Every Engineer Is a Manager Now 🤖 — with Chris Lattner

有些人觉得，好吧，将来某个时候，新出的模型会变得完美，所有贡献都能直接搞定。如果是那样的话，那我想说，如果你理论上都能从零开始随便写整个内核了，那还需要开源吗？

Some people think that, okay, well, someday in the next future model that will come out, the models will actually be perfect, and all the contributions just work, and if that's the case, then I'd say, okay, well, do you need open source anymore if you can just theoretically vibe code entire kernels from scratch.

我的意思是，如果你觉得那是个好结果，那对开源项目和开源社区来说，其实也不是什么好事。

I mean, if you think that's a good outcome, then that also isn't really great for open source projects and open source communities either.

我个人对此非常怀疑。

I'm personally very skeptical of that.

是的，我也很怀疑，说实话。

Yeah, I'm skeptical too for what matters.

就像你之前说的，不管AI多厉害，我们也不可能用AI替换掉旧软件，因为从效率、性能、延迟这些方面来说，根本说不通。

Just like before you said, for as good as AI can be, it's not like we're going to replace old software with AI because it doesn't make sense for inefficiency, performance, latency, and da da da.

同时，我觉得可组合性，还有利用我们已经做过的东西，这一点我很难想象会消失，因为我们不可能什么都从零开始重建。

At the same time, I think that composability and using stuff that we've already done, it's something that I find a hard time thinking that it's going to go away because we can just recreate stuff from scratch.

我的意思是，就算我们能做到，那也会显得特别低效，而且很奇怪，我们居然没找到更好的办法来复用现有的东西。

Mean, even if we were able to, right, it would feel like completely inefficient and would feel weird that we haven't found a better way to just reuse stuff.

没错。

That's right.

说实话，这根本说不通。

Well, and it doesn't even honestly make sense.

比如，AI能生成大型软件。

Like, so AI can generate large scale software.

这已经被证明了。

Well, that's proven.

我写了一篇博客，你知道的，讲的是Claude C编译器。

So I wrote a blog post I know you've seen talking about the Claude C compiler.

一群智能体在几乎没有人工输入的情况下，做出了一个C编译器，虽然达不到生产级质量，但确实很有意思。

It's very impressive what a team of agents with effectively zero human input can go and make a C compiler that it's not production quality, but it's it's like in it's it's interesting.

我觉得非常有意思，就这么说吧。

Like, I find it very interesting, let's just say.

对。

Yeah.

但这没什么新意，它能成功是因为训练数据里有大量的C编译器。

But there's no novelty to it, and the reason it worked is because it has a huge amount of C compilers in its training set.

对。

Yeah.

所以基本上就是把现有的LLVM和GCC编译器转译成新的形式。

And so it's basically transcoding LLVM and GCC compilers that exist into a new form.

对。

Yeah.

嗯，这确实很酷，但对于创造新事物、推动世界进步，或者建立人们协作的社区来说，这并不酷。

Well, so that's cool, but that's that's not cool for creating new things or driving the world forward or building consolidated communities of people working together.

我觉得这对那些想剥离许可证的人最有用。所以你会说，好吧。

That I think is gonna be most useful for people that wanna, like, strip licenses And so you say, okay.

我不喜欢GPL许可证。

Well, I don't like the g p I don't like the GPL license.

嘿，Claude。

Hey, Claude.

去把这个从C语言改写成Rust。

Go rewrite this from C into Rust.

对。

Yeah.

现在

Now

这不是一回事。

it's not the same thing.

关于那个也是

About that too

在我的笔记里。

in my notes.

所以，或者这里有一个专有程序。

So or here's here's a proprietary program.

LLVM社区里有个问题，有人拿了一些专有的EDA工具，然后用代理基本上克隆了它们的行为。

There's been a problem in the LLVM community where somebody took some proprietary EDA tools then used used agents to basically clone the behavior.

对。

Yeah.

实际上，他们反汇编了这些工具，还进行了逆向工程，这违反了许可协议，然后生成了一个结果，克隆了这个专有软件的很多行为。

It actually disassembled disassembled the tools and reverse engineered them, which is against the license, by the way, to generate an outcome that then cloned a lot of behavior of this proprietary

工具。

tool.

对。

Yeah.

所以我不认为这只是开源的问题。

And so I don't I don't think it's just open source.

这个问题必须解决。

It's gotta figure this out.

我认为所有软件都必须解决这个问题，但我确实认为这意味着我们应该改变对软件价值、维护者以及驱动它的社区的看法。

I think all software has to figure this out, but but I do think it means we should change how we think about the value of the software that we're creating and the people that maintain it and the communities that drive it.

而且我认为这实际上是很多人甚至没有在讨论的关键点。

And I think that's actually the the key thing that a lot of folks aren't even talking about.

对。

Yeah.

我觉得这真的很有意思。

I mean, this is so interesting.

我对这个话题有好多问题，大概一千个吧。

I have, like, 1,000 questions about this topic.

说到内容和开源项目被这个影响，很多知名人士都站出来说了，从米歇尔·桥本到蒂亚德罗，他们甚至关闭了外部贡献。

So about content and open source autos being overrun by this, I mean, there are many prominent people that are coming out saying this from Michel Hashimoto to Tialdro actually closing external contributions.

而且就像米歇尔说的，这样做就像把孩子和洗澡水一起倒掉了。

And as Michel said, like throwing the baby with the bathwater while doing this.

你觉得这是不是要找到一个更好的工作流程的问题？

Do you think this is a matter of figuring out a better workflow?

因为可能我们之前的工作方式，比如用PR什么的，是为人类优化的，而且有一些关于人类的隐含假设，现在这些假设已经不成立了，但我们会找到一个可行的办法。

Because maybe, you know, the way we've been working so far with PRs and stuff, was optimized for humans and had some implicit assumptions about humans that just don't stand anymore, but we will settle on something that works.

还是说你觉得我们有点麻烦，因为现在还不清楚该往哪里走？

Or you think we are kind of in trouble because it's not clear where we should go from here.

不，我觉得你的直觉完全正确。

No, think your intuition is exactly right.

我同意你说的第一部分，是的。

I agree with your first part, which is Yeah.

我们只是需要学习新的流程。

We just we just need to learn new processes.

而且我觉得，再说一次，我对人类的聪明才智和解决问题的能力有着无限的信心，这绝对是一个正在出现的问题。

And I think that, again, I'm I have the infinite belief in the human ingenuity and ability to solve problems, and this is definitely a rising problem.

我们需要着手解决这个问题。

We need to get on this.

我们需要搞清楚这个问题，但我们一定能做到。

We need to figure this out, but we will.

