Molly Graham Urges Tech Workers to Stop Offloading Core Craft to AI

Molly Graham 呼吁科技从业者停止将核心技艺转嫁给 AI 在缺乏严格人工把关的情况下将复杂工作委托给 AI 模型注定行不通，因为算法更像是未经核验的初级实习生，而非自主权威。 Molly Graham 重温了其经典的“交出你的乐高积木”（Give Away Your Legos）框架，阐释了向 AI 分配任务与向人类移交职责在本质上的不同：将工作交给人类可以释放心智空间，而委托给 AI 则如同管理一名新手实习生，监督、核实和问责的全部重担依然落在人类员工身上。这种机制，加上企业界被夸大的恐惧叙事以及专业技能边界的变动，已导致科技行业的职业倦怠率上升至 55%，并在那些被迫从亲力亲为的“划桨者”转变为管理型“掌舵者”的工程师和设计师中引发了真正的失落与痛苦。不过，受访员工中有半数在获得自主权时表现出色，Graham 认为整个行业正处于“缓慢起飞”阶段，职业将会转型而非消失。要想脱颖而出，员工与管理者必须拒绝外包核心的人类判断力与品味，为失去的传统技艺举行“葬礼”，严格自律以避免交付“AI 劣质产物”（AI slop），并依靠充满同理心的管理引导团队度过动荡期。 在未增加薪酬的情况下产出期望不断提高，加之企业在激进使用与成本控制之间反复摇摆，导致科技从业者的职业倦怠率从 2025 年的 44% 飙升至 2026 年的 55%。 (29:18) 将 AI 视作超级智能而非实习生，已导致代码返工率激增约 8 倍并引发更多安全事件，因为未经审查的粗制产物将认知负担转嫁到了下游。 (35:07) 将任务委托给 AI 并不能减轻心理负担：与将工作移交给人类同事不同，管理自主代理时，所有的认知负荷和责任依然完全留在人类操作员身上。 (42:02) 行业指标表明当前处于“第一局”的“缓慢起飞”阶段，而非即刻的劳动力替代，对于适应 AI 工作流的员工而言，从新手到专家的距离依然非常短。 (69:16)

Molly Graham reassesses her foundational career advice to "give away your Legos," arguing that delegating tasks to artificial intelligence fundamentally differs from handing work to colleagues and requires professionals to fiercely protect their core craft and judgment. Rather than succumbing to narratives of immediate obsolescence, she stresses that navigating this transition requires acknowledging widespread burnout and allowing workers space to grieve shifting professional identities. Delegating to Robots Versus Humans (42:02) Graham explains that her original hypergrowth framework—handing responsibilities entirely to another person and walking away—breaks down when delegating to AI models. Unlike seasoned colleagues who operate autonomously, current AI systems behave like unvetted junior interns that require continuous context, supervision, prompt adjustments, and verification. Delegating to models fails to deliver mental liberation because oversight cannot be surrendered. Because of this dynamic, individual contributors are forced into management roles managing swarms of synthetic agents without the corresponding training. Treating AI as an infallible authority leads workers to "copy, paste, and send" unedited outputs, flooding organizations with low-quality "AI slop." Graham cites engineering data indicating that while raw code production has increased, the volume of rewritten lines of code has jumped roughly eightfold alongside an increase in security incidents. Professional Grief and the Burnout Surge (19:27) The rapid automation of routine execution has destabilized craft identities across tech disciplines, creating deep, unaddressed grief. Lenny Rachitsky notes that software engineering has shifted from hands-on "rowing"—the flow state of writing code directly—to "steering" agents and reviewing automated runs. Many craftspeople actively dislike steering, while designers face comparable frustration as generative tools enable non-designers to produce crude mockups that neglect deliberate product craftsmanship. This loss of craft intersects with severe workforce fatigue. Rachitsky highlights survey findings showing tech worker burnout climbed from 44% in 2025 to 55% in 2026, driven by corporate demands for elevated output without increased pay, as well as rapid narrative thrash. Graham emphasizes that workers must be allowed to process this loss—comparing it to Chip Conley's notion of "throwing a funeral" for past chapters—rather than being forced into toxic positivity. Dismantling the Fear Narrative and Role Silos (25:36) Graham critiques the dominant corporate framing that demands workers train AI tools to replace them within months, labeling many "AI-branded layoffs" as opportunistic rebranding by leadership to mask prior overhiring. Citing journalist Manoush Zomorodi's 30-year media career, Graham suggests reframing expectations around the premise that roles will endure, but their operational workflows will transform roughly every six years. This platform shift is eroding legacy boundaries separating product managers, designers, and software engineers. While defensive knowledge-hoarding represents a natural survival impulse, Graham warns that clinging to legacy methods guarantees falling behind. Startups and first-principles learners benefit by ignoring historical discipline silos, such as design leaders leveraging AI tools to push functional code directly into production. Protecting Judgment and the Human Sandwich (59:38) In a marked departure from her original scaling philosophy, Graham asserts that some Legos should never be given away. Tasks relying on human discernment, aesthetic taste, organizational trust, and areas where an individual is exceptionally skilled should not be outsourced to automated agents. Delegating high-level strategy or writing without personal oversight represents an abdication of core responsibility. Rachitsky frames sustainable integration around the "human sandwich": humans direct the intent and framing at the top, AI accelerates drafting in the middle, and humans refine, edit, and uphold standards at the end. Maintaining accountability remains essential, as exemplified by corporate policies requiring humans to take full responsibility for published text regardless of AI involvement. Graham notes that maintaining empathetic management structures is vital to support teams through these disruptive organizational cycles. Graham and Rachitsky frame the current landscape as a manageable "slow takeoff" rather than an abrupt replacement of human labor, giving workers time to experiment and adapt. However, it remains an open question whether the industry will experience a cultural whiplash that eventually restores a premium to human-crafted execution, or whether teams will remain trapped in repeated cycles of organizational disruption.

[0:00] Molly Graham: Change sucks. It also can be awesome, but we don't have to be fluffy bunnies about this. We can also just say this is hard. [0:00] Molly Graham: What would you do if you believed your job was always going to exist? It was just going to look completely different every 6 years. [11:27] Molly Graham: Your main job in the face of rapid growth and change is to make yourself irrelevant because it is the only way that you can be prepared for whatever is coming next. [15:37] Molly Graham: The future will be defined by the people that learn, not the people that know. [19:27] Molly Graham: I don't want to fucking steer... I want to row. [35:07] Lenny Rachitsky: A growing part of everyone's job is cleaning up the AI slop from other people trying to do your job. [42:02] Molly Graham: The best way to give Legos away is to chuck them at their face and run in the other direction. [51:50] Molly Graham: Protection and holding on and gripping to what you know is not the way you thrive in change. It's not the people that define the future. [69:16] Molly Graham: There was a really strong narrative out there that was like you're too late. You're already too late... If you're not automating every single part of your life and managing 26 agents... that you're behind. And every single conversation I have with every leader, every manager at all of the big labs, every company is like: we are early. This is like whatever sports ball game you want to be in—this is inning one, period one, yard one. [69:16] Max Mullen: the distance from beginner to expert is really short [81:20] Molly Graham: Treating AI as like a junior intern and realizing that it's fundamentally just a tool to get work done. But what matters is like the work is still done mostly by the humans and the human brains, and we got to take care of the humans and we got to help them figure out how to navigate this wild wild west that we are in. [87:24] Molly Graham: Sometimes grief needs a funeral.

