Practical AI
AI Proficiency: From Users to Builders
In this episode of Practical AI, hosts speak with Mike Lewis about AI proficiency in large organizations, focusing on the shift from AI users to builders of durable solutions. Lewis outlines levels such as L0, L1, L2, and L3, and argues that companies should match training, tools, and expectations to different roles rather than demand universal adoption. The discussion also covers common employee attitudes toward AI and how non-technical builders and domain experts can use agentic AI within existing workflows to create scalable enterprise value.
本期 Practical AI Podcast 由主持人与嘉宾 Mike Lewis 讨论企业中的 AI proficiency，即从普通使用者走向 builder 的路径。Mike Lewis 介绍了 L0、L1、L2、L3 等不同熟练度层级，并强调企业不应只是要求所有人使用 AI，而应针对不同角色提供合适的培训与工具。节目分析了员工对 AI 的多种态度，如 job fearful、quality disappointed、too busy，以及为何不能简单替换这些人。讨论还涉及 non-technical builder 如何利用 agentic AI、现有工具和工作流构建可持久扩展的解决方案。最后，嘉宾认为 L2 这样的领域专家型 builder 能把 AI 能力与公司品牌和业务需求结合起来，真正推动企业价值。
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Welcome to the Practical AI Podcast where we break down the real-world applications of
欢迎收听 Practical AI Podcast，在这里我们拆解 AI 在现实世界中的应用
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artificial intelligence and how it's shaping the way we live, work, and create.
以及它如何塑造我们生活、工作和创造的方式。
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Our goal is to help make AI technology, practical, productive, and accessible to everyone.
我们的目标是让 AI 技术变得实用、高效，并且对所有人开放。
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Whether you're a developer, business leader, or just curious about the tech behind the buzz,
无论你是开发者、企业管理者，还是只是对这股热潮背后的技术感到好奇，
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you're in the right place.
你都来对地方了。
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Be sure to connect with us on LinkedIn, X, or Blue Sky to stay up-to-date with episode
记得在 LinkedIn、X 或 Blue Sky 上关注我们，及时获取
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of Drops, Behind the Scenes, Content, and AI Insights.
Drops、Behind the Scenes、Content 和 AI Insights 的剧集更新。
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You can learn more at practicalai.fm.
你可以在 practicalai.fm 了解更多。
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Now, onto the show.
现在，进入节目。
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Welcome to another episode of the Practical AI Podcast.
欢迎收听 Practical AI Podcast 的又一期节目。
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This is Daniel Whitenack, I am CEO at Prediction Guard, and I'm joined as always by my co-host
我是 Daniel Whitenack，Prediction Guard 的 CEO，像往常一样，和我一起主持的是
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Chris Benson, who is a principal AI and autonomy research engineer.
Chris Benson，他是首席 AI 和 autonomy 研究工程师。
00:55
Are you doing Chris?
Chris，你最近怎么样？
00:56
Doing good today.
今天不错。
00:57
How's it going?
你怎么样？
00:58
It's going great.
一切都很顺利。
00:59
I'm continually impressed by the amazing AI work that's happening around not only on
我一直对各地发生的惊人AI工作印象深刻，不仅仅是在
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the coast, but in kind of the, I guess, the heartland, the middle of the country, where
沿海地区，而且在，我猜，中西部，国家的中心地带，那里
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a lot of actually the large enterprises of our country are located.
实际上我们国家很多大型企业都位于那里。
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We have a guest related to that today, but I do want to remind folks, we're also involved
今天有一位相关的嘉宾，但我想提醒大家，我们还是
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in a sponsor of the Midwest AI Summit, which is coming up October 15th in Indianapolis.
中西部AI峰会的赞助方之一，该峰会将于10月15日在印第安纳波利斯举行。
01:35
Really cool event, Chris.
真是个超棒的活动，Chris。
01:37
You're there.
你在那里。
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You saw what was going on.
你看到了当时的情况。
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There's tables where you can sit down with actual AI practitioners, and rather than just
有些桌子可以让你和真正的 AI 从业者坐下来聊，而不是只听一堆演讲；你能得到关于你正在做的事情的反馈、建议、设计等等，还能听到很棒的演讲。
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hear a bunch of talks, you can actually get feedback on what you're doing, suggestions,
我建议大家去看看，Midwest AI Summit。
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design, et cetera, and hear great talks.
你可以用代码 practical AI20 享受八折优惠。
01:51
I recommend people check it out, Midwest AI Summit.
但我们有一位很棒的 AI 从业者，来自我附近，更靠近 Cincinnati。
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You can use the code practical AI20 for 20% off.
Mike Lewis 之前和我们一起录过一期节目。
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But we have an amazing AI practitioner from close by my area, more towards Cincinnati.
那期节目我们收到了很多很好的反馈。
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Mike Lewis was on a previous episode with us.
Mike Lewis 之前来过我们节目。
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We got a ton of great feedback on that episode.
那期节目我们收到了很多特别好的反馈。
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He's chief AI architect at tier one performance.
他是 tier one performance 的首席 AI 架构师。
02:18
Welcome, Mike.
欢迎，Mike。
02:19
Thank you, Daniel.
谢谢，Daniel。
02:20
It's great to be here again.
很高兴再次来到这里。
02:22
I have multiple people comment on just the utility and insights that they got out of
有很多人评论说，他们从我们之前的讨论中
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our previous discussion, and just for context, because I think it's so impressive what you're
获得的实用性和见解。为了说明一下背景，因为我觉得你现在所做的
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doing and what you're involved with.
以及你所参与的事情都非常了不起。
02:38
Could you just set a little bit of context for kind of the types of projects that you work
你能稍微介绍一下你参与的项目类型吗？
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on, like give an example of some of the types of companies that you work with in relation
嗯，比如举个例子，关于你合作的那些类型的公司
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to AI initiatives?
在AI initiatives方面？
02:50
Yes, sure.
是的，当然。
02:51
So tier one performance is an end-to-end organizational performance and transformation
所以，Tier One Performance是一个端到端的组织绩效和转型
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partner.
合作伙伴。
02:58
What does that mean?
那是什么意思？
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We kind of help some of the most of the largest organizations in the world rethink transformation.
我们算是帮助一些世界上最大的组织重新思考转型。
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I would add in though that we have a non-traditional approach and a multi-decade track record of
不过我要补充一点，我们有一种非传统的方法和几十年的
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success there.
那方面很成功。
03:18
The types of clients we'd work with day-to-day would be like Google, Eli Lilly, Takeda,
我们日常合作的客户类型包括 Google、Eli Lilly、Takeda，
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Air Force, most of the Fortune 100s, and we see everything related to transformation.
Air Force，以及大多数 Fortune 100 公司，我们会看到所有与 transformation 相关的事情。
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Obviously, AI would just represent a sliver of the types of challenges we encounter as
显然，AI 只是我们作为组织日常所遇到的挑战中的一小部分，
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an organization day-to-day, but that sliver is my whole life.
但这一小部分就是我的全部生活。
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I don't really see all the other stuff.
我其实不太看到其他那些东西。
03:47
I kind of get a glimpse into it every now and because more and more AI touches everything.
我时不时会瞥见它，因为 AI 越来越多地触及一切。
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But we are sort of a transformation partner, so you can just imagine how the phone starts
但我们有点像 transformation 合作伙伴，所以你可以想象电话响起来的样子。
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ringing when a massive disruptive technology is birthed into our lives, whether we want
当一项巨大的颠覆性技术诞生并进入我们的生活时，无论我们愿不愿意，响声便会响起。
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it or not.
对。
04:09
Yeah.
我觉得人们在转型方面挣扎的一部分原因是信息来源太多了。
04:10
Part of that I think people are struggling with on the transformation side is there's
围绕着你该关注什么、人们实际在做什么、人们说他们在做什么、什么上了新闻，有太多噪音。
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so many sources of information.
各种各样的事情都有，显然其中很多都可能只是噪音。
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There's so much noise around what you should be paying attention to, what people are
现在有太多噪音了——到底该关注什么，别人实际在做什么，别人说自己在做什么，什么又成了新闻热点。
04:20
actually doing, what people are saying they're doing, what is hitting the news.
各种事情五花八门，显然其中很大一部分都是噪音。
04:27
There's all sorts of a range of things and obviously a lot of that can be noise.
你平时日常工作里，显然会听到很多东西，既有来自你合作的客户的，也有新闻周期里的，还有 Anthropic、OpenAI、Hugging Face 这些公司发布的新东西。
04:32
One of the things I've appreciated in interacting with you over time is that ability to pick out
在和你长期互动中，我很欣赏的一点是，你能从噪音里挑出一些信号，并形成某种结构化的思考方式，去理解AI和转型在真实组织环境里的实际影响。
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some of that signal from the noise and develop some kind of structural ways of thinking about
在你的日常工作中，显然你会听到很多东西——来自你在跟的客户、新闻周期里的，还有Anthropic、OpenAI、Hugging Face这些发布的各种内容。
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AI and transformation in an actual real-world organizational environment.
你的流程是什么样的？或者说，你日常的节奏怎么帮你隔离出那些信号，也许还能提炼出一些你应该...
04:53
In your kind of day-to-day, obviously you're hearing a lot of things both from customers
在你日常工作中，显然你会听到很多东西，无论是来自你合作的客户，还是新闻动态，还有 Anthropic、OpenAI、Hugging Face 这些公司发布的东西。
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that you're working with, the news cycle, the things from anthropic, open AI, hugging
到了第一年，这实际上就是 workforce enablement、performance，你懂的，基本上不是 Substack 上的文章，而是看着事情在公司里展开，回顾我的工作经历，那些曾和我一起工作的年轻人。
05:02
face whoever that's coming out with things.
我，你知道，绝不会再那样了。但我还是带来了200页的研究引用和综合。
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What does your process look like, or how do you feel like your rhythms day-to-day help
你的流程是什么样的，或者你觉得你日常的节奏是怎么帮助
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you kind of isolate some of that signal, maybe kind of distill down some of what you should
你筛选出一些信号，也许提炼出一些你应该
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be paying attention to?
该关注什么？
05:21
Any suggestions?
有什么建议吗？
05:22
I think it's something on all of our minds, certainly on my mind.
我觉得这是我们所有人都在想的事，至少我是这样。
05:25
Yeah.
对。
05:26
Maybe I'm very good at this because I am just like the weirdo oddball guy who stumbled into
也许我很擅长这个，因为我就像一个怪人，误打误撞地
05:38
this at the perfect moment.
在完美的时机钻了进来。
05:40
I mean, Daniel, you know this about me and your audience might remember.
我是说，Daniel，你知道我的这件事，你的听众可能还记得。
05:43
I was a portrait painter for almost 20 years.
我当了差不多20年的肖像画家。
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I mean, from when I graduated college, still 2016, I painted portraits and I owned a fine
我是说，从我2016年大学毕业那会儿起，我画肖像画，拥有一家美术公司，还有一个版画艺术家团体。我之所以进入这行，是因为听说了OpenAI的Dolly model，申请成为商业艺术beta testers之一。我之前了解过那个。有天晚上吃饭时收到一封邮件，我当时就想，哇，我居然获得了这个当时就有所耳闻的东西的访问权限。我懂一点Python啊编程之类的，足够我瞎折腾了。
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arts company and a print-ist-a-bunch-of-artist and I only got into this because I had heard
艺术公司，还有一个版画家...一堆艺术家，我是因为听说了
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about the Dolly model from OpenAI and applied to become one of the commercial arts beta
关于OpenAI的Dolly model，并且申请成为商业艺术beta
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testers.
测试者。
06:07
I'd looked into that.
我之前查过那个。
06:08
I got an email one night at dinner and I was like, oh wow, I just got access to this
有天晚上吃饭时我收到一封邮件，我想，哇，我刚刚获得了这个
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thing known and heard of at the time.
当时已经听说过的东西的访问权限。
06:14
I knew a little bit like Python and coding or whatever, so enough to like fumble around
1. 我懂一点 Python 和 coding 之类的，够我瞎折腾了。
06:18
and get things installed and I felt in love with language models.
把东西装好之后，我就爱上了 language models。
06:23
I mean, almost instantly.
我是说，几乎立刻就爱上了。
06:24
I just couldn't believe all the new things you could make computers do.
我就是不敢相信你能让电脑做出这么多新东西。
06:29
And you know, this is before we really thought about them as chatbots or whatever.
而且你知道，这还是在我们把它们当成 chatbots 之类的之前。
06:33
In my mind, it was like something you plug into code to just manage edge case weirdness
在我的脑海里，它就像是你插到 code 里，专门用来处理 edge case 那种奇怪情况的东西。
06:38
to, you know, pick a path and make your app keep working and, you know, context models
就是，你知道，选一条路径让你的 app 继续正常工作，而且，你知道，context models
06:43
were minuscule back there.
在那个时候还非常小。
06:44
I'm running things locally.