开源项目正在发生的事情也发生在公司内部，有些公司激励员工写尽可能多的代码，告诉他们必须使用代理工具，而且，你知道，CEO会说，我想衡量员工的效率，我们需要使用这些工具，等等等等。

The same thing that's happening with open source projects is happening inside of companies, where certain companies are incentivizing people to write the most amount of code, and they're telling them you have to use agents for things, and, you know, the the CEO is saying, like, I wanna measure productivity of my people, and we need to use these tools and blah blah blah blah blah.

他们的初衷可能是好的，但结果是你得到很多bug，范围蔓延，大量运行不佳的代码，巨大的维护问题，以及没人愿意碰的糟糕代码库。

And they may be well intended, but then what you get is you get a lot of bugs, you get scope creep, you get lots of code that doesn't work very well, you get huge maintenance problems, and you get, like, toxic code bases that nobody wants to

去处理。

work with,

所以我觉得，不同团队的管理水平确实有高有低。

and so I think that, again, different teams are better or worse managed.

不是每个人都能保持一致，但我确实认为我们整个行业需要解决这个问题，而且我相信我们能做到。

It's not consistent for everybody, but I do think that we as an industry need to figure this out, and I think we will.

问题就在于这些工具发展得太快了，而且随着我们建立新的流程，就像你说的，或者模型变得更好，或者其他东西在演变，我们肯定会找到一个新的稳定点。

It's just a matter of these tools are moving really rapidly, and kind of as we build perhaps new processes, like you say, or maybe the models get slightly better or other things evolve, we'll definitely find a new stable point.

对，我也这么认为。

Yeah, I believe that too.

你之前还提到了许可证的问题，确实有很多不同的案例。

And you mentioned licenses even before, and there have been instances, as you said, of many different cases.

比如某个库被AI重写，许可证从GPL变成了MIT，维护者声称是干净室实现，但实际上因为是AI做的。

Either some library gets rewritten with AI and with this different license from GPS to MIT and claiming there was a case where the maintainer claimed it was a clean room implementation, quote unquote, but actually because it was done by AI.

所以这完全是新领域。

So, it's all, I mean, new territory.

基本上没人知道该怎么处理这些事。

It's all with nobody knows what they're doing basically with this.

你觉得我们需要考虑一下许可证怎么运作吗？

Do you think that we need to think about how licenses work?

或者你对这件事的未来有什么看法？

Or do you have a vision about what's going to happen with this?

是的，我觉得绝对需要，版权法肯定得进化，百分之百。

Yeah, I think that absolutely, like copyright needs to evolve, 100%.

现在版权保护的是输出的形式，我觉得这在这里会过时。

So copyright currently protects the form of the output, and I think that's going to be obsolete here.

我觉得它已经过时了，所以法律程序要花时间来解决这个问题，我也不知道那会是什么时候。

I think it is already obsolete, and so it'll take some time for the legal processes to figure this out, and I have no idea when that will be.

可能花的时间会比我们期望的长得多，所以我觉得这类例子还会继续出现，我们可以预料到这一点。

It'll probably take way longer than it would be desirable for, and so I think that more of these examples will keep happening, and we can expect that.

对。

Yeah.

我觉得这真的很难预测。

I I think it's very hard to predict.

有些人说我们也许可以给界面申请版权，然后用它们作为锚点。

Some some are saying we maybe can copyright, like, the interfaces, and they use those as anchors.

我的意思是，我也不确定。

I mean, I don't know.

对。

Yeah.

但是，再仔细看看。

But but look at it again.

我就说说我的看法吧。

I'll I'll I'll just give you my my take on it.

再说一遍，我只是一个人。

And again, I'm one person.

我很奇怪。

I'm very strange.

我有自己的想法。

I have my own ideas.

对吧？

Right?

我觉得任何想靠受版权保护的标题之类的东西来创业的人，就是不够努力。

I think that anybody who's trying to build a business and on, like, copyrighted headers or something is just not trying hard enough.

这真的很疯狂。

It's really crazy.

对吧？

Right?

所以从我的角度来看，我觉得这是一个非常棒的时代。

And so I from my approach, I just look at this as just such an amazing time.

对吧？

Right?

我们在建设一个很棒的开源社区。

We're building an amazing open community.

我们开源所有这些，因为开源是更好的软件开发方式，而且，你知道，如果你还在经营一家试图保持专有、把那些当作秘密武器的公司，有很多公司，特别是硬件公司，会这样做。对。

We're open sourcing all this stuff because open source is, like, the better way to do software, and and, you know, if you're still running a business where you're trying to keep things proprietary and that's your secret sauce, which there's a lot of companies, particularly hardware companies, do that Yeah.

那你已经落后二十年了。

Well, you're you're already twenty years out of date.

这其实不是什么新鲜事，所以你得适应，得想办法解决，他们可能会遇到一些挑战，但也许这只是个推动力，逼他们整体提升自己的方法，这对世界也是好事。

Like, this isn't really a new thing, and so, yeah, you need to adapt and you need to figure this out, and they're gonna be kind of having some challenges, but but maybe it's just a forcing function to get them to up level their approach in general, and that's also good for the world.

所以，是的。

So Yeah.

我总体上是个乐观主义者，对吧，所以我总是从我们能拿它做什么的角度看问题，但这也是另一种思考方式，是的。

I'm I'm I'm generally the optimist, right, and so I I look at things from a what can we do with it perspective, but that's the other way to think about Yeah.

而且，因为我们基本上把那些悲观的情况都聊完了，但还有看涨的一面，就是AI能带来更多开源软件的爆发，让人们更容易上手开源项目，因为现在学习一个新项目的门槛降低了。

Also, because, I mean, we we have we have basically covered all the doom and gloom, but there is also, like, the bullish case in which AI allows for an explosion of more open source software, and it makes it easier for people to pick up open source projects because now the ramp up to get to learn a new project is easier.

我是说，如果我们去找，肯定能找到很多积极的东西，嗯，

Mean, there are a ton of positives that we can find if we look for Well,

我来告诉你我看到的积极面，但先提醒你一下。

I'll tell you the positive I see, but let me just caution you on that.

我同意你的看法。

I agree with you.

我们会看到更多的软件。

We're gonna see a lot more software.

是的，确实如此。

That is Yeah.

绝对没错。

Definitely true.

不过，我对这个问题的看法是，我们并不需要更多的软件。

The problem I have with that, though, is that we don't want more software.

我们需要的是更高质量的软件。

We want more high quality software.

有更多的左填充包或者其他类似的东西的克隆，并不会真正让世界变得更好。

Having more left pads or other clones of other things is not actually gonna make the world better.

那并不是我们真正想要的。

That is not actually what we want.

我们需要的是高质量的新想法，推动世界向前发展。

Want high quality new ideas that move the world forward.