[0:00] So, we've been chatting about your [0:01] famous giveaway, your Legos career [0:04] advice. This idea of how this advice [0:06] applies in today's very strange AI [0:09] world. [0:09] >> The narrative right now is literally [0:11] like, okay, we hired this new employee. [0:13] This new employee is [music] the [0:15] smartest employee that you have ever [0:17] met. I want you to pour [clears throat] [0:19] every single thing that you know into [0:21] this employee and then they're going to [0:23] take your job in 6 months. Like, who the [0:25] wants to do that? [0:26] >> Here's the big question, Molly. Are [0:27] there any Legos you should not give away [0:29] >> in AI land? I think we got to caveat [0:32] this. There are some Legos that [0:34] shouldn't be given away. There's just [0:36] some work that shouldn't be outsourced. [0:37] >> There's a radical departure from your [0:39] advice over the many years. [0:40] >> You individually are phenomenal at a set [0:43] of things. Don't outsource it to these [0:45] weird robots that, you know, are [0:46] effectively summer interns. [0:48] >> AI is taking a lot of our Legos whether [0:50] we like it or not. And we're being [0:51] encouraged to give away our Legos to AI. [0:53] you had someone on who talked about like [0:55] the job used to be rowing and now it's [0:57] steering and I was like I feel like [0:59] there's a lot of people out in the world [1:01] right now that are like I don't want to [1:02] steer. [1:03] >> I've heard from a lot of engineers just [1:04] like I really miss what it used to be. [1:06] >> Change sucks. It also can be awesome but [1:09] we don't have to be fluffy bunnies about [1:11] this. We can also just say this is hard. [1:13] >> This is almost a discussion around what [1:15] should AI do? Where do you want AI to be [1:17] involved and where you not want it [1:19] involved? What would you do if you [1:20] believed your job was always going to [1:23] [music] exist? It was just going to look [1:25] completely different every 6 years. [1:29] Today, my guest is Molly Graham. This is [1:32] Molly's second visit to the podcast. And [1:34] man, this is a powerful conversation. [1:38] The frame for this conversation is her [1:40] classic give away your Legos career [1:42] advice. But in an AI world, Molly's [1:45] advice for the last 13 years has been [1:47] that your career will be better off if [1:49] you give away your projects and your [1:52] teams and your responsibilities to other [1:54] people as your company grows versus [1:57] trying to hold on to it, which is what [1:59] we naturally want to do. Essentially, to [2:01] give away your Legos. After 13 years of [2:04] giving this advice and it unlocking so [2:06] much wind for so many people over the [2:08] past decade, Molly has realized that it [2:10] is no longer true. when you are giving [2:13] away your Legos to AI, it's a lot more [2:16] nuanced and complicated [music] now. And [2:18] so in this conversation, we try to get [2:20] to the bottom of this question. What [2:23] Lego should you still be giving away? [2:25] And what Lego should you keep? If you're [2:27] not familiar with Molly, she has spent [2:29] 20 plus years helping organizations and [2:31] the humans inside them navigate growth [2:34] and change. She's held leadership roles [2:36] at Google and Facebook and Quip and the [2:38] Chan Zuckerberg Initiative. These days, [2:40] she hosts Ted's work life podcast, which [2:42] she took over from Adam [music] Grand. [2:44] She also runs an incredibly important [2:46] leadership community called Glue Club [2:48] and writes a newsletter called Lessons. [2:50] Now, before we get into it, I noticed a [2:52] lot of people don't finish our full [2:54] episodes and miss some of the best [2:56] stuff. So, to help you, we've just [2:58] created a new Lenny's Most Replayed [3:01] Moments YouTube channel that has exactly [3:04] this, the most rewatched and shared [3:06] segments from our long- form [music] [3:08] episodes. You can now check it out and [3:10] subscribe to the channel at [3:12] lennispodcast.com/mostreplayed [3:15] moments. There's also a link in the [3:17] description. Finally, don't forget to [3:18] check out lenniesprob.com for a free [3:21] year of the hottest and most beautifully [3:22] crafted AI and nonI products in the [3:25] world. That's lenny'sprobass.com. [3:28] With that, I bring you Molly Graham. [3:34] Molly, thank you so much for being here [3:36] and welcome back to the podcast. [3:38] >> Thanks for having me, Lenny. I'm excited [3:40] to be back. [3:41] >> Uh, I'm even more excited to have you [3:42] back. Let me add a little context to [3:45] this slightly unusual conversation we're [3:47] gonna have. So, we've been chatting over [3:49] the past couple months about your famous [3:52] uh infamous giveaway your Legos career [3:55] advice and this question came up and I [3:58] know you're hearing this a lot from [4:00] other people. This idea of how this [4:01] advice applies in today's very uh [4:04] strange AI world where AI is taking a [4:08] lot of our Legos whether we like it or [4:10] not and we're being encouraged to give [4:12] our legos to AI. People are afraid about [4:14] AI taking their legs. And so, uh, the [4:18] question is just how this advice now [4:20] applies in a world of AI. And I know [4:23] this is kind of an ongoing thought [4:25] process for you, but you actually have a [4:27] lot of really interesting insights and [4:28] takes on how to think about this advice [4:30] now in today's very strange world. And [4:32] so, we're going to have a conversation [4:34] about it, see where it goes. This [4:35] episode is brought to you by our [4:37] season's presenting sponsor, WorkOS. [4:40] What do OpenAI, Anthropic, Cursor, [4:42] Replet, Sierra, Clay, and hundreds of [4:45] other winning companies all have in [4:46] common? They are all powered by work OS. [4:49] If you're building a product for the [4:51] enterprise, you've felt the pain of [4:52] integrating single sign on, skim, [4:55] arback, audit, logs, and other features [4:57] required by large companies. Work OS [4:59] turns those deal blockers into drop-in [5:02] APIs with a modern developer platform [5:04] built specifically for B2B SAS. [5:06] Literally every startup that I'm an [5:08] investor in that starts to expand up [5:10] market ends up working with Work OS. And [5:12] that's because they are the best. [5:14] Whether you are seedstage startup trying [5:16] to land your first enterprise customer [5:18] or a unicorn expanding globally, work OS [5:20] is the fastest path to becoming [5:22] enterprise ready and unblocking growth. [5:24] It's essentially Stripe for enterprise [5:26] features. Visit works.com to get started [5:29] or just hit up their Slack where they [5:31] have actual engineers waiting to answer [5:33] your questions. Work OS allows you to [5:35] build faster with delightful APIs, [5:37] comprehensive docs, and a smooth [5:39] developer experience. Go to works.com to [5:42] make your app enterprise ready today. [5:44] I'd say as a first step, let's remind [5:46] people what this advice is. Uh I imagine [5:49] most people have heard it. A lot of [5:51] people probably like, "Oh yeah, I kind [5:52] of get the idea." So explain kind of the [5:54] original uh idea of giving away your [5:56] Legos. It actually started when I was at [5:58] Google and Facebook and it started as a [6:01] a little talk that I would give people [6:03] that worked for me and for context like [6:06] Google was pretty big when I joined. It [6:08] was like 10,000 employees in 2007 but my [6:12] department grew from 25 people to 125 [6:15] people in nine months. So that was my [6:16] first experience with like really rapid [6:19] scale and then I went to Facebook and [6:21] Facebook was relatively small when I [6:23] joined. it was 500 employees and 80 [6:25] million users smaller than MySpace which [6:27] is always good context to remember um [6:30] and you know while I was there you know [6:32] obviously a huge growth curve I left 5 [6:34] years later it was 5500 employees and [6:37] over a billion users so that experience [6:40] was nuts uh from a scaling perspective [6:43] and what I witnessed at Google and then [6:46] sort of really witnessed at Facebook was [6:49] how hard and scary that experience was [6:54] for people. Um, I watched a lot of folks [6:58] go from sort of like you you build a [7:00] thing, right? You show up and you become [7:02] the person that owns the blog or owns [7:05] this part of the stack or built that [7:07] product and you sort of build like an [7:09] identity around it. You're the this [7:11] person, whatever that is. And then the [7:14] nature of scale is that everything [7:15] around you changes. And so somebody [7:17] shows up and your manager shows up and [7:19] says, "Hey, you need to, you know, hand [7:21] that thing that you've built your whole [7:23] identity around to someone else and, you [7:26] know, go on to doing something else." [7:27] And your first instinct is like, "What?" [7:30] You know, like no, I don't I don't want [7:31] to give it away. Like I I'm good at [7:34] this. I know how to do this. Um I also [7:36] think it's fun and what if it's the only [7:38] fun thing to do? And so you kind of [7:41] witness people like would have this [7:43] tendency to hold on. And so what I [7:46] started to do with people on my team was [7:47] say, "Hey, this change is happening and [7:50] here's how you might feel, right? That [7:52] you might feel like all these feelings [7:55] territorial and wanting to hold on." And [7:58] actually the most important thing to do [8:00] is to give things away to to to evolve [8:03] as the company is evolving. And my brain [8:05] is a really weird place. Like I grew up [8:07] on the Muppets, so I just like spits out [8:10] I always think there's just like a lot [8:11] of tiny monsters dancing around singing [8:13] songs in my head. But like that is why [8:14] metaphors come out uh for me. And so I [8:17] always use this metaphor of like just a [8:19] bunch of kindergarteners and like [8:20] somebody dumps a pile of Legos in front [8:22] of you and at first it's fun, a little [8:24] overwhelming, then you start building [8:27] and and the giveaway your Legos part is [8:29] like that feeling when somebody else [8:31] shows up and they try to take the tower [8:33] out of your hands and the kindergartener [8:36] response is like get out of here. You [8:37] know what I mean? It's like shoving [8:39] someone away. when actually like you get [8:42] multiple people. It means oh you can go [8:44] build something new and fun. You can [8:45] start from scratch and you can learn [8:47] something. But the natural human [8:48] instinct in the face of change is to [8:52] hold on to things and to resist the [8:54] change, right? To um to be territorial [8:57] and all of those things. So anyway, I I [9:00] started giving this talk to folks on my [9:02] team to kind of help them understand [9:04] that change and what was coming. And [9:06] then eventually I sent it