我是在本地跑这些东西的。
06:45
I'm like gaming computer, you know.
2. 我就像个游戏电脑，你懂的。
06:49
And then, you know, medical records company start calling and I've built this book of business
3. 然后，你知道，医疗记录公司开始打电话来，我已经建立了这么一本业务账。
06:54
into your one acquires my company here's the only reason that's worth unpacking is to
4. 进入你的一个收购我的公司，这里唯一值得展开的原因是
06:57
say like, I don't have this like muddy, long history in the industry where I had opinions
5. 比如说，我没有那种乱七八糟的、漫长的行业历史，在那里我有各种看法
07:04
about everything or like a solid, you know, way of thinking about it was all just fun toys
6. 关于一切，或者一个坚定的，你知道，思考方式，都只是好玩的玩具
07:10
for me.
7. 对我来说。
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And then, I think the way I've made it through business my whole life, I've owned maybe
8. 然后，我觉得我这辈子在生意场上一路走来的方式，我可能拥有过，也许
07:15
a dozen businesses all small, but is I've always just had a firm rule is like, I do not
有十几个小企业，都很小，但我一直有一条坚定的原则，就是，我不会
07:22
concern myself with things outside of my sphere of influence.
我不会去关心那些不在我影响范围内的事情。
07:25
So, you know, there may be this big thing going on at the edge of the AI sphere, but the
所以，你知道，AI 领域边缘可能正发生着一些大事，但
07:31
reality is like, if I, if I don't have influence or if it doesn't impact like the way I'm interacting
现实是，如果我没有影响力，或者它不会影响我和客户互动的方式，
07:35
with my clients, if it's not, then I just don't, I just ignore it.
如果不是这样，那我就不管，我就忽略它。
07:38
These things are not going away.
这些事情是不会消失的。
07:40
Like I know for sure, whatever this is, it will be here probably forever.
就像我很确定，不管这是什么，它很可能会永远存在。
07:46
And in my experience, I'm a much better worker.
而且以我的经验，我工作起来要高效得多。
07:49
I mean, I can fool almost anyone in the thinking I'm a smart guy when I'm using a high and
我的意思是，当我使用一个高……的时候，我几乎可以让任何人以为我是个聪明人。
07:55
I'm aligning contacts to like whatever my work project is.
我把联系人都对齐到我当前的工作项目上。
07:58
I mean, it just works so much better using these tools.
我的意思是，用这些工具就是效果好太多了。
08:02
And I just have that conviction.
我就是有这个信念。
08:03
That's probably true for most people.
对大多数人来说可能都是这样。
08:05
So, Daniel, my trick is really only focusing on like what, what directly impacts like the
所以，Daniel，我的诀窍就是只关注那些直接影响到我日常工作的东西。
08:11
things going on in my day to day.
而在第一年，那主要就是 workforce enablement、performance，你知道，基本上不是
08:13
And at year one, what that is is a workforce enablement, performance, you know, basically not
所以这不是200页的研究报告。而是200页，每页包括论文名称、一个URL，可能还有一句话，说明它为什么可能和我工作相关，就是用来读的。
08:23
worrying so much about tools or whatever, but just outcomes and performance.
不要太担心工具什么的，只看结果和性能。
08:28
Yeah, that makes a lot of sense.
是啊，很有道理。
08:29
I, and one of those things, you know, last time we talked, I looked up the date.
呃，而且，你知道，上次我们聊的时候，我查了下日期。
08:35
It was like 2024, right?
好像是2024年，对吧？
08:38
Yeah, sometime in 2024, obviously a lot has changed.
对，2024年某个时候，显然发生了很多变化。
08:43
It's impacting all of us in different ways.
它正以不同的方式影响着我们所有人。
08:46
At that time, we had a discussion about what's, I think, doable, scalable, et cetera.
那时候，我们讨论过什么是可行的、可扩展的，等等，我觉得。
08:54
You've, I know, spent a bit more time recently thinking about this concept of AI proficiency.
我知道你最近花了不少时间在思考AI proficiency这个概念。
09:02
And I know myself, you know, obviously if you're doing AI things, you're searching them,
而且我自己也清楚，你知道，显然如果你在做AI相关的事，你就会去搜这些东西，
09:08
you get targeted online.
然后你在网上就会被精准投放广告。
09:09
I'm all this, all the time seeing these like ads for whatever it is, Harvard school,
我整天都在看这些广告，什么哈佛学院啊之类的，
09:15
like what the engineering or what, becoming AI proficient in your business or whatever
比如什么工程学啊，或者让你的业务精通AI什么的，
09:22
the, you know, the course or thing is.
你知道，就是那些课程啊之类的东西。
09:25
And so there, there's a lot of people trying to understand this because of, like you say,
所以有很多人想搞明白这个，因为就像你说的，
09:32
the wide-reaching impact across the workforce.
它对整个劳动力市场有着广泛的影响。
09:36
So next week, our company is doing an AI accelerator with one of our customers.
所以下周，我们公司要和我们的一位客户一起搞一个AI accelerator。
09:42
I know that there's going to be a whole range just from discussions of, quote, AI proficiency.
我知道，光是讨论那个所谓的“AI 熟练度”，就会有一整个范围。
09:51
But general, like other than thinking, well, I know that there's that range, right?
但一般来说，除了思考之外，呃，我知道是有那个范围的，对吧？
09:57
Um, it's another step to go and say, well, in light of that range of proficiencies,
呃，接下来还要再进一步说，嗯，鉴于这一系列的熟练度，
10:06
what do I need to change for different proficiencies?
针对不同的熟练度，我需要改变什么？
10:08
How do I advance people through proficiencies?
我要怎么让人们逐步提升熟练度？
10:10
Do they even need to advance through different levels of AI proficiency?
他们真的需要去经历不同等级的 AI 熟练度吗？
10:15
What is enough for some people?
对某些人来说，什么才算足够？
10:17
What, what is too much, right?
什么，什么算太多，对吧？
10:19
So I don't know if you want to help us launch into this topic.
所以我不知道你愿不愿意帮我们切入这个话题。
10:23
Maybe just starting with a little bit of definition of what we mean by proficiency
也许先稍微定义一下我们所说的“熟练度”
10:29
would help us just so that we're all talking about the, the same thing.
会有帮助，这样我们就都在说同一件事了。
10:33
If you don't mind, Daniel, I'd like to even go a step further back.
如果你不介意的话，Daniel，我想再往回退一步。
10:36
Yeah.
嗯。
10:37
And just give you a sense for how and why even started thinking about this.
只是想让你了解一下我是怎么以及为什么开始考虑这个的。
10:41
So if, if inside of our, if at tier one, we have, you know, most of the largest,
所以如果，在我们内部，如果是在tier one，我们有，你知道，大多数最大的公司，
10:47
we and three or four other companies are helping the largest companies in the world
我们和另外三四家公司正在帮助世界上最大的那些公司。
10:51
navigate this disruption.
应对这场 disruption。
10:53
And we also see the same story playing out inside of every company.
而且我们在每家公司内部也看到同样的故事在上演。
10:58
Like, I mean, I could, I could tell you 95% of the companies, I could walk through the timeline
就像，我的意思是，我可以告诉你，95%的公司，我可以把时间线过一遍
11:03
and you'd say, yeah, I saw that at fill in the blank, fill in the blank, fill in the blank.
然后你会说，嗯，我在某某公司、某某公司、某某公司都见过。
11:07
They've made all the same mistakes.
他们犯了所有同样的错误。
11:09
That, I, it's kind of watching that happen sort of helpless at the periphery.
那种感觉，就像是在外围无助地看着这一切发生。
11:13
You know, as a consultant, you, you don't have a lot of control.
你知道，作为顾问，你没有太多控制力。
11:16
But, you know, and you don't have perfect ideas either.
但是，你知道，你也没有完美的想法。
11:19
You know, so everyone's just sort of watching this thing unfold and like,
你知道，所以大家就都在看着这事儿慢慢展开，然后就像，
11:22
oh, I really thought that was going to work.
哦，我原本真以为那会成功的。
11:23
But that didn't stick.
但那个没成。
11:24
And, and the big thing that I focused on early on was developing tools that help people
而且，而且我早期重点关注的是开发一些工具，帮助人们
11:29
learning, get good with AI.
学习，怎么用好AI。
11:31
So I, I developed our, you know, solution archetypes framework, where we kind of like
所以我，我开发了我们的，你知道，solution archetypes framework，我们有点儿
11:36
tried to pin down, we talked about that on the last episode.
试着去界定清楚，这个我们上一集聊过。
11:39
And then I built our super user habits index, which is basically it's like,
然后我又建了我们的 super user habits index，基本上就是，
11:43
hey, these are the 24 habits we see super users displaying.
嘿，这些就是我们看到的 super users 展现出来的24个习惯。
11:47
And, and then I built a coaching tool that people could use.
然后呢，我建了一个大家可以用的辅导工具。
11:50
And, and in my mind, it was like, I'm going to put all this together and turn people into super
而且在我心里，我想的是：我要把这一切整合起来，把人们变成 super users。
11:55
users. And guess what? It's kind of didn't really happen.
你猜怎么着？其实并没有真的发生。
11:59
For some people, it did.
对有些人来说，确实发生了。
12:00
But I couldn't help but feel like most of them, it was going to happen anyway.
但我不禁觉得，对大多数人来说，他们本来也就会变成那样。
12:04
And at the same time, I'm watching, I'm at the same time, I'm sort of reading all the
与此同时，我在观察——同时也在读所有相关的 Substack 文章，看着公司里的事情发展，回顾自己的工作经历。
12:10
substack articles on it, watching things unfold at companies, looking at my work history,
关于它的 substack 文章，看着各家公司的动态，回顾我的工作经历，
12:16
thinking through the people, looking at the statistics we create or stuff in the literature.
思考这些人，看看我们创造的统计数据，或者文献里的那些东西。
12:23
And then I think the breakthrough moment for me, I was invited to a bachelor party with some
然后我觉得对我来说的突破时刻，是我被邀请去一个单身派对，跟几个以前在我手下工作的年轻小伙子一起。我，你知道，再也不去了。但我带了200页的研究引用和综述。所以这不是200页的研究内容。是200页的论文标题、URL，可能还有一句话说明为什么跟我的工作相关，就是为了在那周、在单身派对期间读的。我当时觉得自己大概得经常抽身出来。这些人都是更年轻的家伙。而我确实那样做了。我全读完了。里面就是，就是，就是有一些模式，回答了我的很多问题，而且——
12:28
young guys who used to work with me. I, you know, never again. But I brought 200 pages of research
那些曾和我共事的年轻人。我，你知道，再也不会了。但我带了 200 页的研究
12:37
citations and synthesis. So this is not 200 pages or researches. 200 pages of the name of a paper,
引用和综述。所以这并不是 200 页的研究。200 页的论文名称、
12:44
a URL, and maybe a sentence about why it might be relevant to my work, just to read
一个 URL，以及可能一句话说明它为什么与我的工作相关，只是为了读
12:49
during that week during the bachelor party. I thought I was probably going to need to pull away
那周是在 bachelor party 期间。我当时以为自己可能得经常抽身出来。那些都是比较年轻的哥们。结果我还真读了，全读完了。然后里面就是，就是有一些模式，解答了我很多疑问。而且那个突破性的时刻，差不多就发生在30到60天之内。那就是在形成的“汤”。我读了一篇 Substack 文章，作者是 Peter Yang。我大概还在屏幕上扫一下细节。但基本上那篇叫“你的新工作是 onboard AI agents”，讲 AI native 公司到底怎么运作。然后他们就是有这样一个思考框架，从 L0 到 L3。所以那个不是我想出来的，我是在那篇 Substack 上读到的，L0 到 L3。
12:54
a lot. These are all younger guys. And I did. I read it all. And there were just,
很多。这些都是比我年轻的家伙。而我确实，把那些全读了。然后就是有，
13:00
there were, there were just patterns in there that answered a lot of questions for me and,
就是有一些模式在里面，回答了我的很多疑问，而且，
13:04
and the breakthrough moment with all of that just sort of happening within like 30 to 60 days.
而且那种突破性的时刻，所有这些差不多就在30到60天里发生了。
13:10
That's stew forming. I read a substack article is Peter Yang. I'm kind of skimming my screen
那就像是在慢慢酝酿。我读了一篇Substack文章，是Peter Yang写的。我正快速浏览我的屏幕，
13:18
here for the details on it. But basically it was called your new job is to onboard AI agents,
想找找里面的细节。不过基本上它叫“你的新工作是让AI agents上手”，
13:24
how AI native companies actually operate. And, and they just had this, this, this way of thinking
AI native公司实际上怎么运作。然后他们就有这种、这种思维方式，
13:30
through the L0 through L3. So I didn't invent that. I read it in that subset L0 through L3
从L0到L3。所以那不是我发明的。我是在那个Substack里读到的，L0到L3，
13:37
classification. So L0, L1, L2, and L3. And the L0s are the people who aren't using it. And the L3s
分类。所以是L0、L1、L2和L3。L0是不用它的人。L3是那些，
13:43
are the ones who are, you know, just making a difference across the entire enterprise. And we all
你知道
13:49
know those. And then they labeled L1 and, and L2, the like knocked me off my chair almost when I,
你知道那些。然后他们给L1和L2标了出来，那几乎把我从椅子上震下来——当我...