这确实是有价值的。

That's actually value.

所以对我来说，构建Mojo、构建Macs、构建新社区和新工具，AI真是太棒了，因为我们看到的是，由于Mojo是开源的，而且我们有数十万行GPU内核代码和大量示例代码，你只需要说，嘿，把这个CUDA内核移到Mojo上，Clog就会自动完成。

And so, for me, so building Mojo and building Macs and building new communities and building new tools, AI is fantastic because what we're seeing is so Mojo, because it's open source and because we have, hundreds of thousands of lines of GPU kernels and tons of example code, you can just say, Hey, take this CUDA kernel, move to Mojo, and Clog will just do it.

这是可验证的，是AI工具的完美用例，这是一个很好的入门方式，因为这样你就能很快从专有生态系统转移到开放生态系统。

It's verifiable, it's a perfect use case for AI tools, That's an amazing way to get started because now you get off of a proprietary ecosystem onto an open one really fast.

对。

Yeah.

你不需要成为超级专家就能做到这一点。

You can do this without being the super expert.

另一个令人惊叹的地方是，因为我们构建Mojo的方式，以及我们有这些高级抽象层覆盖了很多硬件细节，真的很棒，因为你可以说，嘿，我这里有一个遗留的GPU内核。

One of the other amazing things, because the way we built Mojo and because we have these higher level abstractions that cover a lot of the hardware details, it's really amazing because you can say, Hey, I have this legacy GPU kernel over here.

把它移到Mojo上，然后采用最佳实践，通常它会运行得更快。

Move it to Mojo, and then adopt the best practices, and often it runs faster.

所以这真的很棒。

And so that's that's actually fire.

那真的很酷。

That's really cool.

是的。

Yes.

而且，能够比以往任何时候都更快地创建社区和推动新技术发展，这简直太棒了。

And the ability to create communities and catalyze new technologies faster than ever before is just, like, amazing.

这真是行业里一个充满力量的时刻。

It's just such a powerful time in the industry.

对。

Yeah.

绝对是的。

Absolutely.

现在我很高兴我们给出了自己平衡的看法，既谈到了这些事情的坏处，也谈到了好处。

And now I'm happy that we've given our own balanced take that with the with the bads and the goods about all this.

我还想特别问问你关于AI和软件的事情，因为我记得大概在十一月你去播客的时候说过，你用AI来写代码，速度大概提高了10%到20%，差不多是这样。

I also wanted to ask you about AI and software specifically, because I saw that in I think in November you went to podcast and said, you used AI for coding and you were probably getting 10 to 20% faster, something like that.

现在过了三四个月，情况怎么样了？

How is it going today, three to four months later?

对，这个问题问得好。

Yeah, well, so it's a great question.

从十一月以来，工具确实进步了很多。

So, the tool's gotten way better since November.

可以说是一个相当大的飞跃，但并没有直接让我的效率变得更高。

It's kind of a a pretty significant step change, but it hasn't directly made my productivity any higher.

所以，它可能可靠了10%到15%，用起来也更舒服了。我觉得不能低估程序员心情好这件事的价值，效率不是唯一的衡量标准，但总体来看，差别并没有那么大。

And so it's probably It's 10 to 15 way more reliable, and so it's way more pleasurable, and I think that don't underestimate programmer happiness as actually a good thing, and so productivity isn't the only measurement, but I don't think the aggregate has been that big of a difference.

我觉得很多人忽略的一点是，软件的生产和创造，其中只有一小部分是写代码。

Here's the thing that I think that a lot of people gloss over, is that software production and creation is only a tiny part of that is about writing the code.

大部分时间是在决定要做什么，跟其他人协作，处理各种其他问题。所以AI确实在大规模重构这类事情上减少了摩擦和那些小麻烦。

Most of it is deciding what to build, working with other humans, working with a whole bunch of other issues, and so AI definitely takes the friction in the microaggressions out of large scale refactoring, right, and things like this.

对于这些可以自动化、可以验证的测试来说，它非常棒，但你仍然需要做决策，仍然需要去处理事情。所以我发现，我把大部分时间都花在最棘手的问题上，这其实挺让人沮丧的，因为那些容易的、让人感觉良好的部分已经被自动化了，剩下的都是更难啃的骨头，所以从那个角度看，体验是完全不同的。

It's fantastic for these automatable and verifiable tests, but you still have to make decisions, you still have to engage with things, And so what I found is I spend most of my time on the thorniest problems, and so this is actually the frustrating part is that kind of the easy, it feels good part has been automated away, and you get left with some of the harder pieces, and so different different lived experience from that perspective.

对。

Yeah.

我觉得你之前说了一个很有意思的点，你说工具变好了，AI让你作为程序员更开心，即使有些事情，比如说，不会直接影响你的生产力底线。

I I think you said something very interesting before you said that tooling got better, AI makes you happier as a programmer, even on things that don't move, let's say, the bottom line of your productivity.

对吧？

Right?

有哪些事情让你作为程序员更开心，即使它们不算真正的生产力？

What are these things that make you happier as a programmer, even if they don't count to the real productivity?

哦，是的。

Oh, yeah.

对我来说，就是更新测试用例。

So so for me, updating test cases.

你做了一个改动，然后这是一个有意的行为变化，所以你得去更新所有相关的东西。

You make a change, and then it's an intentional behavior change, and so you have to go update all the stuff.

就像，嘿，直接帮我搞定吧。

It's like, hey, just go do it for me.

不用做这些事让我特别开心，因为我可以开始写PR摘要或者做其他事情，而这些事就自动帮我完成了。

It makes me so happy to not have to do that because I can start writing the PR summary or whatever and do this stuff while this is just being done for me.

不用操心那些机械性的部分。

Don't have to worry about the mechanical piece.

比如把X重命名为Y，对吧？

Doing the rename X to Y, right?

但要根据上下文灵活处理，还得调整参数位置，或者就是一些很机械的事情，现在都不用做了。

But do it contextually sensitively, and you have to move an argument around or just very mechanical stuff going away.

这真的太棒了，而且类似的事情还有很多。

It's just wonderful, and so there's a lot of things like this.

另外，现在的工具在上下文学习方面也特别厉害。

Also, tools are so great with in context learning.

它们甚至能处理像MLIR语法这样冷门的东西，这让我觉得非常神奇。

They can even handle obscure things like MLIR syntax and stuff like this, and so it's just amazing to me.

有时候会有那种神奇的时刻，即使只是用Tab补全，也依然很有用、很强大，所以这方面有很多不同的体验。

Have the magic moments where even tab, tab, tab is still very valuable and still quite powerful, and so there's a lot of different aspects of that.