out to my [9:10] friends at first round who were building [9:11] the first round review at the time. And [9:13] just to be clear, this is now 13 years [9:15] ago. Um the talk I was like when when I [9:18] was at Facebook, it was over 20 years [9:20] ago. Um and uh it I sent it to first [9:25] round and we published it and you know I [9:28] would have said I was speaking to folks [9:32] going through a Facebook like [9:33] experience. Like I would have said like, [9:34] "Hey, this is an article that is for [9:36] like the Stripes or the Slacks or [9:38] whoever was, you know, uh, blowing up in [9:40] in 2013 to normalize, hey, this is what [9:44] it feels like and this is what you have [9:46] to do to grow as fast as your company is [9:48] growing." Um, but what happened when it [9:51] was published is that I got emails from [9:54] all over the world. I got emails from [9:56] people at companies like Safeway, you [9:59] know, where and this woman, I still [10:01] remember this email, wrote me and was [10:02] like, "This was so helpful to me. This [10:04] like perfectly describes what I've been [10:07] going through on my team." And I got an [10:08] email again, I remember it very vividly, [10:11] from a founder in Nigeria who was like, [10:13] "My team went from two people to four [10:15] people this year and give away your [10:17] Legos like is so valuable to me. Like, [10:19] this is exactly what I've been feeling." [10:21] And my first reaction was like, I didn't [10:25] write this for you. Like, this is not [10:27] this was not meant for you. Um, but my [10:29] second one was, whoa, this is about [10:31] something much bigger than just what it [10:34] feels like to be inside of rapid scale. [10:37] Um, and fundamentally, I think the [10:40] Lego's message is about change, you [10:42] know, and it's about the fact that when [10:44] you go through change, a lot of [ __ ] [10:47] happens to you. You know what I mean? [10:49] like it just is a very specific [10:51] experience and I think that's why it [10:53] ended up end ended up being so universal [10:56] and it is crazy like I still get emails [10:59] about it multiple emails a month about [11:01] it to this day. Um so it's it's lasted [11:05] in a way that again like I just thought [11:07] I was I was sending out a note to the [11:09] folks that are going through crazy rapid [11:11] change. I uh I was at a first round [11:13] event I don't know a year ago or [11:14] something and they were talking about [11:15] all the different posts people have [11:16] written and I think it's one of the [11:18] maybe the first or second most popular [11:20] post on the first round review. [11:22] >> It's it's up there and it's traveled in [11:24] ways that I don't think any of us [11:26] imagined it would. [11:27] >> Okay, so let's talk about what still [11:30] holds true in this advice in this [11:33] today's very strange AI world. What [11:36] still holds true? What's still correct [11:37] about this advice based on what you're [11:39] seeing? One thing that's crazy about [11:40] this article is I still get so many [11:42] emails about it today. I still get asked [11:44] to give speeches, you know, at every [11:46] fast growing company. So I think for [11:48] anybody that's going through rapid [11:50] scale, Legos is still really relevant. [11:53] But the interesting thing is like what [11:55] started to happen, it's probably like [11:57] two years ago is I got more inbound from [12:02] managers um and more inbound from [12:05] leaders about Legos. just more people [12:10] grappling with change inside their [12:13] companies and I think that is the thing [12:16] that really holds true today and [12:18] actually has just become more universal. [12:21] Um you know I used to [12:24] uh really check before I went and did a [12:27] speech at some company how fast the [12:30] company was growing. Um, I would ask [12:32] like kind of about revenue growth and [12:34] about headcount growth because that just [12:36] helps me contextualize like how I should [12:38] speak to to employees and I still do [12:41] that. Um, but it's also become really [12:44] clear that every single company in the [12:46] world is going through enormous change [12:49] of varying shapes and kinds right now. [12:52] And that is the fundamental underlying [12:55] message of Legos is how do you deal with [12:58] change and how do you um be your best [13:00] self in the face of change. So I feel [13:02] like the the number one thing that is [13:06] true today as true as it was you know 10 [13:08] or 15 years ago is the change is really [13:11] scary and hard. And I always say like [13:14] somebody once asked me to like summarize [13:16] the Legos article in one sentence. [13:17] They're like Molly this is too long. [13:19] like give me the cliff notes [laughter] [13:21] and I I said two things. Um [13:24] unfortunately they didn't get one [13:26] sentence, they got two. The two [13:27] sentences were [13:30] number one, your main job in the face of [13:33] rapid growth and change is to make [13:35] yourself irrelevant because it is the [13:38] only way that you can be prepared for [13:40] whatever is coming next. [13:42] And the second piece of advice or sort [13:44] of second summary of it was don't worry, [13:47] it's all going to be okay. I always feel [13:49] like the Legos article and the speeches [13:51] I give are like a form of group therapy. [13:53] They're like just a giant hug. Like yes, [13:55] it feels chaotic and overwhelming and [13:57] stressful, but there's all this [13:58] opportunity on the other side. And I [14:01] think that the don't worry, it's all [14:02] going to be okay is really something [14:04] everybody needs to hear that like change [14:06] is scary and hard, but it doesn't [14:08] necessarily mean the world is ending. I [14:10] think this the second piece of that is [14:13] that change comes with this incredible [14:17] set of emotions like this wild roller [14:20] coaster um that we don't talk about [14:22] enough. And I think that was a lot of [14:23] why I first started talking about Legos [14:25] like at Facebook and on my teams was I [14:28] just wanted to normalize for people what [14:29] it felt like that that you might feel [14:31] all these feelings and that that was [14:34] what everyone around you was feeling, [14:35] right? That it didn't make you crazy and [14:37] it didn't make you broken or something [14:39] like that. It also didn't mean anything [14:40] was wrong. It actually meant that all [14:41] the right things were happening. And I [14:44] think that is very real today. Like when [14:47] I travel around and I'm talking to [14:49] leaders, um, and I know you and I are [14:51] going to talk about this, but a lot of [14:52] what I'm hearing is is grief and all [14:56] these different emotions. There's [14:57] obviously like excitement and um joy in [15:00] in this moment of of chaos and change [15:02] with AI, but there is a lot of sadness. [15:06] There's a lot of overwhelm that all, you [15:08] know, manifests. Some of it manifests in [15:09] burnout, but it's like there is just a [15:12] lot going on for people right now. And [15:15] you really can't lead right now without [15:17] talking about that um and without [15:19] normalizing that. And I think that's [15:20] like such a big part of the giveaway or [15:24] like I was, you know, today is just like [15:28] helping people understand that these [15:31] emotions are just part of sort of your [15:34] body and your identity reacting to [15:35] change. [15:37] The other two things I would say that [15:39] really do still feel true to me that I [15:41] both talk about in the article and have [15:43] talked about a lot since is [15:46] like [snorts] one of the things I say to [15:47] people that are inside of a really [15:48] rapidly growing company is the future [15:50] will be defined by the people that learn [15:54] not the people that know. You know, I [15:56] always say like what you can learn by [15:58] tomorrow matters way more than what you [16:00] know today. And like never has a truer [16:02] sentence been said than like about the [16:04] age of AI. Do you know what I mean? like [16:06] whatever we thought we knew six months [16:07] ago, like toss it out the window. [16:09] Something new is true today. But what I [16:11] used to say to people and I still say I [16:12] guess when I when I do these speeches is [16:14] like you go look at that graph of how [16:17] fast your company is growing, right? You [16:18] go look at like that curve, you know, [16:20] and at Facebook it was like felt like we [16:22] were falling off of it. That is the [16:24] graph of how fast your company is [16:26] growing. Yes. But it is also the graph [16:28] of how fast uh your job is growing, [16:31] right? how fast every single thing [16:34] around you is growing and changing, [16:36] which means it's also the graph of how [16:38] fast you need to grow. And I think that [16:42] is such an important thing to understand [16:44] inside of a a world of change, which is [16:47] that standing still, right? It feels [16:50] safe. It feels like [16:53] hold on to what you know, you know, [16:54] because that that at least it's not, you [16:56] know, scary and unknown. But actually [16:58] standing still is like [17:01] the least safe thing you can do. It's [17:03] basically you're guaranteed to fall [17:06] behind. Um and I saw this viscerally at [17:09] Facebook when because the first two [17:11] years I was in HR and um you could [17:15] literally see like the highest performer [17:18] one year if they didn't grow and change [17:20] and if they didn't evolve their team [17:22] fast enough, they were underwater like [17:24] less than a year later because it was a [17:25] different company. And I think this is [17:27] happening with AI as well. Um, which is [17:31] that we do have these instincts to like [17:34] hold on to what we know and to defend [17:36] what we know and to fight for what we [17:38] know for a bunch of different reasons. [17:40] Many of them good. But the future is [17:43] going to be defined by the people that [17:45] are willing to just take the stance of [17:47] learning and to throw themselves into [17:49] this change, scary and unknown as it is. [17:53] Um and that that message again remains [17:55] true in this this wild wild world. [17:59] >> Before we get into just what how the [18:00] advice is different which when you go [18:03] back to your summary of the two kind of [18:04] items that kind of summarized the idea [18:06] one is become redundant and then two [18:09] what was the second uh sentence. [18:10] >> The second one is basically don't worry [18:11] it's all going to be okay. [18:12] >> Don't worry. Yeah. Okay. So those don't [18:14] feel necessarily correct anymore. So [18:17] we're going to get into that because I [18:18] think that's as you said the core of [18:20] people's concern. [18:21] that was like comforting and now it's [18:23] like well are you sure? [18:24] >> Yeah. [18:25] >> Um this grief piece just to spend a [18:27] little