13:56
when they talked about the concept of a non-technical builder. And they just gave a name to a thing
当他们谈到non-technical builder这个概念时，他们只是给一个东西起了个名字。
14:02
that I just thought, wow, this is, this is something we need to really focus on is like the idea
我当时就想，哇，这就是我们真正需要关注的东西，就是non-technical builder这个想法。
14:08
of a non-technical builder. We're all focusing on converting L0s, people who are disengaged. And
我们都在专注于转化L0，也就是那些不参与的人。
14:14
it will unpack what that is. I think we need to because there's so much important stuff there. And
我们会展开讲那是什么。
14:20
they're trying to get people from L0 to L1. And L1 is what everyone is, what everyone knows,
我觉得我们需要这样做，因为那里有太多重要的东西。
14:24
it's the user. It's the one who's like, I couldn't live without this. And they kind of feel like
他们试图让人们从L0到L1。
14:28
it ends here. And then that leap, you know, the big jump from like, okay, someone who like uses AI
L1就是每个人现在的状态，每个人都知道的，就是用户。
14:33
to wait a minute. No, this is a non-technical builder. This is a person building durable solutions
就是那种会说“我没它活不了”的人。
14:38
that emulate the company's work in an uncanny way. That jump is actually the one that now I sort
那些以不可思议的方式模仿公司工作的东西。那个飞跃实际上就是我现在算是到处宣传的东西。比如这才是你真正需要投入精力的地方。但是，Daniel，我猜我说这一大堆就是想表达，对我来说，我就像是，怎么说呢，一锅乱炖，就是，你知道，一个本来跟这事毫无关系的人，意外地创建了一家公司。它被Tier 1收购了。现在我在这里。我身处所有这些公司内部，试图帮助他们理解这件事。然后，你知道，所有这些外部输入就这么碰撞在一起。所以现在我们，这就是我们推行、宣传并帮助落地的框架。并让大家好好想明白。如果你过去几个月一直在听这个节目，
14:46
of run around evangelizing. Like this is actually where you need to focus your energy. But so, so Daniel,
到处去宣传。真的，这才是你该集中精力的地方。
14:51
I just, I guess I unpacked all that to say, like for me, I had the, like, the stew, I guess,
不过，Daniel，
14:59
as a way to say it, of like, you know, the guy who like, didn't have a dog in the fight,
我，我想说，我刚刚说了那么多，就是想表达，对我来说，我就像，嗯，一锅大杂烩，
15:04
built a company on accident. It was bought by Tier 1. Now I'm here. I'm inside of all these
这么说吧，你知道，就是那种原本跟这件事毫无关系的人，
15:09
companies trying to help them make sense of this thing. And then, you know, all these external
意外创建了一家公司，然后被 Tier 1 收购了。现在我就在这里。
15:14
inputs sort of just clashed. And so now we, this is the framework we push and advertise and help.
我身处所有这些公司内部，试图帮他们理解这件事。
15:21
And ask people to think through. If you've been listening to the show over the past few months,
然后，你知道，所有这些外部输入就这么碰撞在一起。
15:26
you realize how transformative agentic AI is, whether it's Claude or Hermes agent or your own
你会意识到 agentic AI 有多么具有变革性，无论是 Claude、Hermes agent，还是你自己部署用于提升运营效率或作为产品推向市场的定制软件。
15:34
custom software that you're deploying for operational efficiencies or as a product into the market.
这些系统具有变革性，也是行业发展的方向。
15:42
These systems are transformative and it's where the industry is going. But agents have a lot of
但 agents 也伴随着很多风险。
15:48
risk associated with them. They have agency. They take action within your environment within
它们有 agency。
15:52
your infrastructure, within your systems. And that's why security teams and governance teams
它们会在你的环境、基础设施和系统中采取行动。
15:59
view it as risky to deploy these agents within high impact environments and industries like
这就是为什么安全团队和治理团队认为，在 high-impact environments 以及制造业、物流、金融服务、公共部门等行业中部署这些 agents 是有风险的。
16:05
manufacturing, logistics, financial services in the public sector. And that's why I've personally
也正是因为这个原因，我个人一直在花时间与一个很棒的 AI 团队合作，开发一款名为 Prediction Guard 的产品。
16:12
been spending my time working on a product called Prediction Guard with a great team of AI
所以现在我们，这就是我们推广、宣传并帮助大家使用的框架。
16:18
engineers. Prediction Guard is an AI control plane that you host within your own environment,
工程师们。Prediction Guard 是一个 AI control plane，你可以把它托管在自己的环境里，不管是 on-prem、hybrid，还是你的 cloud VPC，甚至是 air-capped 场景。你可以设置自定义 AI 策略，或者那些符合 NIST 和 OOS 标准的策略。然后这些策略会在每一次 handshake、每一个 agent 之间自动强制执行，不管底层用的是你自己的 self-hosted 模型，还是你 cloud 环境中的模型，比如 Azure 或 AWS bedrock 提供的模型。所有这些 telemetry 数据都会回流到你的 monitoring 和 observability 系统中。我非常希望大家来看看我们在做什么。可以预约一个 demo，并和我们团队通个电话，了解更多信息，访问 PredictionGuard.com/practical AI。就像我说的，今天就预约通话吧。我们很乐意展示。
16:24
whether that's on-prem, hybrid or in your cloud VPC, even air-capped scenarios. You can set custom
不管是 on-prem、hybrid，还是在你自己的 cloud VPC 里，甚至是 air-capped 场景。你可以设置自定义的
16:32
AI policies or those that are aligned with NIST and OOS standards. And those are then enforced
AI 策略，或者是那些符合 NIST 和 OOS 标准的策略。然后这些策略就会被强制执行
16:39
automatically across every handshake, across every agent, whether that's being powered by your
自动地在每一次 handshake、每一个 agent 上执行，不管是由你的
16:46
own self-hosted models or models in your cloud environment like those from Azure or AWS bedrock.
自己的 self-hosted models 还是你 cloud 环境里的模型，比如来自 Azure 或 AWS bedrock 的那些模型。
16:54
And all of that telemetry goes back to your monitoring and observability system. I would love
而且所有这些 telemetry 数据都会回到你的 monitoring 和 observability 系统。我很想
16:59
for you all to check out what we're doing. Schedule a demo and a call with our team to find out more
让大家看看我们在做什么。
17:06
at PredictionGuard.com slash practical AI. Like I say, schedule a call today. We're happy to show
预约演示，和我们团队打个电话，了解更多。
17:13
you how this works and why we think it is so beneficial to the market. People already have this
你知道这是如何运作的，以及为什么我们认为这对市场如此有益。人们已经在生产环境中部署了它，为多个行业的变革性agentic systems提供动力。所以请到PredictionGuard.com/practical AI来看看我们。就是PredictionGuard.com/practical AI。所以Mike想问你一个问题。当你在思考如何让你的一家客户公司的员工从L0s升到L3s时，我想再加入一个变量。那就是人们的态度，这些态度非常多样，总有一些人很兴奋。就像你之前提到的，有些人自然会想要去L1、L2，一直到L3。但也有人会强烈反对这一点。
17:20
deployed in production, powering, transformative agentic systems across a number of industries. So
访问 PredictionGuard.com slash practical AI。
17:26
check us out at PredictionGuard.com slash practical AI. That's PredictionGuard.com slash practical AI.
就像我说的，今天就预约电话沟通。
17:38
So Mike wanted to ask you a question. As you are thinking about how you get the employees of one
我们很乐意展示
17:47
of your client companies moving from the L0s up to the L3s, want to throw another variable in. And
已经在生产环境中部署，驱动着多个行业的变革性 agentic systems。
17:54
that is the attitudes that people have, which are very varied in terms of there's always people
所以去 PredictionGuard.com slash practical AI 看看我们吧。
18:00
who are excited. As you mentioned before, there are people that will naturally want to go to
就是 PredictionGuard.com slash practical AI。
18:04
that L1, L2, and up to L3. But there are also people that are going to push back hard on that.
就是L1、L2，一直到L3。但也有一些人会对此强烈反对。
18:10
And so when you're kind of coming in and you're trying to start your process of helping them achieve
那么当你进来，开始帮助他们实现这个目标的过程中，你怎么带动那些其实不想动的L0们？
18:17
that, how do you bring along the L0s that don't really want to move? Or even the ones that have
或者甚至那些已经做了一点、但也在抵触的人？
18:23
done a little bit, but they're also pushing back on that. Maybe they fear for their jobs or
也许他们是担心自己的工作之类的。
18:28
something like that. So there's that kind of L0s and maybe some L1s. How do you get over that process
所以就有那种L0，也可能有些L1。
18:34
as you're trying to bring everybody into this to kind of level up through those? Any thought?
当你试图让所有人都参与进来，让他们通过这些层级升级的时候，你是怎么能迈过这个过程的？
18:41
Can you kind of throw that in as you're talking about your process?
有什么想法吗？
18:45
Yeah, I love that you're asking me about L0s because the reality is we don't try to move in L0.
你能在讲你的流程时顺便聊聊这个吗？
18:53
Here's the thing. The article I mentioned, the sub-stack article, I disagreed with 98% of what
嗯，我很高兴你问我关于L0的事，因为实际情况是我们并不试图让L0动起来。
19:00
I read in that article. I just latched onto the concept of an L2 and non-technical builder.
我在那篇文章里读到的。我一下子就抓住了L2和非技术型builder这个概念。
19:04
That name resonated with me. The L0s in that article, at least at ramp, the way I interpreted
这个说法让我很有共鸣。那篇文章里的L0们，至少在ramp，按我的理解
19:12
what I read, they were saying that, hey, if you're an L0 at ramp, of course, it's a software
我读到的内容是，他们在说，嘿，如果你在ramp是L0，那当然，这是一家软件
19:17
company. If you're an L0 at ramp, that's grounds for dismissal. You have until this date for
公司。如果你在ramp是L0，那就该被辞退。你有一个最后期限，到那时
19:22
our system to assess you as an L1. And man, that just broke my heart because it's kind of like,
我们的系统会把你评估为L1。天哪，这真的让我心碎，因为这就有点像，
19:28
okay, wait a minute. Let's back up. Let's back up. Name another technology that we would say
好吧，等一下。我们退回去。退回去。还有哪项技术能让我们说
19:33
that true, but can you imagine you just go company wide? Hey, by the way, everyone, we want you
这是真的？但你能想象你就这样推广到全公司吗？嘿，顺便说，各位，我们希望你们
19:37
to geek out about smart sheets and be great at smart sheets by the end of this year or AWS or
对smart sheets特别上头，到今年年底能精通smart sheets，或者AWS，或者
19:45
it's ridiculous. This is just another technology like that. Yet, I think a lot of executives are
这太荒谬了。
19:51
kind of scrambling and panicking and they're saying, hey, guess what, we're going to be AI enabled,
这只是又一项类似的技术罢了。
19:55
we're going to be activated. Everyone in our company needs to speak AI by accident or there's
但我觉得很多高管都在手忙脚乱、惊慌失措，他们说，嘿，你知道吗，我们要实现AI赋能，我们要被激活了。
20:01
not a place for you here. And so, first of all, you remember, I read 200 pages of science and a lot
我们公司里的每个人都必须会说AI，否则这里就没有你的位置。
20:08
of it was like, it was just about learning. It wasn't even about AI. And so threat framing actually
所以，首先，你记得，我读了200页科学文献，其中很多都只是关于学习的。
20:15
does slow down adoption. So, you know, if you put, if you back someone into a corner and say,
甚至根本不是关于AI的。
20:20
learn this or there's not room for you here, they will not learn it as well as if you came to them
所以说，威胁框架实际上会拖慢采用速度。
20:25
and said, let's figure this out together if it interests you. And I will acknowledge that there
所以，你知道，如果你把某人逼到墙角，说，学会这个，不然这里没你的位置，他们学习的效果，肯定不如你走到他们面前说，我们一起搞清楚吧，如果你感兴趣的话。
20:30
are some positions where you absolutely need an AI enabled individual. It's true. Like, you know,
有些岗位绝对需要具备 AI 能力的人。这是真的。比如说，你知道，
20:35
and so there are cases where an L0 is not going to work in that role. But I think we're going to
所以有些情况下，L0 在那个岗位上是干不了的。但我觉得我们将
20:40
realize in 10 years looking back at all this that it's just not true in every role. And I think
在十年后回头看这一切时意识到，并不是每个岗位都如此。而且我认为
20:45
the one that hit me the hardest is my wife, probably the smartest person I know in the world,
最让我触动的是我妻子，她可能是我认识的人当中最聪明的，
20:49
my wife, the smartest person I know. And she has no use for AI in her job. She's a nurse.
