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lauren· @poteto · X·· 2 小时前AI 评分42
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Lauren Tan 提出用"time to rewrite"(ttr)作为粗略启发式,估算代码库为 AI 智能体准备好的程度:假设用不同语言/框架/架构重写代码,单个工程师需要多久。ttr 数值本身不重要,关键是它引出验证能力、重写质量、性能是否退化、代码是否易删易扩展等方向性问题。她强调这只是思维实验,尚未成形。

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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