但话说回来，还是得靠人，你知道，我还没见过那种情况，就是它真的能根据一个大概的方向去执行。

But again, still have to, you know, I haven't seen it where it's like, okay, well, here's a generalized idea of which direction I want you to go, and it can actually do that.

我觉得那不太现实。

I don't see that working.

对，但我觉得你提到的这些点很有价值，而且这也符合我看到很多成功使用AI的团队的模式。他们都提到，与其说是靠AI实现什么大突破，不如说是更好地落实基础工作，比如测试文档、代码健康和代码质量这些基本规范。现在这些比以前更容易执行了，因为AI能处理很多这类事情。

Yeah, but I think you mentioned very valuable things, and it stays within a pattern that I've seen also with many teams that are using AI successfully, and they all mentioned, rather than, I don't know, some big moonshot that they're able to do with AI, it's more about enforcing better the basics and the basic hygiene, like testing docs and basic code health and code quality, all things that now you can enforce in an easier way than before because AI can actually take care of a lot of that.

对，那我得先说明一下。

Yeah, so I'll give you the caveat here.

对吧？

Right?

所以，再说一遍，我是一个相当有经验的程序员。

So, again, I'm a pretty pretty experienced programmer.

对吧？

Right?

所以，能让我效率提升10%其实已经很了不起了。

And so lifting me 10% is actually a big deal.

对吧？

Right?

是的。

Yeah.

就是这类事情。

Stuff like this.

所以我看到的是，那些还在学习阶段、刚起步的人，提升的幅度远不止10%。不过，我确实是个例外。我给你举个例子，说说我想看到的东西。

And so what I've seen is that people that are earlier in their journey and they're still learning things get way more than 10%, I'm But definitely an outlier in that I'll tell you an example of something that I want to see.

这是我希望Modular也能做到的事情。

This is something I would love even Modular to do.

我们还没时间做这个，就是说，嘿，AI，我要在每个目录里放一个README。

We haven't had time to build this yet, is say, Hey, AI, I'm going to have a README.

Md文件，描述我们正在构建的技术，我还想在仓库里放一份架构文档，说明每个模块是怎么工作的、它做什么、职责是什么，等等等等。一份真正出色的设计文档。然后说，好吧，首先，你需要和AI进行一些协同设计，确保架构文档是正确的，结构也合理，而且你需要审查正在发生的事情，但AI几乎可以一次性生成80%的内容，对吧？

Md in every directory of our technology that we're building, and I want an architecture doc in the repo that describes how each module works and what it does and what the responsibilities are, etcetera, etcetera, etcetera, good, really amazing design doc, and say, well, of all, you need a little bit of co design with the AI to make sure that the architecture doc is right, and then it's structured the right way, and you need review of what's going on, but AI can generate 80% of that, almost one shot, right?

所以，你可以在此基础上迭代，把它完善，然后先做前期工作，把这份架构文档建立起来。

So, you can iterate on that, you can get that in, and then you do upfront work to build out this architecture doc.

但我想设置一个每周定时任务，去扫描所有这些文档，找出可能过时的内容。

But then I want a weekly cron job that says, Go scan all these docs and identify likely out of date things.

我觉得你得两件事都做，不能只做一件，但一旦你做了，你就能拥有非常棒的设计文档，让新人更容易上手项目，也能让AI本身理解期望的设计，而不仅仅是现有的东西，对吧？

I think that then what you could do with you have to do both, you can't just do one, you have to do both, but once you do that, you could have really amazing design docs that make it way easier for people to onboard into the project, make it so that the AIs themselves can understand the design that's desired, not just what exists, right?

我觉得在创建这些架构文档的过程中，你会遇到很多像‘好吧，现在是这样运作的，但本不该如此’的情况，这实际上能推动架构向前发展。

I think that in the process of creating these architecture docs, you get a lot of these like, Okay, well, that is how it works, but it shouldn't work that way, and it could actually drive some of the architecture forward.

我觉得这样的方法会非常强大，不仅对我们内部这样的项目，对开源项目也是如此，因为，再说一次，你希望人们进入项目后能快速理解、学习和提升，而我认为这是一个绝佳的机会，目前还没人尝试过。

I think that an approach like that would be very powerful, both for projects like ours internally, but also for open source projects as well, because, again, what you want is you want people to get into the project, be able to understand things and learn and upscale very quickly, and I think this is one amazing opportunity that I haven't seen people tackle yet.

是的，这是个绝佳的用例。

Yeah, it's a fantastic use case.

我同意。

I agree.

而且这也节省了你宝贵的时间和精力，让你能专注于真正值得的事情，而不是去更新文档或做那些测试。

And it also saves your precious time and brain for the things that actually deserve it as opposed to updating the docs or these other tests.

嗯，我们确实有内部文档，但它们会过时。

Well, and this this is something where we do actually have internal docs, but they get out of date.

那更糟糕的是什么呢？

And so what what's worse?

是没有文档，还是有文档但已经过时了？

Not having docs or having docs that are out of date?

对。

Yeah.

要我说，有过时的文档几乎更糟糕。

It's almost worse to to have them out of date if you ask me.

几乎更糟糕。

Almost worse.

不知道。

Don't know.

没错。

That's right.

对。

Yeah.

你之前还说过一个很有意思的点，你说你是个经验非常丰富的程序员。

And you also said something interesting before when you said you're a very experienced programmer.

所以对你来说，哪怕只是提升15%，也是很有意义的。

So for you, even getting 15% better, it's something.

但如果是年轻人，他们从AI那里得到的提升可能远不止这些，对吧？

And while if you look at younger folks, they might get way more than that out of AI, right?

完全正确。

Absolutely.

最新的模型和AI工具，是不是改变了你招聘工程师时看重的素质？

Has the latest models and tooling with AI is shifting what kind of qualities you're looking for in engineers that you're hiring?

或者说，初级工程师的工作方式是不是也变了？

Or even how junior engineers are working?

你在这方面是不是有意识地做一些调整？

And are you being intentional about this in a way?

百分之百。

A 100%.

再说一次，我有些关于这个世界的奇怪想法，大多数人都在说，是啊，我们不招初级程序员了，或者我们要裁掉所有人。

Again, I'll give you I have these weird ideas about the world where most people are running around saying, Yeah, we're not hiring junior programmers, or We're laying off all of our people.

我们正在积极招聘。

We are actively hiring.

所以，我们要解决的问题比我们能找到的优秀人才多得多，而且我们确实有很多优秀的人才。

So, have way more interesting problems to solve than we have amazing people to do it, and we do have a lot of amazing people.

但我们也在招聘新毕业的大学生和其他初级人员。

But we're also hiring new college grads and other people that are junior.

实习生也很棒，因为这些人带来了完全不同的专长。

Interns, it's amazing, because a lot of these folks bring a completely different expertise.