more time here. I've been I've [18:29] been seeing this a lot in a lot of [18:31] different professions. I've done these [18:32] surveys that um we might get into a [18:34] little bit but like just engineering as [18:37] a role has completely transformed in two [18:41] years. It's been like the same job [18:43] forever. Writing code, sitting there [18:45] writing code in various forms of idees, [18:48] no longer part of the job. Now it's [18:51] talking to your AI to write the code. [18:53] Whether you're there or not, that's [18:54] where it's all going. It's going to be [18:56] 100% write this thing, build this thing. [18:58] And I used to be an engineer and I moved [19:01] into product and I was I was so missing [19:04] that flow state of being an engineer, [19:06] just sitting there coding, building. And [19:08] now that's gone. [19:10] You no longer sit there and just build a [19:12] thing. You're just like waiting for [19:13] agents to run and then checking. You [19:14] probably have a hundred different agents [19:15] and it's just like a very strange new [19:17] job. And I've heard from a lot of [19:19] engineers just like I really miss what [19:21] it used to be. [19:22] >> Yeah. [19:22] >> Anything more there about just I don't [19:24] know what you're hearing from folks [19:25] about just like man this sucks. [19:27] >> No, it's exactly um it's such a perfect [19:32] example of like the grief. Um I was [19:36] giving a speech like two weeks ago at [19:38] you know pretty fast growing tech [19:40] company and this guy came up to me after [19:44] and he'd been at the company for a [19:46] couple of years so it's gone through [19:47] like a huge amount of change and he was [19:48] talking to me about the fact that he [19:49] just wasn't enjoying his role as much [19:51] anymore and my brain immediately went to [19:54] oh right like you enjoyed it when it was [19:56] smaller and there was more creativity [19:58] and now there's more structure and so I [19:59] was talking to him about that and it [20:01] took like a while and to some extent [20:03] like I want to go talk to him again [20:04] because I feel like I missed it in the [20:06] first conversation where actually I [20:08] think what he was talking about was the [20:11] grief that is very present for him now [20:14] in the fact that he's not sure what is [20:17] his current job like what is this the [20:19] company has grown and so he's more in a [20:21] more structured environment and what is [20:23] just the simple fact that engineering [20:25] has totally changed. Um, and a lot of [20:28] what he was talking about was how much [20:29] he missed being more handson, which is, [20:33] you know, one way of saying it. But I [20:35] think that that grief is happening for a [20:38] lot of people. I think engineering is [20:40] like probably one of the most visceral [20:42] areas where people's jobs have genuinely [20:45] transformed. Um, [20:48] you know, so you had someone on last [20:50] week, um, who talked about like the job [20:53] used to be rowing and now [20:55] >> Yeah. from OpenAI. [20:57] >> She said like the job used to be rowing [20:58] and now it's like [21:00] >> steering. [21:00] >> Steering. And I was like, I feel like [21:03] there's a lot of people out in the world [21:04] right now that are like, I don't want to [21:06] [ __ ] steer. Do you know what I mean? [21:07] I want to row. like I like rowing or I I [21:10] I mean it's and I think it can be hard [21:12] to separate I like rowing or I'm scared [21:15] that rowing is the only thing I'm ever [21:18] going to be good at or it's what I know [21:20] and I don't know if I uh can be good at [21:24] steering and I think that's happening in [21:26] a lot of disciplines you know um and so [21:29] that grief like first and foremost like [21:31] that grief is really real you know I was [21:33] talking to a product leader just the [21:35] other day who was like I don't know man [21:38] we're like all supposed to be these like [21:40] you know universal builders now and and [21:43] she was like I don't it's kind of lonely [21:46] you know she's like I miss these parts [21:48] of the collaboration that have been a [21:50] little bit stripped away because now I'm [21:52] working with robots all the time you [21:54] know and I was like I just said to her [21:56] like yeah man that sucks sit with it for [21:59] a second you know like change sucks it [22:03] also can be awesome but we don't have to [22:06] be fluffy bunnies about this we can also [22:08] just say this is hard. [22:09] >> There's so much power in just like [22:11] saying the thing that you're feeling. [22:12] What a what a [22:14] >> I swear to God that that is a big chunk [22:16] of what the Legos article did was just [22:18] like this is hard and scary and that's [22:22] and and it's going to be okay. You know, [22:26] >> this loneliness piece is such a [22:28] important part to touch on. I had um [22:31] Fiona Fong on the podcast who leads [22:34] Claude Code, the engineering team of [22:35] Cloud Code. She's Boris Journey's boss. [22:38] Fun fact. And she said this exact that [22:40] they're like I asked her just what's [22:41] what's kind of the downside of this [22:43] world and it's engineers are used to [22:45] work with a bunch of engineers. Teams [22:46] used to be, you know, five engineers, 10 [22:48] engineers. And now it's fewer teams, [22:50] fewer engineers per team. And it's just [22:52] like you're talking to agents all day. [22:55] And so, so it's [22:57] >> not the same. [22:58] >> It's not the same. [22:59] >> It's not the same. And I think that's [23:00] actually something that leaders of [23:02] companies that are actually like in [23:04] charge of org structures and thinking [23:07] about what the future of structure of [23:09] teams, you know, needs to look like. You [23:12] actually need to think about it cuz like [23:14] yeah, maybe you can like strip out all [23:16] the humans and you get all this [23:19] productivity and maybe you get [23:20] efficiency, but you also get sad humans. [23:22] Do you know what I mean? And like that [23:24] doesn't lead to like the best work for [23:26] anyone. Like I thought your survey data [23:28] around the fact that small teams and [23:31] smaller companies are so much happier [23:33] than people at the bigger companies was [23:35] really interesting. Um just because a [23:38] that like very much resonates with what [23:40] I see in all my conversations with [23:41] leaders. Um, but it also to me is a [23:44] reflection of like I think we're seeing [23:48] more at these bigger companies where [23:50] people are stripping out management [23:51] layers and there's a lot more pressure [23:53] on productivity and and things like that [23:56] and there's less room for the human, you [23:58] know, there's less room for the joy and [24:01] the excitement when all you're doing is [24:03] focusing on optimizing cost and robot [24:05] efficiency, you know? [24:07] >> Yeah, man. There's so much to talk about [24:08] here. Um there's this really cool [24:11] framework I don't know mental model that [24:12] Corey Doctro wrote about uh a while ago [24:15] where he talks about the the centaur and [24:17] the reverse centaur. You heard of this? [24:19] >> No, but I love it already. [24:21] >> So, okay. [laughter] [24:22] So, I think I don't know even how to [24:24] pronounce it. Centaur. Does that sound [24:25] right? Centaur. Okay. So, centaur is a [24:27] human body on top of a animal like a [24:30] horse. Sorry. A human head, torso, top. [24:32] >> Clearly, you do not read enough Greek [24:33] mythology. [laughter] [24:35] >> I just watched the Odyssey. I'm an [24:37] expert on all things. your kid is going [24:38] to get older and you're going to read [24:40] the like lightning thief books and [24:41] you'll get it. [24:42] >> Lightning thief. Okay. Yeah, I'll look [24:44] forward to it. Okay. So, so idea is a [24:46] centaur is human head controlling a [24:48] animal body. Reverse centaur is an [24:50] animal head controlling a human body. [24:53] So, the the way he his kind of insight [24:55] here is what we want is AI that we [24:58] control. We are in charge. It's doing [25:00] our bidding. Awesome centaur. It's a [25:02] cool way to live. What we need to avoid [25:05] and fear is the reverse centaur where [25:07] the AI is using us to do things like [25:11] Door Dash people and Uber people are in [25:14] that world already, not the funnest [25:16] life. And it might expand to knowledge [25:20] work and I think that's a lot of [25:22] people's fears. You're just this like [25:23] thing that's just controlling agents and [25:24] just this like closing gap of here's [25:26] where humans still are valuable and then [25:29] AI is kind of telling you where to build [25:30] and what to do and then it's and then [25:32] it's doing the thing. So, so I've been [25:35] thinking a lot about that. [25:36] >> Yeah. I mean, I want to get to the fear [25:40] side of this and the fear narrative as [25:43] well because I think that's one of the [25:45] things that is really different uh in [25:48] this this stage uh and this sort of [25:51] phase because it's really hard to tell [25:53] people like lean into change when [25:56] they're like but wait like what's on the [25:59] other side? Like you're telling me to [26:00] let go of my Legos. You're telling me to [26:01] make myself irrelevant. like [ __ ] you. [26:03] You know what I mean? Like I I don't [26:05] believe there's a job on the other side. [26:08] And I think that fear narrative like I [26:12] am sure some of it is real, but some of [26:16] it is really overblown and it's and it's [26:19] creating like a pretty toxic environment [26:22] for people where it's so hard to lean [26:25] into this change with joy or excitement [26:28] or any sense of opportunity. I always [26:31] say like the narrative right now is [26:33] literally like okay we hired this new [26:36] employee. This new employee is the [26:39] smartest employee that you have ever [26:42] met. This employee is like 10 times [26:43] smarter than you and I want you to pour [26:47] every single thing that you know into [26:50] this employee and then they're going to [26:52] take your job in six months. Like who [26:54] the [ __ ] wants to do that? Do you know [26:55] what I mean? No one wants to do that. [26:57] Like that is not a good narrative for [27:00] anyone. By the way, it's also not [27:01] reality. Like as of right now, like [27:04] there is not a lot of data, although you [27:05] may have more than I do that says that [27:07] AI is genuinely taking jobs away. Um, [27:10] and I have a lot of beef to pick with [27:12] all the AI branded layoffs out there [27:14] because they're [ __ ] Like they're [27:15] not about AI. Like they are about badly [27:17] run companies slapping an AI label and [27:19] getting some share points from that [27:22] versus saying, "Whoops, we made we hired [27:24] too many people." Um, and they're [27:26] propagating this fear narrative that is [27:28] like all these jobs are