我妻子，我认识的最聪明的人。她的工作完全用不上 AI。她是护士。
20:57
And she kind of just, I know what she does. She pokes people in the arm with needles. And,
她基本上就是，我知道她做什么。她用针扎别人的胳膊。还有，
21:03
you know, some other things. And there's medical records. Maybe someday it'll be useful to her.
你知道，还有一些别的事。还有病历。也许有一天会对她有用。
21:07
It's just really not right now. It would be in the way. And, and I started doing research on the
但现在真的不是。反而会碍事。而且，而且我开始研究这个
21:14
concept of L zero people who are disengaged. And I realized there are multiple buckets. So when
关于L zero人群的概念，就是那些不投入的人。然后我意识到这有好几类。所以当
21:23
we talk about an L zero, it's not a thing. So an L zero is not just someone who doesn't use AI.
我们说到L zero的时候，它不是一种单一的东西。L zero不只是不用AI的人。
21:29
I found five major categories. So one is the performative user. They've been doing this. They've
我发现了五大类。第一类是表演型用户。他们一直在做这些事。他们一直
21:34
been nodding their head and all the trainings, the meetings. They've logged into the thing. They've
在各种培训和会议中点头。他们登录了那个东西。他们
21:38
submitted a chat. And they've gone about their job. Like, you know, like, they're not really getting
提交了一次对话。然后又继续干活了。就像，你知道，他们其实并没有真正搞懂
21:42
and, and hey, they're still getting their job done. There's the disinterested.
但是，嘿，他们工作还是照常完成了。还有一种是不感兴趣的。
21:48
I think the moment when this hit me the hardest was when I was looking at all the research. And I
我想我最受触动的时刻，是在我翻看所有研究的时候。然后我
21:53
saw a chart that showed the adoption rates of personal computers in the office space.
看到一张图表，显示的是个人电脑在办公室的普及率。
21:59
A back when PCs were first released and AI. And there's almost the exact same adoption curve over
回溯到 PC 刚发布和 AI 刚出现的时候。采用曲线几乎一模一样，
22:05
the same period of time. It looks like it's happening at the same rate. And when I saw that, I thought,
在同样的时间段里。看起来是以同样的速度在发生。当我看到这一点时，我想，
22:10
how silly is it? Like, to think back to that. And, and, and like, no one is in a panic because
这有多傻？想想那时候。而且，而且，就像，没有人会恐慌，因为
22:16
the people in their company haven't figured out personal computers now. Like, it took care of
他们公司里的人到现在还没搞明白 PC 呢。就像，它会自己解决
22:20
itself because everyone wound up with one. And the same thing is happening with AI. Everyone went
因为最后每个人都有一台。AI 也是在发生同样的事。每个人都回家
22:24
home and just created a chat GPT account or whatever. It's free. This is not true with your CRM.
然后直接注册了个 ChatGPT 账号什么的。这是免费的。但你的 CRM 不是这样。
22:31
This is not true with smart. Like, everyone didn't run home and create a smart sheet account
Smart 也不是这样。就像，没有人会跑回家去创建一个 smart sheet 账号
22:36
because, you know, like, they just got to have one. And so, you know, but the disinterested are
因为，你知道，就像，他们就是需要一个。所以，你知道，但那些不感兴趣的人...
22:42
still detached there. Okay, here's another bucket. The too busy. I can give you 10 names at tier 1.
还是那样置身事外。好，这是另一类。就是那些太忙的。在 tier 1 我能给你 10 个名字。
22:47
We almost don't want them running around trying to figure out AI because they are just so critical
我们几乎不想让他们四处跑去琢磨 AI，因为他们太关键了
22:51
in their role. They're so good at what they do. It's just like, it's a don't break it or don't touch
在自己的岗位上。他们做事做得太好了。就像，就是那种“别搞坏”或者“别碰”
22:56
it. It's a broke type role. And, you know, who cares if they're using AI or not? And I think
它。这是一种“没坏别修”型的角色。而且，你知道，谁在乎他们用不用 AI 呢？而且我觉得
23:02
that is also really hard for the people who are here in communication, use AI or you're out of
这对在这里搞沟通的人来说也真的很难，要么用 AI，不然你就别想待
23:07
here. And then they can look around and see the people who like, very often it's some of the
在这儿了。然后他们环顾四周，看到那些人，通常就是一些
23:11
highest performers in the company who don't really care about it because they're in a rhythm.
公司里表现最好的那些人，他们根本不在乎，因为他们有自己的节奏。
23:16
So those I kind of push past. But the next two, these are still buckets in L0. These people who
所以那些我基本就不管了。但下面这两种，还是 L0 里的类别。这些人...
23:21
aren't using it really matter. And there's something you can learn from these people. And I think when
没用它的人其实很关键。而且你能从这些人身上学到点东西。我觉得当
23:26
you say like, Hey, you're going to be doing this, you're going to be using AI at this company, they
你跟他们说，嘿，你要干这个，你会在这家公司用AI，他们
23:31
will just zip their lips and they will not they're not their head. And you know, and they'll say,
就会闭上嘴，不会——不是点头同意那种。你知道，然后他们会说，
23:34
yes, you know, but here's the thing. First of all, we have the job fearful and Chris, I think you
是的，但问题是。首先，有这种“工作恐惧”，Chris，我觉得你
23:40
mentioned this, you might have mentioned this early job fearful. What do we do? What do we do about
提到过这个，你可能之前就提到过这种“工作恐惧”。我们该怎么办？怎么应对
23:43
the job fearful? First of all, very often these people don't really understand how the tool work.
这种“工作恐惧”？首先，这些人在很多情况下并不真正理解工具是如何运作的。
23:48
And they're under the impression that if they use AI to do their work, it's going to learn how to
他们会有一种印象：如果自己用AI来干活，AI就会学会
23:52
do what they do and replace them. And that's almost never true. I mean, just if you kind of know how
怎么干他们的活，然后取代他们。但这几乎不可能。我的意思是，只要你对怎么用稍微懂一点
23:58
these things work, I mean, you know, maybe self-driving cars, I could think of a few examples of
这些东西真的管用，我是说，你知道，也许 self-driving cars，我能想到几个例子。
24:02
like the AI is actually learning from watching us, but my vote doesn't really impact whether or not
就像 AI 实际上是在从观察我们中学习，但我的投票并不会真正影响是否
24:08
it's going to replace that profession someday. You know, and so I think with the job fearful,
它有一天会取代那个职业。你知道，所以我觉得对于那些对工作感到恐惧的人，
24:13
there's an opportunity to help them see like, Hey, you might be in the middle of a self-fulfilling
有机会帮助他们看到，嘿，你可能正处于一个自我实现的
24:17
prophecy here. Like, if you continue to push back against this, you might lose your job,
预言之中。比如，如果你继续抵制这件事，你可能会失去工作，
24:22
but it won't be because the AI replaced you because Joe who's willing to use AI will replace you,
但那不是因为 AI 取代了你，而是因为愿意用 AI 的 Joe 会取代你，
24:27
you know, so that's one way to address an L0. But another one, and this is actually six out of 10
你知道，所以这是解决 L0 的一种方式。但另一种，实际上有十分之六
24:33
people that we talked to. And I've seen this number in research hover around 60% in more than one
我们采访过的人。而且我在不止一个研究中看到这个数字徘徊在60%左右。
24:38
place are the quality disappointed. This is where I think every executive's ears should turn on.
而且，质量让人失望。我觉得每位高管的耳朵都应该竖起来。
24:43
They should lean forward in their seat and they should realize, do not dismiss these people.
他们应该身体前倾，意识到：不要忽视这些人。
24:47
If they are resistant to AI, there could be some very valid reasons why. And I met a person
如果他们抵制AI，可能有一些非常正当的理由。我遇到一个人
24:54
at a company who her complaint was, it's not good enough for what I have to produce from my work.
在一家公司，她的抱怨是：对我来说，要完成我的工作，它还不够好。
25:02
And she kind of showed me and she's just like, humans do this better. And it was a marketing role.
她给我看了一些东西，然后说：人类做得更好。那是一个营销岗位。
25:07
It was copy generation. It was some other stuff. And she was just right. And it may not stay true
那是 copy generation，还有一些其他的东西。她完全正确。而且这也许不会永远成立
25:12
forever, but no one had ever actually just no AI expert had ever just sat and listened to her.
但从来没有人——实际上没有任何AI专家——曾经坐下来听她说话。
25:18
And I walked away from that conversation with just a brand new perspective on how much value there
那次对话后，我获得了一个全新的视角，关于那里有多少价值
25:23
is to mine from the group of people who say, it's not ready to do this work yet. Or either it's not
就是从那些说“这工作还干不了”的人里面去挖掘。或者要么就是还没准备好
25:30
or they need better tools or better training, but you can't really do that until you listen first.
或者他们需要更好的工具或更好的培训，但你不先倾听，那你是做不到这些的。
25:37
And so, and I also don't think about it like a ladder. I don't think an L1 is better than an L0.
所以，我也不认为这是个梯子。我不觉得L1比L0更好。
25:42
And I don't think an L2 is better than an L1. Or an L, actually, I don't see it that way.
我也不觉得L2比L1更好。或者L——实际上，我不这么看。
25:49
I just see it as kind of a division within an organization for how different ways of thinking about
我只是把它看作组织内部的一种划分，关于如何以不同的方式去思考
25:55
the toolkit. And maybe one follow up question on that. I'm wondering, you mentioned maybe part of
这个工具包。然后也许对此有个追问。我在想，你提到也许部分
26:04
the stumbling block here is the quality dissolution or however you put it, you know, getting into these
这里的绊脚石是质量消解，或者随便你怎么说，你知道，就是去接触这些
26:11
tools. I sometimes I also wonder about the way in which like I would put myself into the category
工具的时候。我有时候也会想，像我自己会怎么把自己归入那个类别
26:18
of the AI people. Like, yeah, I'm building an product, right? How much of this is us providing AI
那些搞 AI 的人嘛。就像，对，我在做一个产品，对吧？这里面有多少是我们提供的 AI 只是成了他们又一样要加进 workflow 的工具，就像一个不同的工具，而不是真正能在他们 workflow 里起作用的东西。我的意思是，举个例子，我们现在在跟一个组织合作，他们有一整队翻译。我们基本上是用一组 digital agents，通过一个 agent harness 来帮助翻译。他们用的是现有工具，走 drafting、quality checking、post editing 这些流程，反复循环。但我们不会说，嘿，去这个你从来没用过的不同 interface，按 AI 的方式来做。那种 agents 的工作方式...
26:25
in a way that is just another thing that they have to add like a different tool that they have to add
这样一来，它就成了他们不得不额外加的东西，就像另一个非要加进工作流的工具，
26:32
in their workflow versus something that actually works in their workflow. And what I mean by that is,
而不是真正能在他们工作流中发挥作用的东西。我的意思是，
26:39
you know, if I'm to give an example, you know, we're working with an organization now,
比如说，我们现在正在跟一个机构合作，
26:45
they have teams of translators. We have essentially a team of digital agents that helps translate
他们有一支翻译团队。我们基本上有一组digital agents来帮助翻译，
26:53
with an agent harness. And they use existing tools. They go through the drafting and quality
通过一个agent harness。然后他们使用现有的工具。他们会经历起草和质量
26:59
checking and post editing. They do these cycles. But we don't actually say, hey, go to this
检查和post editing。他们做这些循环。但我们并不会直接说，嘿，去用这个
27:07
different interface that you've never used and do things the AI way. The sort of agents work
一个你从没用过的不同界面，然后按AI的方式做事。那种agents的工作方式。我们已经说过了，好吧，L zero，我们明白有些人真的可能永远不会用它，但至少在一段时间内不会。好吧，我们现在先别管他们。我们来看看L ones。丹尼尔，这就是你所说的那类人。你知道，就是那些——信不信由你——会说“你休想从我冰冷的手里夺走它”的人。我离不开这个。你可能觉得那一定是L three之类的吧。不不不，其实他们只是在使用它，但我们可以观察一下，我们并不真正理解那里的价值。我的意思是，他们不想失去它，但他们只是更快地处理邮件而已。
27:14
and then stuff pops up in the translation management system that they already use, right? And so what
然后，他们已经在用的 translation management system 里就会弹出一些东西，对吧？所以呢，
27:20
they see is, yes, there's change, right? But it's actually like allowing them to do the thing that
他们看到的是，是的，有变化，对吧？但这实际上是在让他们能够去做那些
27:28
they want to do with the tools that they're using in a way that actually they want to do that more.