比如，他们天生就会用AI工具。

Like, they're AI tool native.

一些更有经验的人，是的，你知道，他们也在用这些工具，但用得不是最好的方式。

Some of the more experienced people, yeah, you know, they're using the tools, but they're not using them the best way.

工具变化很快，所以这种适应新技术和事物的意愿非常强大。

The tools change very rapidly, and so, like, this willingness to adapt new technologies and things is very powerful.

但同样，我认为对所有团队都适用的一点是，我喜欢建设东西，包括团队，就是团队里需要有各个层级的人。

But also, again, what I think is true for all teams, and again, I like to build things, including teams, is that you want people at all levels within a team.

如果全是经验丰富的工程师，没有新人，或者全是新人，没有经验丰富的人，那两边都会出问题。

If you have all super experienced engineers and no juniors, or you have all juniors and those experienced people, you get into problems on either side of this.

好的团队有不同层级的人，他们互相学习，合作顺畅，效率高，能处理各种不同类型的问题。

Good teams have people at multiple different levels, and they're learning from each other, they're working well, they can be effective, they can be taking on different kinds of problems and things like this.

所以，我认为智能体和新的编程工具真正改变的是，现在新毕业的大学生，或者说那些以从不做管理为傲的人，现在每个人都是管理者了。

And so, what I think that agents and new coding tools have really shifted is it means that new college grads or the power I see that is very proud of never being a manager, well, everybody is now a manager.

是的。

You Yes.

你必须用管理者的思维去思考问题。

Have to think about things with manager thinking.

即使你以从不做管理为傲，你也必须掌握并学习这种思维方式。

Even if you're super proud of never being a manager or something, well, you have to bring and learn the thinking.

即使你刚毕业，而且我觉得有些人学得比别人快得多，你也必须带着这种思维，因为重要的不只是结果，而是我到底想达成什么目标？

Even if you're fresh out of school, and again, I think some of these folks learn way faster than others, you have to bring that thinking because it's not just about the outcome, but it's about what am I trying to achieve?

最好的做法是什么？

What's the best way to do it?

长期维护起来会是什么样？

What's going to be like to maintain this over time?

这些更深层次的问题，最终比你能多快把代码写出来重要得多。

These second order questions end up mattering way more than how quickly can I pound out the code?

对吧？

Right?

对。

Yeah.

对。

Yeah.

完全同意。

Absolutely.

而且我觉得，大家自然会担心初级工程师会受影响，因为他们从一开始就要接触很多以前不需要接触的东西，比如高层次的思考、代码审查这些。

And I think I mean, it feels natural to think that junior engineers might be in trouble because they are exposed to a lot of these things from the get go that were not exposed to before, like high level thinking code reviews.

我觉得这可能是我的一个怪想法，就是我们现在的判断是基于一种过时的直觉，关于工程师需要会什么、不需要会什么。

I mean, I have this feeling is part of my own weird ideas that we are making this judgment based on kind of our outdated intuition about what engineers need to be able to do versus what they are not needed to do.

但实际上，当工具进化了，人们会根据手头有的工具来学习。

While instead, when the tools evolve, people learn based on the tooling they have at disposal.

就像水倒进容器里，会适应容器的形状一样。

So it's like, you know, a liquid that fills the container, the shape of the container they're in.

所以我觉得初级工程师会像以前一样快速成长，只是方式可能出乎意料，难以预测。

So I think that junior engineers will grow as fast as they've always grown in ways we probably don't expect or can't predict.

他们可能就像你说的，是AI原住民，他们可能会比很多经验丰富的老工程师更高效，因为那些老工程师可能很难适应他们多年来的工作方式。

They were probably, as you said, they're an AI native, They're probably going to be more effective than many other more seasoned engineers who may have troubled adapting after many, many years of doing things in a way.

嗯，我是这么看的，AI会放大一切。

Well, the way I look at it is that AI amplifies things.

对吧？

Right?

所以它会放大你写代码的能力，放大你学习的能力，也会放大好的或坏的架构。

And so it amplifies your ability to write code, amplifies your ability to learn, it amplifies good or bad architecture.

比如你用AI快速扩展，如果本来就很乱，那就会更乱。

Like, you scale it rapidly with AI, you can get a mess if it's already a mess.

但在团队里，我觉得会发生的是，那些拒绝使用新工具或拒绝改变的人，就像你说的，会被慢慢落下。

But within Teams, think that what's going to happen is that the people, as you say, that refuse to use new tools or refuse to evolve, those just kind of get left behind.

对。

Yeah.

对吧？

Right?

而那些积极拥抱这些的人，那些充满动力、渴望学习、有好奇心、想成长的人，他们会成长得更快。

And the people that lean into this, the people that are so motivated and hungry and curious and want to learn and grow, they'll grow way faster.

再说，每个人都可以选择自己想做的事。

Again, everybody can choose to do what they want to do.

我见过很多人说AI很荒谬，这些东西都没用，全是胡扯，但事实并非如此。

I think that I've seen lots of people say AI is ridiculous, and none of this stuff is working, and it's all BS, and that's not true.

我也见过有人说，天哪，程序员要失业了。

I've also seen people say, like, oh my god, like, coders are out of a job.

就像，所有AI都会自动生成，或者所有代码都会自动生成。

Like, all AI will just be generated, or all code will just be generated.

但我觉得那也不对。

It's like, well, I don't believe that either.

对吧？

Right?

所以，是的。

So but Yeah.

但你确实得投入进去，得自己摸索出来。

But you do have to lean in and have to figure it out.

对。

Yeah.

而且我觉得你之前有个很好的比喻，你说基本上所有工程师现在都是管理者，而AI奖励的是管理者的行为。

And I think you you got a great analogy before you said, basically all engineers are managers now, and AI rewards manager behavior.

但我的意思是，我的一个比较有争议的观点是，工程师们，大多数，他们其实不想成为管理者，对吧？

But I mean, my provocative take is also that engineers notoriously, most of them, they don't want to become managers, right?

我的意思是，就像格罗斯说的那样。

Mean, like to Gross

这种心态是必需的。

mindset is required.

对。

Yeah.

那你觉得你的团队成员，他们在心理上以及所需技能上，适应这种转变容易吗？

So are you finding easy for your people, people on your team, this kind of transition psychologically in terms of skills they need to apply?

情况怎么样？

How is it?

嗯，这个我不好说，因为我们团队很大，不同的人适应速度不一样，有些人比其他人更吃力，我觉得没有一个很好的指标来衡量。

Yeah, well, so I can't give you an answer to that because we have a large team, and so different people are adapting at different speeds, and so some people are struggling more than others, and I don't think there's a good indicator.