your job is [27:30] going away, right? There is no job on [27:32] the other side. One of the best, so I [27:34] took over this podcast, which you know [27:36] called work life and it's let me have [27:38] all these really fun conversations with [27:41] people and one of the best conversations [27:43] I had uh was with this journalist named [27:46] Man Soari and she has been a journalist [27:49] for 30 years. You want to talk about an [27:51] industry that people have been [27:52] predicting the death of for 30 years, [27:55] right? Journalism. And Minute has done [27:59] everything like she started the BBC and [28:02] she was uh super early in audio and she [28:05] did this like crazy crypto audio podcast [28:07] and she's also like she's the host of [28:09] TED Radio Hour. So, Minute over 30 years [28:12] has built a very successful career in an [28:14] industry that is being constantly [28:17] disrupted. And from talking to her, I [28:21] basically walked away with this really [28:22] interesting question that is totally [28:24] different than, "What would you do if [28:26] you believed your job was going to [28:27] disappear?" It was, "What would you do [28:30] if you believed your job was always [28:32] going to exist? It was just going to [28:34] look completely different every six [28:37] years." [28:38] And I just kind of wish that was the [28:42] conversation we were having about all [28:44] the jobs in tech and honestly all the [28:47] jobs that are theoretically going to get [28:49] taken by AI, which is like the form is [28:52] definitely going to change. But until we [28:55] have real evidence, what if we believe [28:57] that they're not going away? They're [28:59] just going to reinvent themselves. [29:01] >> That is awesome advice. And that's [29:03] exactly what's been happening so far. [29:05] >> Yeah, [29:05] >> there's always this fear that, okay, but [29:07] now it'll be different in X years, but [29:09] that is actually exactly what's been [29:11] happening. Engineering exists, different [29:13] job. There's actually more demand than [29:14] ever for engineers. [29:16] >> Exactly. Your data said that. And I was [29:18] like, "Thank you for publishing this [29:19] [laughter] data, [29:19] >> Lenny." [29:21] >> Before we get into the the advice kind [29:23] of how it's evolved, there's a couple [29:25] things I want to share which touch on [29:26] things you mentioned about how people [29:29] are feeling. So, I'll share these images [29:30] on the screen as we talk about this of [29:33] just people's feelings right now. Just [29:35] to kind of come back to that point. Um, [29:38] so we looked we did the survey for two [29:40] years now in a row of how tech people [29:42] are feeling and how they're feeling [29:44] about AI and all these things. And so we [29:46] have uh a trend now of over time how [29:48] things are changing. And we look at [29:50] burnout and optimism. [29:52] And in 2025 [29:55] 44% of people said they feel burned out. [29:59] LA or this year 55% of people said they [30:02] are burned out. That's a huge jump. [30:04] That's 10% increase in a year of people [30:07] feeling burnt out. [30:10] And it makes sense. as you said, you're [30:13] basically now expected to do more work, [30:16] but not probably more money. And now [30:18] it's just like, okay, well cool. You got [30:20] all these AI. Why aren't you getting [30:20] more done? Look at all these other teams [30:22] moving so much faster. We're screwed. [30:23] We're going to go out of business. We [30:24] got to move faster. So, so it makes [30:26] sense. [30:27] >> I mean, I love that you do that survey [30:28] because I also think I learn a ton from [30:30] it every time you've published it. Um, [30:32] and it's also just like a great reality [30:34] check about how people are feeling [30:35] because literally what your survey says [30:36] is more than half the people [30:38] >> are feeling burnt out which is [30:41] >> like nuts and also yeah I believe it and [30:44] I think you know I mean burnout comes [30:46] from a lot of different places and can [30:47] mean a lot of different things to people [30:49] but to me what I read inside that data [30:52] was like number one like emotions are [30:55] tiring and there is a lot of exhaustion [30:57] trying to understand what's going on in [30:59] a I mean the rate of change right now is [31:01] nuts. [31:02] um both in terms of like obviously the [31:06] technological change but I actually [31:08] think the narrative change is also [31:09] pretty exhausting for people like oh [31:12] this month this is important oh next [31:14] month this you know like there's a [31:16] thrash inside of that that's pretty [31:18] tiring um you know I was emailing with a [31:22] friend at openai and she was like it's [31:25] taken us literally six months to go from [31:28] sort of this token maxing like everybody [31:32] like aggressive productivity like use AI [31:35] everywhere to a conversation that's like [31:38] wait wait wait wait wait wait wait wait [31:39] like is this actually making a [31:41] difference because it's very expensive [31:43] you know and she's like six months [31:44] that's all it took and so if you're [31:46] sitting inside that it means six months [31:48] ago they were like use AI all the time [31:50] every day everywhere and now they're [31:52] like are you doing it well enough you [31:54] know and Hillary Gidley said the same [31:56] thing where she was like you know six [31:58] months ago everyone was like how do I [31:59] get people to use AI and now they're [32:01] like how do I get people to use AI like [32:03] stop using AI so badly you know and it's [32:06] like that sixmon thrash often much [32:11] faster than that is tiring for people [32:13] the grief is tiring let alone like I [32:16] think that feeling which you mentioned [32:18] in your survey of like I'm going to be [32:21] expected to do more for the same amount [32:23] of pay like that's exhausting like that [32:26] I think people feel [32:29] taken advantage of, you know, and like [32:32] what is in this for me? Um like why is [32:35] it fun for me? Um what's the opportunity [32:38] for me? And I think particularly at [32:39] bigger companies, it feels almost [32:42] adversarial sometimes, you know, where [32:44] like, you know, I get why it's good for [32:46] our bottom line, but remind me why [32:49] that's good for me. There's that [32:51] actually touches on one of the biggest [32:52] findings in this survey, which is that [32:55] first of all, half of people that filled [32:57] it out uh are feeling the happiest [33:00] they've ever felt. This is an important [33:01] point we need to make is not everybody's [33:03] feeling [33:04] >> fear and and uh sense that it's all [33:07] doomed. That actually a lot of like half [33:09] of people uh are feeling like they're [33:12] having the best time of their life in [33:13] their career and they're so excited [33:14] about all the things going on. Like you [33:16] may not feel that. You may, if you're [33:17] not that, you may not believe that, but [33:19] from what I can see around me, many [33:21] people are very excited. Even though [33:23] they're working harder than they've ever [33:24] worked, they're also the happiest [33:26] they've ever been about their career. [33:28] >> Yeah. [33:29] >> Well, and I think the context, if I [33:30] remember, was like a lot of the [33:32] happiness tended to be concentrated in [33:34] people that were in smaller teams or had [33:36] more authority like sort of. [33:38] >> Yeah. [33:40] >> Absolutely. And even more interestingly, [33:42] the strongest correlation is people who [33:45] said that a AI has amplified them. [33:48] >> They feel like they figured out how to [33:49] use AI to do more stuff that they're [33:52] excited about. [33:53] >> And that and interestingly, designers [33:55] were the least happy from this work. And [33:57] that's actually what I hear from [33:58] designers is everyone's moving faster. [34:00] Design can't move that fast. You have to [34:03] get feedback from people. You have to go [34:05] through get alignment. You need uh you [34:08] need to think like sit there and think. [34:10] You can't just agent iterate mon. So [34:13] >> I also think isn't there probably well I [34:15] don't know if you're hearing this from [34:16] the designers but there's also a like [34:17] everyone's a designer now. [34:18] >> Yeah that's also a big part of it [34:20] >> when you're when I worked in education [34:23] it's like one of those industries it's [34:25] really hard to work in because everyone [34:26] was a student once so everyone thinks [34:29] they know things. And I feel like now [34:31] designers have that where it's like oh [34:33] yeah I just made this in Gemini or I [34:36] just [laughter] made this in Claude. [34:37] Here you go. Here's my design. And and [34:40] by the way, I think this is true of you [34:41] know a lot of industries which is like [34:43] and and whole products where it's like [34:44] the gap between [34:46] I made this and what is actually great, [34:49] right? The gap between like I created [34:51] this prototype and a product that is [34:52] like exceptional is really big. The same [34:54] is true obviously of design. Design just [34:57] got like way more accessible to the [34:59] average person. Uh at least okay design [35:02] got really really accessible you know [35:04] which can be exhausting when people are [35:06] telling you how to do your job all the [35:07] time. [35:07] >> Yeah. I had this tweet the other day [35:09] that that got a lot of um traction uh [35:12] along these lines. A growing part of [35:14] everyone's job is cleaning up the AI [35:16] slop from other people trying to do your [35:18] job. [35:18] >> Okay. So, I have a lot of feelings about [35:21] this and it goes to this super [35:23] intelligence thing that we were talking [35:25] about where it's like, you know, we [35:26] saying like AI is like the smartest [35:29] employee you've ever hired in the entire [35:32] world and uh it's better than you at [35:35] everything. And I think it causes people [35:37] to like approach it that way when [35:41] actually most of our experience with AI [35:43] I think a lot of people uh have had the [35:45] experience with AI where it's like [35:47] that's wrong like what I just asked you [35:49] to do that like this isn't good I always [35:51] think like AI needs the same coaching [35:54] and training that a human does right it [35:56] needs context it needs onboarding it [35:58] needs all of these things it and it's [36:01] kind of much more like a like an intern [36:03] like a bad intern often I call it a lazy [36:06] intern Um, and what happens like to your [36:09] point about AI slop is that folks are [36:12] approaching it as if it's like a a [36:14] great, you know, the best employee [36:16] they've ever hired. So, they just like [36:18] copy paste send, right? And I'm like, [36:21] you would never do that if you thought [36:23] about it as an intern. You would never [36:24] take the