他们想用他们正在用的工具去做的事情，而且其实他们更想那样做。
27:37
Now that may not always be possible. Like there may need to be a shift of like how people,
现在这不一定总是可能的。比如，可能需要有所转变，像是人们
27:42
you know, the interfaces that people use to do that. But I don't know. Do you have any experience
你懂的，就是人们用来做那些事的 interfaces。但我不确定，你有没有经验
27:47
with that? Like how much of this is we're asking people to use yet another tool? And they've already
在这方面？比如，这里面有多少是我们要求人们再去使用另一个工具？而他们已经
27:53
got tools that they like whether they're AI or not, right? And how much of it is the actual AI
有了他们喜欢的工具，不管是不是 AI 的，对吧？又有多少是实际的 AI
28:01
output? I don't know if you have any sense of that.
output？我不知道你对此有没有什么感觉。
28:04
No, I hear, I think I hear the sort of the spirit of the question. And so this is where I land,
不，我听到了，我觉得我听到了这个问题的核心精神。所以我的落脚点是，
28:10
you know, when it comes to, you know, how do we, who do we train to do what and what do we give them?
你知道，就是关于，我们怎么训练谁去做什么，以及我们给他们什么？
28:15
And how do we, you know, and honestly, at this point, I just feel like that is part of the
然后我们怎么，你知道，而且说实话，到这一步，我只是觉得那是
28:19
noise to me in all the conversations. The main thing that I'll trace us back to is executives
所有这些对话中噪音的一部分。我要追溯到的核心问题是，高管们
28:25
are complaining. We're spending too much on all of these licenses. We don't even understand what we're
在抱怨。我们在所有这些 licenses 上花了太多钱。我们甚至不明白我们
28:30
buying. I can't measure. I mean, yeah, I see this or that anecdotal piece of data, but I can't
买的是什么。我没法衡量。我是说，对，我看到这个或那个零散的数据，但我无法
28:35
measure like the real impact. Like what is the value of the, the, the, this investment compared to
衡量真正的影响。比如说，这个，这个，这个投资相比
28:40
the cost? And so we, we just say like, hey, whoa, let's zoom way out. Let's zoom way, way,
成本的价值是什么？所以我们就说，嘿，哇，让我们把视角拉远。让我们非常非常地
28:47
way, way, way, way out. And let's think about where we should actually focus. I mean, if we've
非常非常非常非常遥远。然后我们来想想真正应该把注意力放在哪里。我的意思是，既然我们已经说了，好的，L zero，我们知道有些人确实不会用它，也许永远不用，但至少在一段时间内不会用。好，我们现在先不考虑他们。我们有L ones。Daniel，这就是你在说的那类人。你知道，就是那些，呃，信不信由你，会说“你休想把它从我冰冷的手里抢走”、“没有它我活不下去”的人。你可能会觉得那必须是L three之类的吧。不不不，其实他们只是在使用它，但我们对那里的价值并不真正理解。我的意思是，他们不想失去它，但他们只是更快地处理邮件而已。
28:51
already said, okay, L zero, we understand some people just really aren't going to be using it
已经说了，好吧，L zero，我们理解有些人就是真的不会用它
28:56
maybe ever, but definitely for a while. Okay, let's not even think about them right now.
也许永远不会，但至少在一段时间内不会。好吧，我们现在先不想他们。
29:01
We got the L ones. This is kind of who you're talking about Daniel. It's, you know, it's the people
我们来看 L ones。这大概就是你说的那类人，Daniel。就是，你知道，就是那些人。
29:05
like, um, believe it or not, it's the people who would say you could pry it from my cold head
就像，嗯，信不信由你，就是那些会说“你可以从我冰冷的脑袋手里把它撬走”的人。
29:09
hands. I could not live without this. You think that must be like an L three or whatever. No, no,
没有这个我可活不了。
29:13
no, actually, it's just people using it, but we can look at that and we don't really understand
你以为那一定是像 L three 之类的玩意儿吧。
29:18
the value there. I mean, they, they don't want to lose it, but they're just doing an email faster
不不不，其实只是人们在用而已，但我们可以看看这个，我们并不真正理解其中的价值。
29:23
or they're interpreting technical documentation. But the company can't look at that and say,
或者他们在解读技术文档。但公司不能看着那些就说，
29:28
there's four million dollars. We, you know, saved or whatever. You know, it's just, so, so we say,
这里省了四百万美元之类的。你知道，就是这样，所以我们说，
29:33
that's noise too. That's going to happen. It's going to take care of itself. I wouldn't focus too
那也是噪音。那是会自然发生的，会自己解决。我不会太关注
29:37
much on that. When we talk about L two's, so at tier one, we have a, we have a process for
那个。当我们谈论 L2 的时候，在 tier one，我们有一个，我们有一个流程来
29:43
assessing and identifying quality L two candidates. Now, Daniel, I'm going to work my way backwards
评估和识别高质量的 L2 候选人。现在，Daniel，我要从这儿倒着推回去
29:48
to your actual question from here. So the idea is within L two, this is a person who you might
到你真正的问题。所以，在 L2 里，这个人是那种你可能会
29:53
think, Oh, great. How do you assess them? And so they have some aptitude ray. I know we really
想，哦，太好了。你怎么评估他们？他们有一些天赋，对吧？我知道我们其实真的
29:57
don't even kind of start with any sort of technical aptitude assessment. What we care most about is
根本不会从任何技术能力评估开始。我们最关心的是
30:02
company DNA. Do they understand the work in an uncanny way to the, to the company? Do they know which
公司DNA。他们是不是能以某种不可思议的方式理解工作，理解公司？他们知不知道哪个
30:08
cell of a spreadsheet to like fight over? Do they like, do they know how to deliver the work in a way
电子表格的单元格值得争来争去？他们是不是，知不知道怎么以一种方式交付工作
30:15
that the company wants to deliver? Is their work style uncanny to what we want? Like that is, is absolutely
公司想要交付的那种方式？他们的工作风格是不是和我们想要的惊人地一致？就像，这绝对是
30:22
necessary. Before we screen anyone for L two training candidacy. And here's the reason why,
必要的。在我们筛选任何人进入L2训练候选资格之前。原因如下，
30:28
right now, the wrong people are in the driver's seat. It's the, we call them the AI excited.
现在，错误的人坐在驾驶座上。就是，我们叫他们AI excited。
30:34
The AI excited are the ones who are getting all the attention in the company. They're running
AI excited是那些在公司里获得所有关注的人。他们跑在
30:38
on the hall, screaming words like nano banana and mythos class models. And everyone's just like,
走廊上，尖叫着像nano banana和mythos class models这样的词。然后每个人都说，
30:42
well, they must be the, they must be the person, you know, who should be building things when in
嗯，他们一定是那个，他们一定是那个人，你知道，应该去构建东西的人，当在...
30:46
reality, what we see, Daniel, is these people who maybe by definition are often distractable
现实是，Daniel，我们看到的是这些人，他们也许本身就经常容易分心，
30:55
and not very focused on the work. Don't know exactly how to align an agent to work in a way that
而且对工作不太专注。他们并不完全知道怎么 align 一个 agent，让工作的方式
31:03
is absolutely uncanny to what the smartest and best and most qualified semis inside of that function
与那个职能内部最聪明、最优秀、最有资质的 SMEs 所认为的
31:11
would call good or accurate or what we want done. And so we say we want to start with,
好的、准确的或者我们想要的结果绝对惊人地一致。所以我们说，我们要从某个人开始，
31:18
it doesn't need to be the Sme necessarily, but it needs to be someone who, who in the Venn diagram,
不一定是 SME，但必须是某个人，在 Venn diagram 中，
31:23
like can replicate the work the company needs done in the way they do it that honors the brand.
能够以尊重品牌的方式，复制公司需要完成的工作。
31:30
And has the aptitude to learn these models, the interest. And though, Daniel, we only want one of those
并且有学习这些 models 的能力和兴趣。而且，Daniel，我们只想要一个这样的人，
31:36
on each team, we find that it is not, it is not a one plus one equals two thing. Too many chefs
在每个团队里，我们发现这不是一加一等于二的事。厨师太多。
31:43
in the kitchen, if you have two L2s on a team, they are not necessarily as good as just an L2,
在厨房里，如果一个团队有两个L2，他们不一定比只有一个L2、几个L1和一些L0更好。我们希望确保每个L2，每个非技术构建者都有一个L3在伸手可及的地方，这样他们就可以复核工作。L2可以让它变得诡异，但L3可以让它变得 scalable、耐用，做出一个不会坏掉的东西，或者不违法，或者不违反治理政策。Daniel，这就是你的整个世界，对吧？但我们就是这么告诉别人的。这样想的另一个好处是，如果你能意识到我们其实只需要每个高绩效团队里有一个L2，那也意味着我们不用考虑那么多昂贵的许可证。而且我们可以集中培训。
31:49
a few L1s, some L0s. And we want to make sure every L2, every non-technical builder has an L3
几个L1，还有一些L0。
31:56
within arm's reach so that they can double check the work. The L2 can make it uncanny,
我们要确保每个L2，也就是每个非技术背景的构建者，身边都有一个触手可及的L3，这样他们就能复核工作。
32:01
but the L3 can make it scalable, durable, make a thing that won't break,
L2能做得让人叫绝，但L3能让它可扩展、耐用，做出一个不会坏、不会违法、也不会违反治理政策的东西。
32:06
or doesn't break laws, or violate governance policies. And Daniel, this is your whole world,
Daniel，这就是你的整个世界，对吧？
32:13
right? But so this is what we tell, and the other nice thing about thinking about it this way is,
但这就是我们对外说的，而且这样想的另一个好处是：如果你能明白我们其实只需要在每个高绩效团队里放一个L2，那也意味着我们不用考虑那么多昂贵的许可证。
32:19
if you can see what we really only want one L2 inside of each high performing team,
而且我们可以专注于培训、当保姆和手把手指导。
32:24
that also means we don't have to think about as many expensive licenses. And we can focus training
但再退一步说，如果你想想那...
32:30
on pre-qualified candidates. And so if we're just letting the L1s happen naturally, we're saying,
关于预先筛选的候选人。
32:37
okay, L0s will deal with them someday, but what can we learn from them now? And L2s are really the
所以，如果我们只是让L1自然发生，我们实际上是在说，
32:44
ones building the machines that we want to work in a way that honors the work, and think about
好吧，L0总有一天会处理它们，但我们现在能从它们身上学到什么？
32:50
how many tools have you used? It's like, who built this? Where did this come from? These things
而L2才是真正在建造这些机器的人，我们希望这些机器以对得起这些工作的方式运作。
32:54
tend to last for years or decades, and it better work right, you know? And it was particularly when
再想想你用过多少工具？
33:00
you're building something that works at scale. If you're listening to the practical AI podcast,
就像，这是谁造的？这东西是从哪来的？
33:07
I'm guessing that you value practicality, not just the hype around AI, which is why I think you
这些东西往往能用上好几年甚至几十年，所以它最好能正常工作，你明白吧？
33:13
should check out the Midwest AI Summit. This is an amazing event. I'm going to be there this year.
尤其当你在构建能够在 at scale 下运作的东西时。
33:19
It's happening October 15th in Indianapolis. This is an event like no other I've been to. There's
活动将于10月15日在Indianapolis举行。
33:26
actually an AI engineering lounge where for free you can go up and get expert advice from practitioners
这是我参加过的最特别的活动。
33:33
and get feedback on your architecture, your design, your agentic harness, whatever you're looking at,
那里实际上有一个AI engineering lounge，你可以免费向从业者请教专家建议。
33:39
you can get feedback on in real time in between amazing speakers that are on the main stage. So
并获得关于你的architecture、design、agentic harness等任何你正在研究内容的反馈。
33:45
don't miss this event. Again, October 15th in Indianapolis, and you can use the code practical AI20
在主舞台的精彩演讲之间，你可以实时得到反馈。
33:53
for 20% off. So go to MidwestAISummit.com and grab your ticket today, use code practical AI20
所以千万别错过这个活动。
34:01
for 20% off MidwestAISummit.com. Mike, you got me pretty interested, and I'm really thinking about
再说一次，10月15日在Indianapolis，使用代码practical AI20即可享受20%折扣。
34:12
this L2 process that you're describing. I want to rephrase a little bit in my own words and finish
所以今天就前往MidwestAISummit.com购票吧，使用代码practical AI20，在MidwestAISummit.com享受20%折扣。
34:22
with a question from there. It feels from what you're describing there that L2 has the knowledge
带着一个来自那里的问题。
34:31
of the value that the company is producing and locked in their heads. They may not be the L1
从你描述的来看，感觉 L2 把公司正在创造的那种价值的知识都锁在脑子里了。
34:39
that's running down the hallway screaming, hey, AI is cool, we should do it. But they're the ones
他们可能不是那种在走廊上跑来跑去大喊“嘿，AI 很酷，我们该试试”的 L1。
34:43
that are fundamentally and historically bringing that core value into the products and services
但他们是根本上、历史上一直把这种核心价值带进公司想要生产的产品和服务里的人。
34:49
the company's trying to produce. And that's kind of how it sounded to me. Whether or not they're
我听下来的感觉大概就是这样。
34:55
into AI, they have that. So it seems like you're trying to get kind of the L2s to be able to
不管他们对 AI 感不感兴趣，他们都有那个东西。
35:04
best use these capabilities to enhance their ability to drive value creation in the company.
