poteto@poteto

量确实重要 听着，我懂。如果你在 agent 出现之前就是工程师，那你对拿代码行数和 PR 数量来衡量任何形式的生产力持怀疑态度，完全合理。我也同意！或者说，至少我以前同意。为了方便解释，我会从一个至少 50 人的大团队里的工程师视角来讲。 以前量不重要，因为我们看的是影响力。就算 PR 不多，你也可以有很大的影响：比如改一行配置，就可能给公司省下几百万美元。 但在 agent 出现之前，我看到量被拿出来讨论的时候，基本都是针对极端情况。差的一端可能是表现吃力的人，另一端可能是“编码机器”型的人。所谓编码机器，就是那种能把自己关在房间里，出来时抱着一摞 PR、解决了一大堆问题的人。所以量确实重要，但只在分布的两端，而且要和影响力结合起来看。 如果你在大厂干过，你就懂我的意思。agent 的特点是，大厂的问题现在也成了中小公司的问题。 agent 怎么改变了这笔账？嗯，现在每个人都有能力成为编码机器。你手里有极其强大的前沿模型，写代码比我们任何人都好，速度也比我们快得多。在这样的世界里，如果你产出的 PR 数量还和以前一样，你难道不会停下来想想，为什么自己没有变得更高效？外星智能都来了，你却还比不过一个人类编码机器？ 这又回到我为什么一直在讲信任。如果你没下功夫去建立对 agent 输出的信任，就很难把生产力规模化。 没错，这种做法确实需要更多 token，但我是从“每单位智能的成本”来考虑的。在 agent 之前，这个成本非常高——你得雇很多拿六位数高位年薪的软件工程师来干活。token 现在还是贵，但算上智能的成本，它很可能会随着时间变便宜。今天看起来离谱的开销，6 个月到一年后很可能就负担得起了。一个用 agent 的工程师，能干几十甚至上百个工程师的活，成本只是零头。 我觉得大家还没真正意识到的现实是：软件工程师的工作真的变了。我们的工作不再只是生产软件（好吧说实话从来都不只是写代码，但为了解释先忍我一下），而是打造那台写软件的机器。这种软件工厂的想法，或者我喜欢叫它米其林厨房，现在还是个研究课题。这也是我喜欢分享的东西，不是为了炫耀，而是想让你们看看，当你在大规模使用 agent 时投入大量严谨性，能做到什么。

volume does matter look, i get it. if you were an engineer before agents came along, you're rightfully skeptical about lines of code and number of PRs being used as a metric for any kind of productivity. and i agree! or at least, i used to. for ease of explanation i will talk about this from the perspective as being an engineer on a large team of at least 50. volume didn't matter before because we focused on impact. you could have high impact even with a few PRs: for example you could make a one line config change and save the company millions of dollars. but before agents, the times where i saw volume come into the conversation were for the outliers. on the negative end you might have someone who is struggling to perform, on the other end you might have someone who was a "coding machine" archetype. a coding machine was someone who could just lock themselves in a room and emerge with a stack of PRs that solve a huge number of problems. so volume did matter, but only at the tail ends of the distribution, and combined with impact. if you've ever worked at a large tech company before, you'll get what i mean. the thing about agents is that big tech co problems are now small-medium co problems as well. how do agents change this calculus? well, everyone now has the ability to become a coding machine. you have incredibly capable frontier models that can write code better than any of us, at a rate much faster than we can. in this world, if you're still producing the same number of PRs as before, why wouldn't you pause to wonder why you're not being more productive? alien intelligence is here, and yet you can't outship a human coding machine? this brings me back to why i keep talking about trust (https://x.com/poteto/status/2102050467505430555). if you haven't put in the work to trust your agent's output, it is very difficult to scale up your productivity. and yes, this approach does require more tokens, but i think about this in terms of cost per intelligence. before agents, this cost was very high - you needed to hire many software engineers with high 6 figure salaries to do the work. tokens are still expensive today, but are likely to get cheaper over time (https://x.com/theo/status/2107924138094703084) factoring in the cost of intelligence. what looks exorbitant today will likely be affordable in 6 moths to a year. a single engineer with agents can do the work of tens if not hundreds of engineers, at a fraction of the cost. the reality that i don't think has hit yet is that job of the software engineer has truly changed. our job is not merely to produce software any longer (well tbh it was never only about the code, but bear with me for the sake of the explanation), but the machine that writes the software. this idea of a software factory, or a Michelin kitchen as i like to call it, is still a topic of research. and it's the type of stuff i like to share, not to flex, but to show you what's possible when you put a lot of rigor into using agents at scale