presentation that an intern [36:26] handed you and just like straightforward [36:27] it to your boss. Like, that is a little [36:30] bit insane, right? uh you would iterate [36:34] on it, you would edit it, you would ask, [36:36] make sure that it had all the context [36:37] from like the 57 conversations that [36:39] you've had with the summer intern before [36:41] you ship that preso to your boss. AI is [36:44] the same. And I think part of what's [36:46] going on with all the slop in the world [36:47] is people have like shipped [36:49] accountability. Like it's like, oh, AI [36:52] said this was good enough, so I'm just [36:53] going to like copy paste send, you know? [36:55] And that is never been how good work [36:59] happens. You know what I mean? And so [37:00] like I feel like we need a a change from [37:02] like this super intelligent being that's [37:03] better than all of us at our jobs to [37:05] like no it's just a [ __ ] intern man [37:07] and like it needs the coaching and [37:09] context and all of that and many [37:12] iterations that most interns do. And I [37:14] think the other thing you know to your [37:16] point about accountability is or to your [37:18] point about sort of like if you don't [37:20] take accountability for the quality of [37:22] your work that shifts to someone else [37:24] right the person that receives it has to [37:27] deal with it and that is like just a [37:30] drain on organizations and like I [37:32] literally see CEOs like we talk about [37:34] this all the time in glue club like she [37:38] CEOs like shipping a strategy memo that [37:41] was clearly written by AI that is you [37:44] role modeling for your organization that [37:46] it's fine to outsource your thinking and [37:48] it's fine to outsource your strategy. [37:50] It's you role modeling that you don't [37:51] need accountability for the work that [37:54] you send. Um, and I feel like it goes [37:56] down to this thing of like we're like [37:58] we've this last six months we've really [38:00] been like overvaluing productivity, [38:02] which is just like, you know, you hear [38:03] all these stories about like companies [38:05] like counting tokens and having token [38:07] leaderboards and it's like it brings me [38:10] back to the days when people were like [38:11] counting cars in a parking lot and Slack [38:13] bubbles and lines of code, right? Which [38:16] we all know is a really bad way to [38:18] manage people. Um, and it's it's not for [38:22] we've been focused on sort of like how [38:24] do you run as fast as you can on the [38:26] treadmill, but like not am I going [38:28] anywhere, you know, and which is to me [38:30] the difference between like productivity [38:31] and efficiency. Like productivity is can [38:33] you generate, you know, more, which at [38:36] this point I think we've proven we can [38:37] all generate a bunch of [ __ ] that other [38:39] people then have to wade through to the [38:41] point of your tweet. But is that [38:43] efficient? Does that actually move the [38:44] conversation forward? And the answer [38:47] lately has been why no. It does not. [38:49] >> Yeah, there's a in that report I have [38:51] this iceberg image of just like we're [38:54] doing better on top. Oh, look at all the [38:56] stuff, but the output is worse. Thinking [38:58] judgment is coming down. So, there's a [39:00] lot of a lot of things we're watching. [39:01] The good news is everyone's aware of [39:02] this. They're like, you know, maybe this [39:04] isn't the way we should be working. [39:05] >> No. I thought I there was this really [39:07] interesting engineering report that said [39:10] you know engineer like for engineering [39:12] it has genuinely made people more [39:14] productive but the amount of lines of [39:18] code that have had to be rewritten has [39:20] gone up like 8x so it's like this like [39:23] very clear symbol of productivity [39:25] obviously like also the security [39:26] incidents have gone up etc etc so it's [39:28] like there's just this difference [39:30] between productivity and efficiency and [39:32] I think part of your burnout data is [39:35] like people are just getting swamped, [39:39] you know, and that's exhausting if what [39:41] you're doing all day is waiting through, [39:44] did the person on the other side of this [39:45] actually think about it? Did they [39:47] actually care? Did that's tiring. That [39:50] doesn't feel like a good use of your [39:51] time. It just feels a little bit [39:52] infuriating, you know? [39:54] >> Yeah. Comes back to the grief of like, [39:56] oh man, I missed what I had used to be [39:57] doing. Look at this weird new job I'm [39:59] doing. [40:00] >> Yeah, totally. [40:01] >> Okay, so let's come back to your advice. [40:02] We kind of went on a really important [40:04] tangent, but let's summarize what's [40:07] still true about giving away your Legos [40:10] and then we'll talk about what's no [40:11] longer true. So, I'll summarize briefly. [40:13] Took some notes as you were talking. So, [40:15] still true. Um, change is scary. That's [40:18] normal. [40:20] Understand that. It's it's part of human [40:22] nature. We don't like change. Uh, [40:24] learning over knowing still a very [40:26] important thing to focus on. It's okay [40:28] if you don't know, but if you're focused [40:30] on learning, you'll be probably okay. [40:32] This idea of standing still at [40:34] successful companies is actually you're [40:35] falling behind. The company's growing. [40:37] If you're not growing and taking on new [40:40] challenges and giving away stuff, you're [40:41] going to fall behind. Is there anything [40:43] else core to kind of what's still [40:45] >> Yeah. I think I would just add one which [40:48] is change is scary and hard and the best [40:52] thing you can do is lean into it, right? [40:54] It is not what your instincts tell you [40:56] to do, but it is actually the best thing [40:58] you can do in the face of change. And [41:01] that was the message of Legos, you know, [41:02] basically like you need to lean into [41:05] this comfort of change in order to grow. [41:07] And I think it is still true today, even [41:09] if it is maybe even scarier than it's [41:11] ever been. [41:12] >> This season's supporting sponsor is DX. [41:15] Now that everybody at your company is [41:17] finally using AI, the question that [41:20] engineering leaders face is no longer [41:22] are we using AI, but is it paying off? [41:25] With DX, you can measure and benchmark [41:27] the impact of AI adoption across your [41:30] full product life cycle. DX shows you [41:32] where AI is helping developers and where [41:34] it's creating new bottlenecks. You can [41:36] also use it to evaluate AI vendors, [41:38] monitor costs and licenses, and see [41:41] exactly what's limiting your agents. [41:44] That's why hundreds of enterprises, [41:46] including Snowflake, Sony, and BNY, use [41:49] the DX platform to measure AI's impact [41:52] on developer productivity. Visit [41:54] getdx.com/lenny [41:57] to get a demo of dx. That's [41:59] getdx.com/lenny. [42:02] Okay. So now what is what is different? [42:04] Uh the advice broadly is okay give away [42:07] make yourself redundant. It's going to [42:08] be okay. Uh [laughter] [42:10] >> I know that's the one that's hard to [42:12] talk about today. Yeah. Make yourself [42:15] irrelevant everybody. It's gonna go [42:17] great. [laughter] [42:20] Um yeah. You know, it's funny like when [42:22] I when AI first really took off and I [42:25] first took me a while to really [42:27] understand what was going on in total [42:28] honesty. I was a skeptic for a while [42:30] where I was like we've been automating [42:31] things for a while. What is this? Um but [42:34] eventually I I got on board and all of a [42:37] sudden I was like oh you know that thing [42:39] I used to do before I went to give a [42:40] speech at someone's company where I was [42:42] like how how fast is your headcount [42:43] growing? For me that was like the only [42:45] symbol I had of like are there people to [42:47] give Legos to? you know, if I'm gonna [42:49] get up on stage and be like, "Give away [42:50] your Legos." A lot of times people are [42:51] like, "Wait a minute. We're not hiring [42:53] anyone. Like, who do I give it to?" And [42:55] but now I was like, "Oh, okay." Like, [42:56] this message is like even more relevant [42:58] because like everyone can try to [43:00] automate parts of their job and everyone [43:02] can [43:03] give Legos away. And I will tell you, it [43:08] has been an interesting journey [43:10] realizing how different it is to give [43:13] things away to robots than it is to give [43:16] them to a human. And you know, [43:18] principally the point was like of Legos [43:21] was like you take this thing you've been [43:23] working on and you fully hand it to [43:26] someone else. One of my favorite [43:28] questions that I get asked at companies [43:29] when I do the Legos talk is what is the [43:33] best way to give Legos away to someone [43:36] else? And I love it because I think [43:38] basically people expect me to be like, [43:40] "So, you should incredibly carefully [43:43] hand this Lego to this person and [43:45] explain to them exactly why you put it [43:47] in the position you put it in, you know, [43:48] like perfectly describe your tower. Make [43:51] sure they have like an instruction [43:52] manual that they won't [ __ ] up." And my [43:54] answer is actually no. The best way to [43:56] give Legos away is to chuck them at [43:58] their face and run in the other [43:59] direction [laughter] [44:01] because our tendency again is towards [44:04] control. Like our tendency is to be like [44:07] you will build this tower exactly how I [44:09] built it and you will not mess it up. [44:11] But actually like the point is no you're [44:13] giving it away. You need to fully [44:14] separate your mind. You need to just [44:16] hand it to them and trust that the [44:18] future of whatever that tower is belongs [44:21] to them. Um and there is both obviously [44:24] like a lot of fear and a whole bunch of [44:25] stuff that comes with that. But there's [44:26] a huge amount of freedom, right? You [44:27] take this brain space and you ship it to [44:30] them. Um, [44:33] interestingly, like one of my biggest [44:35] realizations was that delegating [44:38] something to a robot is not the same as [44:41] giving it to a human because you cannot [44:45] get rid of the oversight, right? Like [44:47] you it's more like delegating something [44:49] to someone on your team. You still own [44:51] it. And so we've given yes we've gotten [44:54] more efficient because the robots can do [44:55] X Y and Z for us but it's not the same [44:58] as giving it away to a human because we [45:00] still own the oversight. We still own [45:03] the sort of final product and that means [45:06] the mental tax stays with you. So like [45:09] yes in some ways I can do more but [45:12] psychologically I still have all the [45:15] burden of all the stuff that all the [45:18] robots