所以看起来你是想让那些 L2 能最好地利用这些能力，去增强他们推动公司价值创造的能力。
35:11
Is that a good way to interpret that? And depending on what your answer is, can you kind of give me
这样理解对吗？
35:18
a course correction or can you kind of go down that path and explain it more because I'm pretty
是修正方向，还是你能沿着那条路再展开讲讲？我对那个想法特别感兴趣。
35:26
keen on that idea. Yeah, great. So you know an L2 is a good one when the SMEs in the area and
对，很好。你知道，一个 L2 好不好，就看该领域的 SMEs 对他们创建的那个 AI 工具——不管输出了什么——会不会抱怨。
35:34
don't complain about whatever the AI tool they created, like whatever its output is. You know
你知道，如果 SMEs 能去 align 一个 agent，让它生成的输出感觉跟我们做的那类工作很熟悉，不需要一大堆人盯着、手把手地教，那他们就是好的 L2 候选者。
35:41
you know that they are a good L2 candidate when they can align an agent so that when it creates
但再退一步说，如果你想想这对一个组织实际意味着什么——我马上给你举个例子，是我现在正在做的项目，我觉得能让你立刻看到价值。
35:54
outputs, it feels familiar to the type of work we do and doesn't require a whole bunch of
一个好的 L2 也不仅仅是
36:01
babysitting and hand holding. But also to back up a little bit, if you think about what that
我的意思是，他们不想失去它，但他们只是更快地处理邮件、当保姆和手把手带人。
36:08
actually means to an organization and in a minute I'll give you an example of a project I'm on
实际上对一个组织来说意味着什么，稍后我会举个例子，是我现在正在做的一个项目
36:13
right now that I think would help you see the value this instantly. A good L2 is also not only
我觉得能让你立刻看到它的价值。一个好的 L2 也不仅仅是
36:21
building tools that you know can sort of address like just repeatable work at scale,
构建工具，你知道的，就是能处理那种大规模重复性工作。
36:26
they're also converting tacit knowledge to documented process because once an AI model is aligned,
他们同时也在把隐性知识转化为文档化流程，因为一旦 AI model 被对齐了，
36:34
now you have documentation. Maybe it's in code, but it is documented. And so that's a big problem
你就有文档了。也许是以代码形式存在，但它确实是文档。
36:41
in like every industry right now. It's like oh you know the aging workforce and you know what are
所以这是现在每个行业都面临的大问题。
36:45
we going to do? We got don't get hit by bus guy over here and if you know if that's me if we
就像，哎呀，你知道的，劳动力老龄化，我们该怎么办？
36:51
lose them you know the plant shuts down you know kind of kind of thing. And so I think in my mind
我们这儿有那种“千万别被车撞”的关键人物，要是那个人没了，工厂就得停工，你懂那种感觉。
36:59
like that's how you know you have an L2 there that you don't have to worry about the tool they're
所以在我看来，这就是你判断自己达到 L2 的标准——你不用再担心他们构建的工具能不能运行得好。
37:04
building and whether or not it's it's going to work well. So but here's the other piece of it.
但还有另一部分。
37:08
And really like we exactly have leaned forward in their chair at this part of the conversation
而且真的，我们在这个对话的这部分确实是身体前倾了。
37:12
because when we say you know if you're wondering you know about the value of this investment,
因为当我们说，你知道，如果你在疑惑这个投资的价值，
37:22
let's stop thinking about this as AI work. And really you know like the work of yesterday
我们别把这看作是AI工作。而且真的，你知道，就像昨天的工作
37:28
is going to look like the work of tomorrow. Believe it or not the more things change the more they
会看起来像明天的工作。信不信由你，事情变化越多，它们越
37:31
stay the same. And I know it feels like everything is shifting beneath our feet, but the reality is
保持不变。我知道感觉就像脚下的一切都在移动，但现实是
37:36
we will be doing the same things before tomorrow. Whenever I talk to AI teams it feels like
我们明天之前还是会做同样的事情。每当我跟AI团队聊天时，感觉就像
37:41
what they want to build is agents what they want to build is tools. But if you actually go look
他们想构建的是agents，他们想构建的是tools。但如果你真的去看
37:46
inside of the work at companies they don't they're not thinking about AI. They're thinking about this
公司内部的工作，他们不——他们没在想AI。他们在想这个。
37:51
particular problem in front of them. So with one of my clients let's just say one of the top four
他们眼前的具体问题。
37:57
pharma companies in the world they were sitting on a stack of I can't remember how many
所以，我的一个客户——就说是全球四大制药公司之一吧——他们手头堆着一大摞文档，我记不清是几千份，需要转换，从原来的样子变成这样、变成这样。
38:01
thousand documents they needed converted to look from to look like this to look like this.
这个项目我不能说太多，但你知道，那是一笔四百万美元的活儿。
38:07
And I can't say too much more about that project, but you know it was a four million dollar job.
就是四百万美元的活儿。
38:12
It was a four million dollar job. They knew exactly how much it would cost to convert each one
他们很清楚转换每一份文档要花多少成本，而这需要我来做。
38:18
and it's requires me. And an L2 took a look at it and said this feels like a clawed skill.
然后一个 L2 看了一眼，说这感觉像是 Claude skill。
38:25
Had the clawed skill built within three hours. We drug one of their documents onto that skill
三个小时内就建好了这个 Claude skill。
38:33
out the other end squirted the almost exactly what we were hoping these things would look like
我们把其中一份文档拖到那个 skill 上，从另一头出来，几乎正好是我们希望这些东西变成的样子。
38:39
at the end of the process. You know of course everyone's jaw hit their desk like wait a minute
在流程最后，你懂的，所有人都惊掉下巴，像“等一下，
38:42
you're telling me that was going to be four million dollars. It needs to be done and now our
你是说那本来要花四百万美元？”这件事必须得做，而且现在我们有已经付过钱的 cloud，你知道，直接把它挂上去等着就行了，还能一千个同时跑，整件事几个小时就能完成，简直“什么鬼？”
38:47
clawed which we've already paid for you know you just drag them on and wait you can also run
嗯，这是可以衡量的，你知道。所以我们有点在推动大家往这个方向想，就是——
38:52
a thousand concurrently and like this whole thing can be done in hours like wait what
你不会靠人们花了多少 token 来判断这项投资的价值，你懂吧，你会发现它的价值是在你开始有意识地组建团队的时候，
38:57
um that is measurable you know and so we kind of push people to thinking toward like you know
团队里有几个有战略眼光的人，他们知道怎么发现 AI 机会，然后就直接去做。
39:04
you're not going to find out the value of this investment based on how many tokens people
你不会通过人们花了多少 tokens 来发现这项投资的价值
39:08
are spending or you know like you're gonna find it when you start intentionally forming teams
或者说，你知道，你会等到开始有意识地组建团队的时候才发觉
39:14
with a couple of strategic people in there who know how to spot an AI opportunity and just make
团队里有几个有战略眼光的人，他们知道怎么识别 AI 机会，然后直接去推动
39:21
the headache vanish we call it doing their laundry you know and so like this is where the real
头痛消失，我们称之为“帮他们洗衣服”，你知道的。
39:26
money is and this is where the real savings isn't Daniel I know you know about this because I've heard
所以这才是真正赚钱的地方，也是真正省钱的地方，Daniel。
39:30
you kind of almost complain about it like you know it's like this stuff's not fun um but it's like
我知道你懂这个，因为我听你几乎都在抱怨它，就像那种，你知道，这玩意儿不好玩，嗯，但这是实打实的工作。
39:35
it's real work uh Chris is that helpful it is you know that that helps frame it very well for me
呃，Chris，这有帮助吗？
39:41
I appreciate that yeah and I I would be curious of your take on this mic I think you're the right
有帮助的，你知道，这很好地帮我理清了思路，我很感激。
39:47
person to ask for a critique on some examples that I've been using even personally but I've been
是的，而且我很想听听你的看法，Mic。
39:54
I've been trying to use this example of you know how in like leadership retreats you they always
我觉得你是最适合点评的人，来点评一些我一直在用的例子，甚至是我自己也在用的例子。
40:00
used to show like the the f1 pit stop and how it advanced from like 20 seconds to two seconds
但我一直试着用这个例子，你知道，就像在领导力培训营里，他们以前总会展示F1的进站维修，以及它如何从20秒提升到2秒。
40:07
right and how that happened was like everybody knows their job in the pit lane right and one guy's
对，然后事情就是这样发生的，就像在pit lane里每个人都知道自己的职责，对吧，然后有个人
40:15
job is just to move the tire from here to there and that's all they do like that's their full
的工作就是把轮胎从这儿挪到那儿，然后他们就只干这个，就像那是他们的全部
40:19
responsibility and it almost seems like in some of these use cases that I'm seeing at least those
责任一样。而且在我看到的这些use cases里，至少那些
40:27
kind of very targeted jobs or outcomes right but like you're talking about this document from here
非常针对性的工作或结果，对吧。但就像你说的，这份文档从这儿
40:36
to there right that that needs to be done and that is is maybe a good candidate for um however
到那儿，对吧，需要被完成，而这件事也许是一个很好的候选，嗯，不管你
40:44
you frame it a use of AI an agent to take care of it however you word that like that's a that's a
怎么去界定它，用AI或者一个agent来处理它，不管你怎么说，这就像是一个
40:51
thing and it kind of in my mind it then it doesn't remove the human but it it actually kind of
东西。而且在我看来，它并没有取代人类，反而实际上有点
41:00
elevates in some cases the dignity of the human from being the person's like all you're going to do
在某些情况下提升了人类的尊严，而不是让一个人觉得，你只需要做
41:07
every day is move the tire from here to there or to you know do this task and certainly I recognize
每天就是把轮胎从这儿搬到那儿，或者做这个那个任务，我当然也承认，确实有些工作会发生转移，而且人们会为此挣扎。但现在的关键在于，你不再是把你的团队框定为——嘿，别越界，只管把轮胎从这儿搬到那儿——而是真正能够在这些单个任务中利用AI，你开始进入 orchestrator 模式，或者 team principal、strategist 模式，真正去思考结果：我想要的结果是什么？与之相关的各个要素是什么？其中很多都可以是AI完成的单个任务。我不知道这么说是不是有点道理，你觉得呢？
41:13
there is legitimate you know jobs will shift right but um and you know people will will struggle
确实，你知道，工作会发生转移，对吧，但嗯，你知道，人们会为此挣扎
41:22
around that but it seems like now kind of the human you're not framing your team of humans as hey
围绕这些变化。但现在看来，某种程度上，你不再把你的团队框定成“嘿，
41:29
don't go don't get out of your lane just move the tire from here to there to actually being able
别乱跑，别越界，只把轮胎从这儿搬到那儿”，而是真正能够去...
