Opus 4.7 不是升级，是范式转变

Claude Opus 4.7 marks a fundamental shift in AI programming, moving from simple model intelligence to a self-disciplined, agentic workflow. The core breakthrough lies in the model's ability to autonomously generate and execute verification loops, requiring developers to provide robust testing environments rather than just prompts. Significant technical changes include the removal of manual thought budget parameters, the disabling of temperature settings to enforce deterministic output, and a new tokenizer that increases costs. While performance gains are substantial in complex, multi-file production tasks, they remain marginal for simple queries, illustrating the "jagged frontier" of AI capabilities. Adapting to this version necessitates a transition from pair-programming to managing parallel, agent-driven workflows, supported by proactive project documentation and rigorous regression testing to navigate the transition from version 4.6.