reinforcement Learning from Human Feedback, and finds today's LLMs weak at organizing long-form technical content despite becoming superhuman at coding and math. He notes GPT 5.5 Pro found deep typos across a 200-300 page manuscript while Claude models proved more useful as editors. He argues that compressing knowledge through writing is a prerequisite for autonomous scientific insight and tempers expectations for near-term AI-driven open science.