41:35
to leverage AI in these individual tasks and you kind of coming into the orchestrator mode or the
利用 AI 来完成这些单独的任务，然后你有点像进入 orchestrator mode、team principle 或 strategist mode，真正去思考结果——嗯，我想要的结果是什么？与之相关的有哪些具体的事项？其中很多都可以是 AI 能单独完成的。
41:43
team principle or the the strategist mode and actually thinking about outcomes well what what is
我不知道这是否真的有道理。
41:48
the outcome I want here and what are the individual things associated with it many of those which
根据研究，我发现，嗯，颠覆这种事，事后回想起来，适应起来并没有你以为的那么难，而且你适应得也比想象中快。
41:53
can be individual tasks that that AI accomplishes I don't know if that that rings true at all I've
所以这其实是有据可查的事实，但感觉从来不是那样。
41:59
been trying to think about um yeah how uh people are very used to thinking now I I think or many
我一直在试着思考，嗯，对，人们现在很习惯于思考，我觉得，或者说很多人
42:08
people are very used to thinking of the one-to-one interaction between a human and uh AI tool let's say
很习惯于思考人类和 AI 工具之间的一对一互动，比如说
42:15
or chat interface and maybe less familiar with this or or familiar with this way of thinking of
或者聊天界面，可能对这种思考方式不太熟悉，或者熟悉这种思考方式
42:23
maybe one human is actually aided by multiple different instantiations or manifestations of AI that
也许一个人实际上是由多个不同的 AI 实例或表现形式协助的，这些 AI
42:31
help them work towards towards outcomes but I don't know if any critique on that rambling example of
帮助他们朝着结果努力，但我不确定对那个东拉西扯的例子有什么批评
42:38
kind of the the the F one pit stop and some of these tasks um you know what are the tasks in your
有点像 F1 维修站那种，以及其中一些任务，嗯，你知道，你的
42:45
in your uh pit box that need to be accomplished and what what of those are good candidates for AI
在你的维修区里需要完成的任务是什么，哪些是 AI 的好候选
42:52
how do I think about managing the set of AI workers or tasks or whatever you whatever you
我该如何思考管理这一组 AI 工作者或任务，或者无论你怎么称呼它们
42:58
whatever you might frame it yeah one of the one of the things that popped in my head while I was
不管你怎么去框定它吧，嗯，我脑子里冒出来的一个想法，当我正在
43:02
listening to Daniel which I always enjoy doing is um yeah I'm very often thrown into rooms with
听Daniel讲话——我一直都很喜欢听他讲——就是，嗯，对，我经常被扔进一个房间，里面是
43:09
people who you know live on a spectrum of you know attitudes and um you know one of the big ones
那些人，你知道，持有各种态度的人。嗯，其中一个大问题是
43:16
is just like all the fear wrapped up in this and um I I kind of always open with hey guess what if
就是所有跟这有关的恐惧。嗯，我我基本上总会开口说：嘿，你猜怎么着，如果
43:22
you're worried about losing your job to I think there's thunder in the background I don't know if
你担心自己的工作会被……哦，我背后好像有雷声，我不确定是不是
43:27
yeah it's definitely it's thunder stormy yeah it's giving it now for it's giving the answer extra
对，绝对是雷声，暴风雨那种。嗯，它这下可给这个回答额外增加了
43:33
trauma right there yeah that's the fear no really you know I when I go in a room and I know there are
创伤效果。对，这就是那种恐惧。不，说真的，你知道，当我走进一个房间，我知道里面
43:38
people who who are dwelling on that hung up on that I I mean you know I just open with guess what
有人一直在想这个、纠结这个。我我的意思是，你知道，我开口就是：你猜怎么着
43:44
you are losing your job you like your job is going to change and that's true for all of us always
你会失去你的工作，你的工作会改变，这对我们所有人来说一直都是如此。
43:50
whether or not AI was invented or not like I don't have any careers I've had and I think the average
不管AI有没有被发明，就像我自己，我换过好几份工作，而且我觉得平均每个人
43:55
person has seven and even if you stuck with one your job would change year over year in time and
会有七份工作，即使你一直做同一份工作，它也会年复一年地变化。
44:01
if if you're if someone is uncomfortable with the concept of change guess what you're not cut out
如果你对“变化”这个观念感到不舒服，那你听好了，你就不适合
44:06
with the for the workforce I mean like the reality is um the reality is like if if my daughter was
职场。我的意思是，现实是……嗯，现实是，就像如果我女儿
44:12
scared there's a monster under her bed I wouldn't go and say there's no monster in her you're
害怕床底下有怪物，我不会走过去说“床底下没有怪物，你
44:16
bad I'd say you're stronger than a monster like and monsters aren't real and you know like um you
不乖。”我会说“你比怪物更强”，而且怪物不是真的，然后你知道，嗯，你
44:22
know and you know it's kind of like that in this job is like hey um uh adaptor die and I don't
知道吧。工作这件事其实就是这样——嘿，要么适应，要么灭亡，然后我就……
44:28
think you're gonna die and and and maybe some of this it might sound a little heartless but it comes
你觉得你会死，而且，而且——也许听起来有点无情，但研究得出的结论是：嗯，颠覆总是——事后看来，适应起来并没有你原本想的那么难，而且你适应的速度也比自己预期的要快。所以这就是，你知道，有据可查的事实，但人永远不会那样感觉。嗯，我觉得我就是那个怪人，真的很喜欢彻底颠覆自己的职业生涯，然后去尝试新东西，你知道吧？我就是——我已经这么干过很多次了，而且我几乎享受其中。嗯，不过后来我想，听你说到的那部分，Daniel，对，我已经回应了，但还要提醒一下，还有什么来着？对，我觉得就是那个想法——变化的一个要素，我觉得是……
44:33
out of the research is that um disruption is always it turns out in hindsight it was not as hard
嗯，我觉得我就是个怪人，真的很喜欢那种把自己的职业生涯连根拔起、然后就去试试的想法。
44:42
to adapt to as you thought it was going to be and you adapt more quickly than you thought you could
但再往回说一点，如果你想想适应它的那个过程——你原本以为会是这样，结果你适应得比你想象的要快。
44:49
and so this is just you know documented um truth and so but it never feels that way um I think I'm
所以这就是那种，你懂的，有据可查的事实，但感觉从来不是那样。嗯，我觉得我就是那个怪人，真的很喜欢那种彻底抛弃整个职业生涯然后去尝试一下的想法。
44:56
just the weird bird who uh really likes the idea of like uprooting my entire career and just trying
就是这个怪人，呃，真的很喜欢那种彻底抛弃我整个职业生涯、然后只是试试的想法
45:05
something new you know like I just get I just have done that so many times and I almost enjoy it um
某种新东西，你知道，就是……我就是做过太多次了，甚至有点享受，嗯。
45:11
so but then I think the rest of what I heard you talk about Daniel yeah I addressed that but like
所以，但后来我想，Daniel，我听到你讲的其余部分，对，我提到了，但就是……
45:17
reminding like what else yeah I think it's this idea of one element of the change I think is
提醒一下，还有什么？对，我觉得这是变化的一个要素，我认为是……
45:25
is understanding that maybe your your position which might be consumed by this task right now
就是理解到，也许你现在的职位可能完全被这个任务占据，但它不只是来上班做这个任务，而是会提升到一种以结果为导向的 creative orchestration mode，你实际上是在编排需要完成的工作。就像你说的，同样的职能、同样的角色、同样的结果都需要在你的业务中达成，对吧？但是嗯，对，这确实需要不同层次的思考——要想“我该怎么编排这些事情来达成结果”，而不是“我怎么做这个任务”，因为我知道怎么做，我知道怎么把任务搞定，对吧？对对，我明白你的意思。嗯，也许我之所以很难直接快速回答这个问题，部分原因是我脑子里一直在跳来跳去。
45:34
might not be just come into work and do this task but it it sort of elevates more to an outcome
可能不只是来上班然后做这个任务，而是它有点儿更提升到一种成果层面。
45:41
kind of creative orchestration mode where you're actually orchestrating work that needs to be accomplished
一种创意的 orchestration 模式，你实际上是在编排需要完成的工作。
45:48
like you say the same functions the same roles like the same outcomes need to be accomplished in your
就像你说，同样的职能，同样的角色，比如相同的结果也需要在你的……
45:54
in your business right but um but yeah it's it does take a different level of thinking to think
在你的业务中，对吧？但是嗯，对，它确实需要不同层次的思考来想……
46:00
about well how do I orchestrate these things to get the outcomes versus how do I do this task because
关于，嗯，我如何 orchestrate 这些东西来达成结果，而不是我怎么做这个任务，因为……
46:06
I know how to do the I know how to get the task done right yeah yeah I hear you um maybe maybe
我知道怎么做，也知道怎么把任务做好，对对，我听到你的话了，嗯，也许吧，也许吧。
46:12
part of why I struggle with just just rapid firing and answer to this is my mind darts back and forth
我为什么难以直接快速回答这个问题，部分原因是我的思绪在来回跳跃。
46:18
from the hundreds of like work environments in situations yeah I've had to kind of inspect and
从数百种工作环境和情境中，嗯，我确实得去审视并……
46:24
solution for uh let me let me frame let me frame it for a moment because I I think I see where Dan's
解决方案，呃，让我先框定一下，因为我觉得我明白丹的
46:30
going and and I think you are the right person to answer this and that would be you know if you
意思，而且我认为你是回答这个问题的合适人选，就是说，你知道，如果你
46:36
go back to that analogy of the f1 pit stop that he was describing and the nature of the jobs that
回到他描述的那个 F1 进站的比喻，以及那里每个人所做工作的性质
46:42
everyone had there and you're kind of looking forward and so you know we're kind of what is our
你在那里，然后你在展望未来，所以你知道我们就是说我们的
46:48
expectation of the future and you know at least I think I think one of the things that probably the
未来期望是什么，而且至少我觉得我们三个人可能
46:54
three of us would agree on at some level is the fact that the human that's in that process
在某种程度上都会同意的是，那个过程中的人
47:01
it may uh may have these AI agents that are able to take over some of those very specific jobs
可能，呃，可能会有 AI agents 能够接管其中一些非常具体的工作
47:07
along the way and you're almost becoming the pit stop manager or orchestrator overall so you're
一路走来，你几乎变成了整个维修站的管理者或统筹者，所以你仍然在做维修站的工作，因为那是你们组织创造价值的地方，但人的本质可能会改变，以便做得更好、更快，并且不断成长，而不是被踢出去——你知道，不是失去工作，而是换了一种工作，在很多方面反而更有价值。你能稍微谈谈，对于那些正在调整自己维修站角色的员工来说，那个未来会是什么样子吗？也许，你知道，可能是上升到 abstraction layer 高一点的位置，去掌控整个流程，在那里他们作为人类是有价值的，同时又充分利用了 agents 的优势。你有什么想法，当你带着公司经历这些时……
47:12
still doing the pit stop because that's the value of what your organization's doing but the nature
还在做 pit stop，因为那是你们组织所做的事情的价值所在。
47:17
of the humans may change to better do it to do it faster and to grow rather than be kicked out of
但人类的本质可能会改变，以便做得更好、更快，并且成长，而不是被踢出去。
47:24
that you know rather than the loss of job it's a change of job that's actually more valuable in a lot
你知道，与其说是失去工作，不如说是工作方式的转变，这在很多方面实际上更有价值。
47:29
of ways could you talk a little bit about what that future might look like for those individual
你能稍微谈谈，对于那些正在调整自己的 pit stop 工作的员工来说，那个未来会是什么样的吗？
47:36
employees that are adjusting their pit stop job it may be you know maybe moving a little higher
可能是，你知道，也许在 abstraction layer 上再往上移一点，去掌控整个流程，在那里他们作为人类是有价值的，而且……
47:43
in the abstraction layer to owning that whole process where they are valuable as humans and yet
在 abstraction layer 中，到拥有整个流程，让他们作为人类而有价值，然而当然，过去你懂的，纠结于过去，但还有未来，以及我们在脑海中编造的所有关于事情会如何顺利发展的故事——那些故事不会成真。其中可能有些元素是真的，当然我不是说我们不应该创新，不应该寻找新的做事方式，我只是说我们经常纠结于未来那些永远不会发生的情况，而当下有一些动态正在发生，我们需要深入挖掘并思考它们在当下如何重要——我真的很喜欢这个视角，在我们即将结束时，Mike，嗯，在经历了这些不同熟练度水平之后，我也知道...
