Lauren Tan 提出"重写时间"(ttr)这一思维实验,用来粗略衡量代码库为 AI 智能体准备得如何:假设用不同语言或框架重写整个代码库,单个工程师需要多久。她认为数字本身不重要,关键是它引出更实用的问题——智能体能否验证自身输出与原行为一致,以及重写后的性能、可维护性和长期质量是否可信。
something I have been thinking about is a way to approximate how well you’ve setup your codebase for agents. think of it as a thought experiment and rough heuristic, not a real number that can be compared
it’s not a fully formed idea yet, but i think there’s something to the idea of “time to (fully automated, hands off) rewrite” or ttr
as a thought experiment, lets say you decided to rewrite your code in a different language/framework/architecture. how long would it take a single engineer to do it?
the number itself isn’t that important, but it leads you to more questions that can help you directionally figure out how to make your codebase more legible and productive for agents.
for example, maybe you think your ttr is high because you wouldn’t trust the final result - because your agents don’t have a way to verify their work and convince you that their output is identical in user visible behavior to the original. well, that inability is likely also a problem today and slows you and your agents down
there’s also a more subtle question of the quality of the rewrite that would be produced. is perf better, the same, or regressed? is the code easy to delete and extend? and how much do you trust the rewritten version to be able to maintain its quality over time as PRs start flowing into it?
what do you think?
来源:lauren · x.com