Aaron Levie：AI 生产力上限两年从 30-50% 升至 5-10 倍
The divergence in AI output weirdly may be the highest it’s ever been, even though adoption is the broadest it’s ever been.
Box CEO Aaron Levie 认为，AI 采用面最广的同时，产出差距可能也达到历史最大：两年前即使最擅长使用 AI 的人，在编程等领域的生产力提升也只有 30-50%，如今视领域不同可达 5-10 倍。他指出，模型能独立完成更长任务、harness 支持智能体工作、训练数据质量提升减少了人工干预，而 RSI 的进展会让这一差距继续拉大。
查看原帖在世界上的某个地方，很可能有一整个由 6 名开发者组成的团队，全职投入一个项目，而这个项目不过就是一条 Claude Code 提示词。
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Somewhere in the world there’s probably an entire team of 6 devs, working full time on a project that’s just one Claude Code prompt
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The divergence in AI output weirdly may be the highest it’s ever been, even though adoption is the broadest it’s ever been.
A few years ago the best productivity gains you could get, even in the most capability-aligned field (like coding), was maybe 30-50% better productivity if you were very good at it. You’d spend a decent chunk of time cleaning up the mistakes of models, the context windows were too limited to do any long running work, and the interfaces required highly synchronous interactions.
Now, the models can do far longer tasks at a time with limited human interaction. The harnesses support agentic work that can take on these larger tasks. The models are trained on vastly better datasets for a growing array of domains so you have to intervene far less. And we have systems that better support working with many agents at once.
In just a two year timespan, the upper limits on productivity gains have gone from 30-50% to now likely 5-10X depending on the field. So we’ve gone from an environment where living at the frontier vs. not paying attention at all could be an order of magnitude difference in your output.
This distance is only getting wider from here given the rate of progress we’re likely to see with RSI. Crazy times.