47:49
they're taking full advantage of of the agents any thoughts like as you take companies through the
他们在充分利用agents，你们怎么看？比如你带着公司从过去——当然，你知道，我们总纠结于过去——但也要看未来，还有我们脑子里讲的那些故事，关于事情可能会怎么顺利发展，但那不会发生；那些故事里可能有些是真的。当然，我不是说我们不该创新、不该找新办法，我只是说我们常常纠结于一些永远不会发生的未来事件，而同时又有些正在发生的动态，我们需要去深挖，想想它们当下有多重要。我真的很喜欢这个视角，Mike，在我们快要结束的时候，嗯，在经历了这些不同层次的能力水平之后，我也知道……
47:54
process how how you would do that and what your expectation of the future will be um on how that
过程是怎样的，你会怎么做，你对未来的预期是什么，嗯，关于它会如何发展。
48:01
progresses I don't I don't think you're gonna like my answer it's all good I decided to stop worrying
发展——我不觉得你会喜欢我的答案，没关系，我决定不再担心了。
48:08
about it I don't even think about it anymore like and maybe maybe it's just because I don't fully
关于这个，我甚至不再去想它了。也许，也许只是因为我没有完全
48:13
understand the question I think I do I spent probably two years inside of all these organizations
理解这个问题，我觉得我理解了。我大概在这些组织内部待了两年，
48:20
trying to like lead and organize and you know um an implement uh enablement and activation campaigns
试图去领导、组织，你知道，嗯，实施 enablement 和 activation campaigns。
48:29
and in the end it just kind of felt like I was just watching water run down a river it was gonna
最后感觉就像我看着水顺着河流流下去，它会
48:35
go down the direction it was gonna go the river is it's just winding the way it winds and and I
朝着它该去的方向流走。河流就是沿着它蜿蜒的路径蜿蜒着。而且我
48:42
think I'm always just searching for like where can I actually make an impact where can I actually
觉得我一直在寻找，我到底能在哪里真正产生影响，我到底能在哪里……
48:47
activate change in an organization that is measurable and and something that we're all glad we did
在组织中推动可衡量的变革，而且是我们做完之后都庆幸做了的事。
48:53
after we're done doing it and you know when I come in and you know and we try to just you know
等我们做完了，你知道，当我进来的时候，我们就是试着，你懂的，
48:58
really analyze and think through you know like well what's the impact of this gonna be after we
真正去分析、想清楚，你知道，比如，嗯，我们做了之后会有什么影响，
49:02
do that and you know what's it in the end like what what it's gonna be is what it's gonna be and
做了之后，你知道，最后会是什么样？该怎样就怎样，然后
49:07
people tend to adapt to these tools very quickly once they've used them once or twice and seeing
人们往往会很快适应这些工具，只要他们用过一两次，看到了
49:12
the result and so in my mind it's kind of like I'm gonna do everything I can to get them to do that
结果，所以在我看来，就像是，我会尽一切努力让他们去用，
49:16
but beyond that if I can't get them to I don't care what I care about is can I find that L2
但除此之外，如果我没办法让他们用，我也不在乎，我在乎的是我能不能找到那个 L2，
49:22
can we get them equipped and activated and and and synergizing that's a better word than that um
我们能不能让他们准备好、激活起来，并且，并且，协同起来——那是个更好的词，嗯。
49:31
effectively cooperating and contributing inside of their team uh in a way that like I want to know
有效地在团队内部协作和贡献，嗯，以一种方式，我想知道
49:39
the difference before and after and and so it's not just that you know maybe the pit crew thing was
前后的差异，而且，所以这不仅仅是因为，你知道，也许 pit crew 那件事
49:46
a distraction for me because I was I was focused on like well it's faster now and it drives me nuts
让我分心，因为我当时只关注着，哦，现在更快了，这让我抓狂
49:51
when people say I want things faster it's your one we say like faster is not always better especially
当人们说“我想要更快”时，我们常说，更快并不总是更好，尤其是
49:55
when it's it's it's a it's a system with a whole bunch of parts and you've just created whiplash
当它是一个有很多部件的系统，你只是制造了冲击
50:01
and angst for everything around that fast piece you know like nothing else is ready to go that fast
和焦虑，给那个快速部分周围的一切，你知道，其他东西都没准备好那么快
50:07
so that's not necessarily better cheaper sometimes that doesn't even matter believe it or not a lot
所以那不一定更好，更便宜有时候也不重要，信不信由你，很多
50:12
of the companies that's that's not like the main thing we're talking about like but new emergent
公司，那其实不是我们讨论的重点，就像，但新的 emergent
50:17
types of work like that is interesting so what can we do now that human minds just really couldn't
像这类工作挺有意思的。
50:24
do well before and and equipping these language models inside of like really clever harnesses
那我们现在能做到哪些以前单靠人脑真的做不好的事？
50:29
so against kind of like Daniel's world you know like whoa uh new kinds of work um and so what's
还有把这些 language models 装进那种特别聪明的 harnesses 里。
50:36
that mean for you know the product or this you know department or function or whatever it is I mean um
所以跟 Daniel's world 那种东西对照起来，你知道，就是“哇，新类型的工作”。
50:42
so um so I guess I put that that whole concept just right outside the periphery of what I can control
那这对你的产品，或者你的部门、职能什么的，意味着什么呢？
50:51
and so therefore not something I worry about and I'm sort of done thinking about yeah that that
所以我觉得我就是把整个概念放在我能控制的范围之外。
50:58
makes sense I actually do like that answer I did I did to uh I think there there there are a lot of
所以它不是我担心的事，我也已经不再去想它了。
51:05
people and maybe maybe this is um I don't know a little bit too personal but but certainly like a
嗯，有道理。
51:13
mode that I think all of us as humans get in is not being present in the moment and thinking about
我觉得我们所有人作为人类会陷入的那种状态，就是没有活在当下，而是在想过去——你知道，沉湎于过去——同时也在想未来，想我们脑子里编造的各种关于事情会如何顺利展开的故事，但这些故事其实不会成真，其中也许有一部分是真的。当然，我不是说我们不应该创新、不应该寻找新的做事方式，我只是说我们常常纠结于未来那些永远不会发生的可能性，而有些正在发生的动态才是我们需要深入探讨和思考的，去想想它们在当下究竟有多重要。我真的很喜欢这个视角，在我们快要结束的时候，Mike，在经历了这些不同水平的熟练度之后，而且我也知道……
51:20
of course the past you know dwelling on that but also the future and the all the stories that we
当然，过去，你知道，纠结于那个，但还有未来，以及我们
51:26
tell in our head about how things might go right which won't there there may be elements of that
在脑子里讲的关于事情可能会如何顺利发展的故事，但不会顺利——那里可能有某些元素
51:33
that are true and it's not of course I don't mean that we shouldn't innovate and look at new ways
是真的，而且这并不是说，当然，我不是说我们不应该创新、不应该寻找新方法。
51:38
of doing things I just mean we often dwell on eventualities in the future that will that will never
做事的方式，我的意思是，我们常常纠结于未来那些永远不会发生的情况，而实际上有些正在发生的动态，我们需要深入挖掘并思考它们在当下有多重要。我真的很喜欢这个视角，在我们即将结束时，Mike，嗯，在接触了这些不同层次的专业技能之后，而且我也知道……
51:44
take take place and there's dynamics that are happening that we need to dig into and think about
会发生一些事情，其中有一些动态变化是我们需要深入挖掘和思考的，看看它们在当下到底意味着什么。我真的很喜欢这个视角，在我们快要结束的时候，Mike，在经历了这些不同熟练程度的层面之后，我也知道——
51:50
how they matter in in the moment which I I really I really like that that perspective as as we close
它们在当下为何重要，这一点我真的很喜欢，这个视角，在我们收尾的时候。
51:56
out here Mike um after kind of working across these different levels of proficiency and I know also
在这里，Mike，嗯，在跨这些不同熟练程度的工作之后，我也知道——
52:05
you're thinking about structured ways of thinking about the the actual things that can be done by AI
你在想的是用一种结构化的方式，去思考AI实际能做到的事情，
52:11
the outcomes that sort of thing what what's on your mind you know today as you're going into your
以及这些结果什么的。那你今天去开下一个会之前，脑子里在想什么？
52:18
next meetings as like the the the kind of challenges or the things maybe like you had done this work
比如说那些挑战，或者你做过的工作——把所有这些研究和AI proficiencies上的工作都梳理一遍，对吧？
52:24
to parse through all of these this research and and um work on AI proficiencies right um what's that
那下一个方向是什么？或者你在想，有没有那么一个领域，你觉得自己还没有完全搞定，
52:32
next kind of or is there a next kind of area in your mind where you're like I don't I don't totally
但你真的特别好奇，想再深入挖一挖，看看能不能理出一些思路来？
52:39
have a grip around this bit of it yet but I'm really curious to dig in more and see if I can see if
那在我们结束之前，你脑子里有什么想法吗？
52:46
I can parse through some of it anything that comes to your mind as as we close out here yeah I think
嗯，我觉得最让我兴奋的，作为一个想法或者一个口号，当它...
52:52
I think the thing that's been most exciting to me as like an idea or like a rallying cry when it
我觉得最让我兴奋的，作为一个想法或者一个口号，就是——你知道，他们的精力在哪儿，他们的势头在哪儿。然后嗯，最近我有一个想法，而且我一次又一次看到它得到回报，那就是在大多数这些大型组织内部——我现在说的是大企业——的现实是，每个人基本上都有一套工具。比如如果你在，呃，像 Procter & Gamble 这样的公司，你大概能接触到一两个或者三个 AI 工具，但它们之间配合不好，也不一定真的好用。你很容易试着去用它们，然后发现它对你需要完成的那件事来说效果并不怎么好，然后就放弃了。而且我觉得……
52:58
comes to the rank and file inside of organizations or leaders who look at me and say like what's you
说到组织里的基层员工，或者那些看着我说“他们的精力在哪？他们的势头在哪？”的领导——嗯，我最近有一个想法，而且我反复看到它奏效——在大多数这种大型组织内部，其实我主要是指大企业——每个人都已经有了一个工具包。比如，如果你是Eddie，一个在Procter & Gamble打卡上班的员工，你大概能接触到一两个或三个AI tools，但它们之间配合不好，也不一定好用。你很容易试一下，然后发现它对你需要完成的事情不太管用，就放弃了。然后我觉得……
53:03
know like where is their energy where is their momentum like what you know um one one idea that I've
你知道，就是他们的精力在哪儿，他们的动力在哪儿？
53:11
kind of had lately and I've seen payoff over and over and over is the reality inside of most of
嗯，我最近有个想法，而且我一次次看到它得到回报。
53:17
these massive organizations it's mostly I'm talking about big business now um is that everyone's
在这些大型组织内部——我现在主要说的是大企业——现实是，
53:23
kind of got a toolkit in place like most if you're you know uh Eddie punch clock proctor and gamble
每个人都有一套 toolkit 放在那儿。
53:31
you probably have access to one two or three AI tools and they don't work well together and they
比如，如果你在 Procter & Gamble 这样的公司工作，
53:37
don't necessarily work well and it is very easy to try to use them and just see it doesn't work
你大概能用到一两个或三个 AI tools，但它们的配合并不好，也未必好用。
53:43
you know super well for the thing that you need to get done and to give up on it and I think like
而且你很容易试一下，发现它帮你解决不了需要做的事，然后就放弃了。
53:49
the thing I'm realizing is that there is massive massive value in the people who are willing
我意识到的是，那些愿意的人身上有巨大巨大的价值。
53:58
to lean against the brick wall and push and push and push and you what you believe it or not
去靠着那堵砖墙，一直推、一直推、一直推——你知道吗，信不信由你。
54:04
you'll start to find ways to use these tools that are are hugely transformative
你会开始找到这些工具的使用方法，它们具有巨大的变革性。
54:08
informative in spite of the fact that they're so burdened by necessary governance and you know rules
富有启发性，尽管它们被必要的治理和你知道的规则所束缚。
54:15
and restrictions and why can't we turn that connector on and why can't you know but um you know
还有各种限制——为什么我们不能打开那个connector？为什么不能？你知道的，但是呢，嗯，你知道的。
54:21
when quad tells you something's not possible you know ask it to get creative and you know and
当quad告诉你某件事不可能的时候，你知道的，让它发挥创意，你知道的，还有。
54:27
or um you know think through you know alternate approaches I think creative solutioning is going
或者，嗯，你知道的，想想其他方法。我认为创造性的解决方案将会。
54:33
to be really really valuable over the next uh two years three four five years before you know
在接下来的呃两年、三年、四年、五年里变得非常非常有价值——在你意识到之前。
54:41
all the wrinkles are ironed out and who knows you know terminators or whatever whatever comes after
所有的麻烦都解决了，谁知道呢，你知道的，终结者什么的，或者之后还会出现什么。
54:45
that um but um I think the yeah the thing Daniel that like I've been preaching lately you know with
那个，嗯，但是，嗯，我觉得，是的，Daniel，我最近一直在宣扬的东西，你知道的，和我信任的同事们，嗯，还有不同的领导者和组织，就是，嗯，尽你所能去鼓励，嗯，呃，那种思考和行为，比如说，好吧，我知道他们并不完美，但要想办法完成你能完成的事情，嗯。
54:53
like my trusted colleagues and um with different leaders and organizations is like um do your best
所以，是的，我觉得这是一个很好的结束时的号召。
54:59
to to encourage um uh that type of thinking and behavior like okay I know they aren't perfect
感谢你再次加入我们，Mike，嗯，我们期待你再次上节目，呃，希望不久之后能再次向你学习，嗯。
55:06
figure out what you can get done though um so yeah that's that's I think a great
但是，是的，感谢你抽出时间，这是一次很棒的对话，谢谢。
55:11
following rallying cry to to end with appreciate you joining us again Mike um we look forward to
好了，这就是我们的节目。
55:18
having you having you on again uh to to learn from you in hopefully not too long again um but yeah
我觉得，再次请你来，希望能很快再向你学习——嗯，就这样。
55:26
appreciate you taking time it's been a great conversation thank you all right that's our show
感谢你抽出时间，聊得非常愉快，谢谢。好了，这就是我们的节目。
55:38
for this week if you haven't checked out our website head to practical a i dot f m and be sure to
这周，如果你还没看过我们的网站，去 practical AI dot fm 看看吧。
55:43
connect with us on linkedin x or blue sky you'll see us posting insights related to the latest
记得在 LinkedIn、X 或 Blue Sky 上关注我们。
55:49
AI developments and we would love for you to join the conversation thanks to our partner prediction
你会看到我们发布关于最新 AI 发展的见解。
55:54
guard for providing operational support for the show check them out at prediction guard dot com also
我们很希望你能加入对话。
56:00
thanks to break master cylinder for the beats and to you for listening that's all for now
感谢我们的合作伙伴 prediction guard 为节目提供运营支持。
56:04
but you'll hear from us again next week
去 prediction guard dot com 看看吧。