我觉得Modular在这方面并不特别。

Don't think the Modular is unique in that way.

我觉得我们可能代表了很多高科技团队的典型情况，所以我不觉得我们有什么独特或者异常的地方，也不觉得我们……

Think that we probably have a representative slice of many very high-tech teams, so I don't think that we're unique or outlier, nor do

我觉得

I think

我觉得真正重要的是，要鼓励那些积极投入的人，如果他们觉得疯狂，而且他们的代币预算很贵，就让他们去探索，去搞清楚，好吧，到底什么在实际中行得通？

What we have a magic I do think is important is I do think that it's important to encourage some of the people that are leaning in, if they feel crazy and their token budgets are expensive, and enable them to path find and figure out, okay, well, what actually works in practice?

我经常挑战大家的是，你看，用 vibe coding 搞出一个惊艳的演示，或者做出一个特别酷、特别让人兴奋的东西，其实并不算成功。

What I always challenge people to do is say, look, vibe coding out some amazing demo and having some crazy thing that's really exciting and very cool is actually not success.

对。

Yeah.

真正的成功是代码进入产品并发布上线。

What is success is when code gets in the product and ships.

对。

Yeah.

所以，有时候这中间会有差距，我也看到过一些危险的情况，比如，有人特别兴奋，甚至可能不是专业软件工程师的人会说，哦，哇。

And so, there's sometimes a gap there, and I've seen some danger cases where, you know, somebody got very excited and some person who maybe isn't even a professional software engineer is like, oh, wow.

看看我能做什么。

Look what I can.

这大概完成了酷炫东西的80%。

It's like 80% of a cool thing.

就像是，好吧。

It's like, okay.

那确实很酷，但对我们开发生产级软件来说，这并不算真正的成功。

That is really cool, but that's not actually a success for us building production software.

它需要以正确的方式开发，进行良好的增量开发，并附带测试用例。

It needs to be developed the right way, good incremental development, land with test cases.

你必须真正完成整个过程，落地、集成，所有这些工作也都极其重要。

You have to actually do the whole thing, and landing and integrating and all that all that kind of work is also super, super important.

没有这些，你就无法发布。

And without it, you don't ship.

或者即使发布了，你也会得到一个无法维护的产品，然后，对。

Or if you ship, you have a product that you can't support, and that Yeah.

这些都是潜在的风险。

Those are some dangers.

对。

Yeah.

你觉得，之前你提到我们可能需要为开源项目找到更好的模型，比如针对PR和这类软件的开发流程，你觉得我们是不是也需要找到类似的东西，从而改变我们对软件开发生命周期以及各个步骤的思考方式？

Do you think, before you mentioned that we probably need to figure out better models for open source projects, for example, for PRs and for development process of that kind of software, do you think we need to figure out something similar in a way that changes how we've been thinking about the software development life cycle and all the various steps?

还是说，只是AI在加速每一个步骤，但整个流程本身还是保持不变？

Or it's just that AI is accelerating every single of these steps, but the pipeline stays the same anyway?

我觉得现有的这些系统还是很有用的。

I think that it's the same the same systems are useful.

这方面可能会有大的突破。

There could well be big breakthroughs in that.

但具体是什么，我也不太确定。

I'm not exactly sure what they are.

我目前看不到什么明显的方向。

I I can't see anything obvious.

但我看到的是，AI就像一个放大器。

But what I see is that AI is an amplifier.

它能让你跑得更快，而且每当你把一项任务压缩了，就会给其他所有环节带来压力。

It allows you to move faster, and any time you take a task and you compress it, it puts pressure on all the others.

所以，如果你的CI特别慢，那猜猜看，这就会变成一个大问题。

So, you have really slow CI, well, guess what, that's going be a big problem.

你需要快速的CI。

You need fast CI.

如果你没有测试用例，那也会是个大问题。

If you don't have test cases, that's gonna be a big problem.

快速的CI、测试用例，这些其实本来就是最佳实践吧？

Fast CI, test cases, these are all actually best practice anyways?

再说一次，AI的作用就是逼着大家去讨论，也许团队积累的巨额技术债务以前从来不是问题，但现在这些技术债务真的会拖后腿。

Again, what AI is doing is forcing a conversation, and maybe it's gigantic amounts of tech debt the teams have accumulated that have never been a problem, but now those tech debt that tech debt ends up really holding them back.

也许现在是时候投资了，也许这就是AI逼着大家做的事，而且我觉得这对各种项目的健康来说，可能确实是件好事。

Well, maybe it's time to invest, and maybe that's that's what it forces, and I think that's actually probably pretty good for the health of various projects.

所以，是的。

So Yeah.

所以，基本上，我们说的是，因为AI，今天的最佳实践比以往任何时候都有更高的投资回报率。

So, basically, we're saying that best practices today have even a higher return on investment than they ever had because of AI.

对。

Yep.

嗯，AI是个放大器，所以如果你有一团乱麻，你会更快地得到更大的乱麻。

Well, AI is an amplifier, and so if you if you have a mess, you'll get bigger mess fast.

我觉得这不是任何人想做的，但我想很多团队实际上正在这么做。

I I don't think that's what anyone wants to do, but I think it's many teams are doing, actually.

嗯，而且我也认为，很多管理团队，或者你知道，CEO之类的，真的在鼓励这种做法，因为他们不了解真正发生了什么。

Well, and and also, I think that many management teams or, you know, CEOs or things like this, really encouraging that because they don't understand what's really happening.

所以，这实际上非常具有挑战性，因为我和很多非常聪明的人谈过，他们中的许多人亲眼看到了这一点，因为他们有工程思维，但他们却受到压力，比如，你需要更快，你需要做这个，你需要做那个，而施加这种压力的人，他们当然是出于好意，对吧？

And so, this is something where it's actually very challenging because I talked to, you know, lots of really smart people, and many of them are seeing this firsthand because they're the engineering mindset, and yet they're getting pressured, like, you need to go faster, you need to do this, you need to do whatever, and the people that are putting that pressure, they're well meaning, of course, right?

他们希望人们有生产力，希望产品快速推进，但他们根本不理解是什么在拖后腿。

Want people to be productive, and they want their products to move fast, but they don't fundamentally understand the the thing that's holding them back.

如果你是的。

And if you Yes.

如果不做这些投入，只是一味地说要加快速度，然后我按你写的代码行数来考核你。

Don't make those investments, and you're just saying go faster, and I'm gonna measure you based on the lines of code you create.

对吧？

Right?

那结果肯定好不了。

You're gonna get you're gonna get a bad outcome.

所以

So

对。

Yeah.