are doing you know and I think [45:20] that does make it quite different [45:23] because it just means you don't have as [45:26] much space to then go on to the new [45:29] things right you're still you've still [45:31] got all the tax of the cost of oversight [45:33] is not zero do you know what I mean [45:34] again I wonder if if this is part of [45:36] what's going on with some of your [45:38] burnout data [45:39] is just like all of a sudden I'm [45:41] overseeing all these robots and maybe [45:43] all these humans and like it's not it's [45:45] it's it's more and um so anyway I think [45:49] that's one of the biggest differences is [45:51] just like [45:53] it isn't exactly the same. It's like the [45:55] difference between like transferring a [45:57] Lego to someone where you genuinely get [45:59] rid of it versus like delegating a Lego [46:01] to someone. It's so funny the way you [46:03] described it where you you need to not [46:05] be you need to disconnect from the [46:07] responsibility of this thing now and [46:09] it's the opposite now where somebody [46:12] else is doing this the AI but you're [46:14] still responsible. [46:15] >> Yeah. And so it's like having this Lego [46:17] tower with this little robot coming [46:18] through and okay, I'm going to build I'm [46:20] going to work on this now, but you're [46:22] it's you still have to represent this [46:24] tower to your boss. [46:26] >> And so I could 100% see this metaphor [46:29] clear. [46:30] >> If you're a manager, it's a familiar [46:31] feeling, right? Your team got twice as [46:33] big and now you just have these weird [46:35] little robots that occasionally like [46:36] [ __ ] up the tower and you have to be [46:37] like, "No, no, no, no, no, no. That's [46:39] not what I said." You know, which is [46:40] like again managing an intern. Like you [46:42] get it. But if you're not a manager, [46:44] like if you've never been a manager, and [46:45] I do think it's important to name that [46:47] like like I said, like managing robots, [46:50] those skills are very similar to [46:52] managing human humans. They have less [46:54] feelings, but you know, it's all the [46:56] same skills of like oversight and, you [46:59] know, giving them context and correcting [47:00] their work and coaching and like all [47:02] those skills are the same for managing a [47:05] robot um as they are for managing a [47:07] human. And a lot of people don't like [47:09] that [ __ ] Like so many people actively [47:12] like chose not to become a manager. Do [47:14] you know what I mean? And so there is [47:16] exhaustion that comes with if you [47:18] haven't you know if you don't enjoy [47:20] delegating if you haven't worked on all [47:22] these skills for many many years like [47:25] then suddenly you are in that stance of [47:27] management but it also just I mean it [47:29] just means literally everyone in the [47:30] world is a manager now you know and um [47:33] all you're doing when you're delegating [47:34] to robots is delegating just like you [47:36] would to another human on your team. So, [47:38] you know, I always say the happiest the [47:40] max people should be managing is like 10 [47:42] to 12 employees. Like I've I've managed [47:44] bigger teams than that and it was not a [47:46] good look. And I don't think there's any [47:48] data that says that people can manage [47:50] more than that now. And if you count [47:52] robots, like I'm worried for people's [47:55] like psychology, you know what I mean? [47:58] Um in terms of like the amount you have [48:00] to hold in your head. [48:01] >> Yeah. I build a lot of random stuff and [48:04] I have all these different agents [48:05] running and on the one hand it's so [48:08] awesome and all these things get done [48:10] and it's just like wow look at this [48:11] thing go I did all these things and then [48:12] also I get pinged all day from all these [48:15] guys they're like what about this okay [48:17] oh I'm stuck here oh is this good and [48:18] I'm like okay I got to look through this [48:20] all actually so I work with an actual [48:22] human engineer also and I'm just like it [48:25] makes you appreciate a human awesome [48:26] engineer that you could just give a [48:28] rough idea to and they could run with it [48:30] and do an awesome [48:32] versus this sucks. Okay, let's try again [48:34] and then sit there for five minutes and [48:36] wait. [48:36] >> Uh so yeah, [48:37] >> it is the difference between managing [48:39] junior employees and managing senior [48:40] employees. Do you know what I mean? Like [48:42] AI right now pretty junior employees. [48:44] It's not my favorite form of management. [48:46] I always say like give me the high [48:47] performers, give me I can turn them into [48:49] these incredible rocket ships. Like [48:52] managing interns, managing like folks [48:54] that are brand new to the workplace is [48:56] pretty tiring. And I do think that is [48:58] like what it feels like managing AI. And [49:00] it's so different, like I said, than [49:02] like throwing a Lego at someone and [49:03] running the other direction, which you [49:05] can do with your senior engineer, you [49:06] know? [49:07] >> Such a good point. Okay, we'll get to [49:09] like actual advice. Here's what you [49:10] should probably do. But before we get [49:12] there, what else is different about the [49:14] original advice around giving away [49:16] Legos? The first one, so good. Just like [49:19] uh you made it so obvious why it is very [49:21] different to give your Legos away to a [49:23] machine because you're not actually [49:23] giving away a they're just going to do [49:25] the work and then you're still [49:25] responsible for it and you have to [49:27] oversee it. [49:28] >> Yeah. Yeah. And I think the second thing [49:30] that's really different and we sort of [49:31] talked about a little bit already, but [49:33] like my message was always like you give [49:37] things away because the only way you can [49:39] make space for new opportunity is by [49:42] giving things away. Do you know what I [49:43] mean? And like that has two assumptions [49:46] under it. One that it's good to give [49:47] things away and two that there's new [49:49] opportunity on the other side. Um, and I [49:52] think this, you know, what I talked [49:56] about with the fear narrative is one of [49:58] the things that's driving me nuts in the [50:00] world, and we talk about it a lot in [50:01] Glue Club is just this dominant [50:05] narrative that like all these jobs are [50:07] going away because of AI and, you know, [50:10] all these layoffs that are branded as [50:11] AI. like that is not going to support [50:16] anybody being in a stance of like yeah [50:19] let's like delegate everything to these [50:21] robots let's give them every piece of [50:23] you know our brain and our data so that [50:25] we can have all this new opportunity [50:28] that's coming along like I think it is [50:30] the hardest conversation to have right [50:32] now and in you know to your point about [50:35] like there's lots of people out there [50:36] that are really excited there are and I [50:39] want that for everyone because this is [50:41] like an incredible moment like you know [50:44] I've been in technology for almost 20 [50:46] years and um I've seen a lot but like [50:50] this is this is one of those moments [50:52] this is you know the mobile phone on [50:54] steroids where it's like all sorts of [50:56] businesses are going to be created I'm a [50:58] believer that a lot of jobs are going to [51:00] be created because of this technology [51:02] but I think we got to start having that [51:04] conversation in order to get to the [51:07] place where everyone can be leaning in [51:09] right everyone can say oh it's great to [51:11] automate all these tasks that I hate [51:13] because it gives me more time to do the [51:14] things that I love, you know, which is [51:16] like I think to your point about the [51:17] people that feel amplified by it, it's [51:19] like, oh, I don't have to do all this [51:21] boring ass work. I can just focus on the [51:23] things that bring me joy, right? I can [51:25] focus on the things that I'm great at. [51:27] That's what we want. But while there's [51:29] this narrative out there that, you know, [51:32] media companies are propagating that [51:35] says like there's nothing for you on the [51:36] other side. Do you know what I mean? [51:38] We've we got universal basic income. [51:39] Everyone needs to be supported by the [51:41] state because no one's going to have a [51:42] job in 10 years. Like, who the [ __ ] [51:45] wants to give Legos to robots if that's [51:48] the narrative? No one. [51:50] >> I went to this um thing called food [51:52] camp. Have you heard of food camp? [51:54] >> I've heard of it. [51:55] >> Tim O'Reilly who started Orley Media, [51:58] awesome, smart guy. He came up with web [51:59] 2.0 is a concept. uh he organizes these [52:02] little kind of intimate camps where he [52:04] invites people that he thinks are you [52:06] know can contribute to this conversation [52:08] um to talk about all like a topic and [52:11] this last one is around just like what [52:13] happens with humans when AI does more [52:15] and more of our job and it started with [52:17] him talking to some I think it was a [52:19] lawyer who's just like okay I'm hoarding [52:23] this very specific knowledge I have [52:25] about doing this job so that AI cannot [52:28] do it it's like I need protect it [52:30] because otherwise I'm I'm going to be [52:32] replaced. They don't need me anymore. [52:34] >> And I feel like a lot of people are [52:35] probably feeling that. A lot of specific [52:37] niche professions especially. [52:38] >> Yeah, absolutely. And I go back first of [52:41] all, yes, of course. Like, how could you [52:43] not be feeling that way? [52:46] I don't know. Maybe I'm an abundance [52:48] person and maybe I'll regret saying this [52:50] in six months or five years, but I'm [52:53] like every piece of data I have from my [52:56] entire life and you know some of these [52:58] convers conversations I've had like the [53:01] one with Minute say you got to lean in. [53:04] You know what I mean? That protection [53:06] and holding on and gripping to what you [53:09] know is not the way you thrive in [53:12] change. Um it's not the people that [53:14] define the future. And you know again [53:17] the minut story would say lawyers are [53:20] always going to exist. They are going to [53:22] look completely different in every six [53:25] years or every three years or whatever. [53:27] So what do you think the next version of [53:30] a lawyer looks like? Do you want to be [53:31] part of designing that? Do you want to [53:33] be part of creating that? Do you want to [53:34] be part of figuring that out? Or do you [53:36] want to stay here and try to protect [53:38] what you know? And this is I think you [53:41] know that's to me [53:43] again like it's scary out there right [53:45] now. So I don't want to undervalue that [53:47] but