我觉得这事儿挺复杂的，因为就像你说的，确实有一些很糟糕的CEO案例，但也有一些人，就像你刚才说的，他们是出于好意，因为他们之前跟工程师交流过，得到了帮助。

I think it's it's complicated because as you say, of course, there are there are very bad CEO stories and so on, but there are also people that were, as you said, well meaning because they are meeting with assistance from engineers, as we said before.

所以我觉得要找到一个合适的平衡点挺难的，既要主动去推动，从上到下地支持，对吧？

So I think it's tricky to find to strike the right balance where you want to be intentional and try to drive something top down and support, right?

而不是放任不管

Not just leave

它

it

底层，但又不显得强制和束缚。

bottom without being like imposing and constrictive.

对。

Yeah.

嗯，平衡来说，我觉得鼓励人们是好的。

Well, balance, on I think that it's good to encourage people.

比如，如果你推动这个问题，鼓励人们采用新工具，如果你以合理的期望去做，我觉得结果会是对的，因为你不希望被落下。

Like, if you if you push the issue, if you encourage people to adopt new tools, if you, like, if you do it with a balanced set of expectations, I think you get the right outcome, because you don't want be left behind.

你不想不修复你的CI或者什么的，但你必须要有合理的期望，我觉得这就是整个世界在调整的地方，有很多实验在进行。不同的人有不同的看法。

You don't want to not fix your CI or something, but you have to have reasonable expectations, and I think this is where the whole world's calibrating, and there's a lot of experiments being run, Different people are taking different takes.

也许我的看法不够激进，我不知道，一两年后我们再看吧。

Maybe my take isn't aggressive enough, I don't know, and we'll see what happens in a year or two.

重要的是，这些公司是否真的能推出更多好产品？

What matters is, again, do these companies ship more good products?

比如说，有没有让他们的客户更满意？

Like, does it make their customers happier?

它真的管用吗？

Does it actually work?

他们有没有服务中断的情况？

Do they have service outages?

就是说，这些是可以衡量的结果，所以现在说还为时过早，很多方面都还看不出来。

Like, there's, like, these things that that are measurable outcomes, and so it's a little bit too early to tell in many ways.

对。

Yeah.

在Modular那边情况怎么样？

How is it at Modular?

我很好奇，你们团队有没有共享的文档，比如CloDMD文件，或者有没有一些会议让大家交流实践、分享知识，实际落地情况是怎样的？

I'm curious, do you have like shared artifacts like CloDMD files for the team or you have ceremonies to come where people talk about practices to share knowledge, how it is on the ground?

是的，Modular跟大多数公司真的很不一样，原因有很多。

Yeah, so Modular is really different than most companies for a bunch of different reasons.

首先，我相信我们在软件工程方面确实遵循了最佳实践。

So first of all, we do follow best practices, I believe, in software engineering.

我们有单一代码库，还有快速的持续集成。

We have a mono repo, we have Fast CI.

这看起来是理所当然的，但对于一家做AI基础设施的公司来说，据我所知，这几乎是新颖的。

That seems like an obvious thing, but for a company working on an AI infrastructure, that's almost novel as far as I'm aware.

比如，TensorFlow的持续集成以前要跑好几天，因为要测试各种奇特的GPU相关的东西，而且都是端到端测试，简直是一团糟。

TensorFlow CI used to take days to run, for example, because you're testing all these exotic GPU things, etcetera, and they're all end to end tests, and it was just a gigantic mess.

所以从那个角度看，Modular非常不同。

And so Modular is very different from that perspective.

另一个主要区别是，我们有开源项目，而且我们还会开源更多的代码。

The other major difference is that we have open source, and we're gonna open source a heck of a lot more of our code.

所以Modular

And so modular

所以标准更高。

So higher standards.

几个月后，从软件的角度来看，我们会非常像一个开源项目，这跟大多数公司很不一样，我觉得这是现代公司运营的方式，但这也是我认为非常不同的一点。

Months ago will look very much like an open source project from our software perspective, which is extremely different than most companies, and I think it's the modern way to run a company, but it's something that I think is very different.

所以，正因为如此，首先，是的，我们有共享的云技能文件之类的，而且我们已经把它们发布到社区里了。

So, as a consequence of that, first of all, yes, we have shared cloud skill files and things like this, and we're publishing them already in community.

我们内部也在用这些，所以，这又是工具链的一部分。

We're using them internally, and so, again, this is part of the tooling.

这就像十到二十年前的Git，对吧？

This is like Git from ten or twenty years ago, right?

你得学会怎么用这些工具，还得跟着它们一起进化，所以，是的，你得在这方面投入，但我们有一些优势，因为首先，从架构上讲，我们构建软件开发生态系统和软件开发流程实践等，都是为了规模化而建的，并且汇集了所有开源项目的最佳知识，以及如何保持高速度的软件工程，但还有一点，随着我们不断开放代码，这真的推动我们投资建设可扩展的社区，而这正是你想要的，你希望随着贡献者和使用你技术的人数增长而扩展，这是我认为大多数软件团队从未考虑过的事情。

You need to figure out how to use the tools, and you need to work with them as they evolve, and so, yeah, you need to invest in this kind of stuff, but we have certain advantages because, first of all, the architecture side of building our software development ecosystem and our software development lifecycle practices and things like this were built for scale and built the best knowledge of all the open source projects and how to keep high velocity software engineering, but then also as we continue to open code, it really pushes us to invest in building scalable communities, and that's actually what you want, is you want to be able to scale with a number of contributors and a number of people working with your technology, and that's something I think that most software teams have never even considered.

大多数人只是想把最后一个bug修完。

Most people are just trying to get the last bug fix out.

对吧？

Right?

这真的是一种非常不同的看待事物的方式。

And it's just a very different way of looking at things.

对。

Yeah.

我觉得这是成功运营大型开源项目的好处之一。

I think it's one of the benefits of running successful big open source projects.

它会提高你的标准，让你更有责任感。

It raises your standards and keeps you more accountable.

对吧？

Right?

没错。

That's right.

对。

Yeah.

作为Modular的领导者，我面临的一个比较大的问题，和很多公司很不一样。

Here's one of the bigger problems I have as a leader at Modular, which is very different than, I think, many companies.

平均来说，Modular的软件工程师都很有原则，对技术债的抵制非常强烈。

On average, most Modular software engineers are so principled, and they push back so hard on tech debt.

他们会说，不不不。

They're like, No, no, no.

我们必须用正确的方式来做，这是我们文化的核心部分。

We have to do it the right way, which is a core part of our culture.

对吧？

Right?

对。

Yeah.

我们正在打造的东西会持续十年、十五年、二十年，所以你必须用正确的方式来做，但你也需要平衡，需要考虑到这一点。

And we're building things that will last ten, fifteen, twenty years, so you have to build it the right way, but you also have to be balanced, and you have to think about this.

在我看过的很多公司里，大多数人甚至不会进行这样的对话。

So, in many companies I've looked at, most people won't even have a conversation.

工程师只会随便应付，把bug从队列里弄出去，随便打个补丁，没人管。所以我们有这么多人想用正确的方式做事，投入建设，为自己的工作感到自豪，有时候就会觉得，好吧，其实技术债务也可以是好事。

The engineer will just do whatever to get the bug out of their queue and just hack something, and nobody So, we have so many people that want to build things the right way and invest in building and being proud of what they're doing that sometimes it's like, Okay, well, actually tech debt can be a good thing.

对。

Yeah.

对。

Yeah.

这太有意思了。

It's so funny.

技术债务只有在不偿还的时候才是坏事，但它可以是推动进展的正确方式，这是一种我从未见过的非常有趣的动态。

Tech debt is only bad if it doesn't get paid down, but it can be the right way to unblock progress, and it's it's a very funny dynamic I haven't seen before.

你自己是否也感受到这种矛盾？

Do do do you find this tension yourself?

我的意思是，作为一位首席工程师，你创造了很多出色的软件。

I mean, as a as a principal engineer who has who has created a lot of fantastic software.

现在你也是创始人、CEO，所以你需要考虑上市时间和投资者，还有资金，这些是否也在你的考虑之中？

Now you're also a founder, SEO, so you need to take care of time to market and investors and So, funding is that in your head as well?

嗯，我希望我们高效，对吧？

Well, I want us to be productive, right?

但同样，我们在Modular的整个策略就是长期取胜。

But also, our entire approach with Modular has been to win for the long term.

所以在内部，我们常说，未来赢得大胜利比只赢得明天更重要。

And so internally, we talk about winning big in the future is more important than just winning tomorrow.

对吧？

Right?

所以，是的。

And so Yes.

长期思维对于构建那种架构、开发技术以及进行我们正在做的投资来说，非常重要。

The long term thinking is very important for building the kinds of architectures and the technology and making the investment that we're doing.

所以作为创始人和CEO，对我来说，这意味着我要寻找那些认同这种方法、认同这个愿景、并且理解其中利害关系的投资者。

And so for me as a founder and as a CEO, that means that I look for investors who are aligned with that approach, aligned with that vision, that understand the stakes.

我们正在构建一个异构计算平台。

We're building a platform for heterogeneous compute.

我们实际上在构建一个——这需要一点时间，但它会像计算领域的超级管理器一样。

We're building effectively It'll take a little time, but it'll feel like a hypervisor for compute.

这将给人们带来选择。

This will give people choice.

这样人们就能在各种不同的芯片上进行扩展。

This allows people to scale across lots of different chips.

这让硬件制造商能够创新，并让他们的芯片被软件企业采用和使用。

This allows hardware makers to be able to innovate and get their chips adopted and used by software enterprises.

风险非常高。

The stakes are extremely high.

我们是唯一一个哪怕稍微尝试解决这个问题的团队。

We're the only ones even remotely trying to solve this problem.

我们不像其他大多数人那样，只是在PyTorch之上加一层。

We're not just a layer on top of PyTorch like roughly everybody else is.

我们正在进行根本性的投资，而且顺便说一句，这确实有效，这也是为什么这是一个非常大的赌注，也是一项非常大的投资。

We're making fundamental investments, and by the way, it works, which is one of the things that makes it a very it's a very big bet, and it's a very big investment.

我们的团队现在差不多有200人，但我们的方向确实与计算的发展趋势和世界的需求保持一致，而且对于那些只是购买、安装GPU然后转售的人来说，我们是一个很好的补充。这也是Modular如此有趣的原因之一，因为我们能够进行深层次的高科技投资，能够发布大量的开源代码，能够投资社区并开发新的编程语言，所有这些有趣又炫酷的东西。

Our team's almost 200 people at this point, but it's it's really aligned with what compute is doing, what the world needs, and it's very much a compliment to people that are just buying and installing GPUs and reselling them, and so this is one of the things that makes Modular so fun, is that we're able to make the deep tech, high-tech investments, we're able to make a ton of open source code, we're able to invest in communities and build new programming languages, all the fun shiny objects.

我们有一个很棒的云平台，所以如果你对云感兴趣，Modular是一个很棒的地方，因为我们不仅是在开源项目上构建Kubernetes和SaaS封装，我们还在构建整个技术栈，并把所有东西垂直整合在一起。

We have an amazing cloud platform, and so if you're into cloud, Modular is an amazing place because we're not only building, you know, the Kubernetes and SaaS wrapper on the open source thing, we're building that entire stack and vertically integrating the whole thing together.

所以能在这样的环境里工作，真的非常少见，尤其是对初创公司来说。

And so being able to work in that kind of environment is really pretty unusual, and particularly for startups.

所以对我来说，这是我解决和攻克大规模问题的一贯方法。

And so, for me, it's my generalized approach to solving and cracking large scale problems.

这也是为什么这些年来我能做成一些事情，但我觉得这很不寻常，很多人以前都没见过。

This is why I've been able to do certain things over the years, but I think it's very unusual, and a lot of people haven't seen that before.

对。

Yeah.

但这是一个非常棒的愿景和使命，我觉得这也是我们这次对话的一个很好的收尾。

But that's a fantastic vision and and and mission, and I think it was a fantastic closing note for this chat.

非常感谢克里斯来参加节目，也感谢这次精彩的对话。

Thank you so much, Chris, for for coming on the show and and for this amazing chat.

是的。

Yeah.

好的，谢谢你邀请我，卢卡。

Well, thank you for having me, Luca.

如果外面有人对Modular感兴趣，我们有一个很酷的网页，当然，我们还有很多空缺职位。

And if anybody out there is interested in Modular, we have a really cool web page, of course, and we have a lot of open positions.

所以请

And so please

查看我们的职业链接，所有信息都在节目笔记里。

check We out our careers link everything in the show notes.

再次感谢。

So thank you again.

太棒了。

Awesome.

非常感谢大家的收听。

Thank you so much for listening.

如果你觉得这次对话有价值，可以在YouTube、Apple Podcasts、Spotify或者你喜欢的任何播客应用上订阅我们的节目。

If you found this chat valuable, you can subscribe to the show on YouTube, Apple Podcasts, Spotify, or your favorite podcast app.

另外，请考虑给我们评分或留下评论，这真的能帮助其他听众找到这个节目。

Also, please consider giving us a rating or leaving a review as that really helps other listeners find the show.

你可以在 refactoring.fm 上找到所有往期节目，了解更多关于这个节目的信息。

You can find all past episodes and learn more about the show at refactoring.fm.

我们下期再见。

See you in the next episode.