I think you have to take that stance [53:49] of you know agency or we got to use a [53:52] different word entrepreneurship you know [53:53] like you got to take that stance of I [53:56] want to be part of designing the future [53:58] of my profession not protecting the [54:01] past. I I really really love this [54:04] framework as like almost a maybe that's [54:06] a big part of the advice from this [54:08] conversation is uh this uh way of [54:10] thinking from minutes is like my job [54:13] will be different but it'll continue to [54:14] exist and and the question is just what [54:16] will it be and let me think about that [54:19] lean in like prepare for that almost and [54:21] not try to resist because like resisting [54:23] is not going to work anyway. [54:24] >> Yeah. And if you listen to Minutiae's [54:26] story, like it's such an entrepreneurial [54:29] story and and I know that not everyone [54:31] is great at that. Um but it is very much [54:34] the like let me try this next. It's just [54:37] like but it comes you know for her it [54:40] just I think it was founded in this [54:41] belief of like this profession is [54:43] evolving and changing and I want to be [54:45] part of defining the future of it you [54:47] know and I again I think that's [54:50] until the data genuinely tells us [54:52] otherwise like I would say that is the [54:54] stance I would take particularly in tech [54:57] what would you do if you believe there [54:59] were going to be more and different [55:02] interesting engineering jobs you know in [55:04] five years um How would you behave if [55:08] you believed there was opportunity on [55:09] the other side of letting go? [55:11] >> Well, let's see if there's more to that [55:12] thread because that's that's really [55:13] helpful, which is okay. This is going to [55:16] go great. My product managers will [55:19] thrive. There will be more need for [55:20] product managers because a lot of [55:22] listeners here are PMs, engineers, [55:24] founders. Um, so what do you think [55:27] people should be trying to do in that [55:30] world where there will be more? Is it [55:31] like pay attention to how you're [55:34] amplified? Is it look at people who are [55:36] doing great and do what they're doing? [55:37] Like what what do you think people could [55:39] be doing to succeed in that future? [55:41] >> It's funny. We had a conversation. We [55:43] run these um my team and I run these [55:45] like top talent cohorts at companies and [55:48] um a lot of what we do is like get [55:50] leaders talking to each other and [55:51] helping each other. And this woman who [55:54] is a head of design brought this problem [55:56] where she was like they won't let me [55:58] ship code. She's like I I did it. like I [56:01] basically built the thing and I was like [56:03] just let me let me get it to production [56:05] and she was like talking to engineering [56:07] was like a brick wall you know where [56:09] they were like no you can't ship code [56:10] like you're you're a designer I'm an [56:12] engineer like I own what goes to [56:13] production and you know there are good [56:15] reasons for not letting things go [56:17] willy-nilly to production you know [56:20] particularly if you work in the [56:21] financial space which they did like I [56:23] get it but I think so much of the stance [56:26] is we got to break down some of these [56:28] walls uh between you know what is [56:32] what was a designer right what was a [56:34] engineer what was a PM this is obviously [56:36] like a lot of what's happening but how [56:39] do we really shed what we knew which [56:41] again is hard it's hard to let go of [56:43] those Legos you know what I mean um and [56:47] imagine okay what does it look like you [56:49] know this is why I think the startup [56:51] land is so happy is because they're not [56:53] fighting against the way things were [56:55] they're inventing the way things could [56:57] be and how can you make more space for [57:00] that inside of a company. Um, to me is [57:03] the is the number one thing I talk about [57:04] when I go, which is like [57:07] if if you're not leaning into the [57:09] creativity conversation versus the fear [57:11] conversation, like you are leading folks [57:15] who are just terrified, right? like how [57:17] do you get people to into a stance of [57:20] like I'm excited and I'm I want to try [57:24] things and I want to like tenatively let [57:26] this designer ship code to production, [57:28] you know? Um so to me like I think how [57:32] can you imagine a world with less walls? [57:35] How can you get rid of some of those [57:37] walls that have felt so important, you [57:39] know, for the way we've done things for [57:41] the last 15, 20, 25 years? Um I think [57:45] that is a conversation that a lot of [57:47] folks should be having [57:49] >> just along those lines just to be clear [57:50] is the idea here. Okay, I have been a [57:52] designer my whole life is the advice [57:54] there. Okay, like maybe I'll be [57:55] something else in the next few years [57:57] that's not just designer. No, I feel [58:00] like a lot of your conversations [58:02] >> are pointing I mean like I think Adam [58:04] Miseri was on here who I worked with [58:06] many years ago and was a designer and [58:08] he's saying like hey we're you know the [58:10] idea that like you're a designer and [58:12] therefore you only do these things [58:14] that's obviously changing right now you [58:16] can prototype you can have a much more [58:17] robust and deep conversations to some [58:19] extent you know you can ship code like [58:21] Elena Varna was talking about being a [58:22] marketer and shipping code to production [58:24] so to me they're just like were these [58:26] very defined roles um and a way that [58:30] things worked and we got to shed a bunch [58:32] of that because things are possible now [58:35] that weren't possible before and that [58:37] you know like when you listen to [58:38] Minutiae's story so so much of what [58:41] she's talking about is like the only [58:43] form of journalism used to be like [58:45] sitting in a newsroom employed by you [58:48] know some giant news corporation like [58:51] you think about journalism today like [58:53] everybody's a journalist like Substack [58:54] and part of what she talked about is [58:56] like the crazy thing is your [58:58] relationship to the business model. Like [59:00] again, it used to be a paycheck and now [59:02] it's like every journalist is an [59:04] entrepreneur. I just can imagine a lot [59:06] of those transformations in tech, but [59:09] you have to be willing to break down all [59:11] the walls and start asking the questions [59:13] of like fundamentally what is journalism [59:15] fundamentally what is design like [59:17] fundamentally what is product management [59:19] which by the way is a question that we [59:20] all should have been asking for many [59:22] many years because it looks really [59:23] different at different country companies [59:25] you know and I feel like that should be [59:27] true of every single person which is [59:29] like what is the value of all these [59:30] different roles when you strip away a [59:32] lot of the stuff that we've built up and [59:35] then what might it look like, you know, [59:37] in five or 10 years. [59:38] >> Here's the big question, Molly, that I [59:40] think a lot of people are wondering. Are [59:42] there any Legos you should not give away [59:44] that you should resist giving away? [59:47] Which is a radical departure from your [59:49] [laughter] advice over the many years. [59:51] >> Totally. I know as we were preparing for [59:53] this um I was realizing that's like the [59:56] biggest difference like when people [59:59] again so the questions I get asked a lot [60:01] like both online and when I give [60:03] speeches and stuff like one of them is [60:05] have you ever regretted giving a Lego [60:07] like do you ever is there something you [60:10] shouldn't give away and in the in the [60:13] context of sort of like the rapid scale [60:14] company where opportunity is flying at [60:17] you and getting dumped on your head my [60:18] answer is no give them the [ __ ] away [60:20] like you you cannot often imagine what [60:23] is coming next. Like you can't always [60:24] design the future and it's not always [60:26] clear. Sometimes you are genuinely [60:28] giving away the known and stepping into [60:30] the unknown. Um but it has basically [60:33] always been a good idea in every [60:34] example. I've seen both personal [60:36] experience and you know everyone I've [60:37] worked with and coached over many many [60:39] years in AI land. I think we got to [60:42] caveat this. Like I think there are some [60:45] Legos that [60:47] shouldn't be given away. um that the [60:50] robots like [60:52] both like don't deserve and like that we [60:55] should hold on to. And I think that is [60:57] like one of the things that's starting [60:58] to show up in this conversation around [61:00] AI slop is like um there's just some [61:03] work that shouldn't be outsourced. Like [61:05] my fervent hope for AI is that it lets [61:07] us do less of the things we shouldn't [61:08] have been doing in the first place and [61:10] more of the things that you know humans [61:13] are best in the world at, right? Like um [61:16] anybody that's RI ridden in a Whimo has [61:19] this experience of like whoa this is [61:22] crazy. Humans shouldn't be driving. Like [61:25] driving is fundamentally just like code [61:27] and systems and we're really bad at [61:29] [laughter] we're really bad at being [61:30] automated. Like we don't stop at the red [61:32] lights. You know what I mean? Uh so I [61:35] think like what are the what are the [61:36] things that we're uniquely suited to do? [61:39] Those are the things we should hold on [61:40] to. And some of that is inside this slop [61:43] conversation which is things that [61:44] require judgment, right? Things that [61:47] require like again to the CEOs that are [61:50] asking AI for a strategy and then [61:52] copying and pasting it and sending it to [61:53] their company like no like that is [61:57] fundamentally something that a human [61:59] brain that you as a CEO of your company [62:01] need to own, right? And I think things [62:04] that require trust like that are you [62:07] know fundamental to relationships like [62:09] we should not be outsourcing these [62:11] things to robots because well for any [62:15] number of reasons I think you know [62:17] things where you don't even if you don't [62:19] know the definition of good how can you [62:21] give it to your summer intern you know [62:23] like if if you don't understand uh what [62:27] quality is like you can't outsource that [62:30] yet. So those are just examples for me. [62:32] I bet you have some too. But that to me [62:34] that is one of the biggest like things [62:37] I've been thinking about lately is like [62:40] as of today I think there's some stuff [62:42] we just shouldn't give away you know and [62:44] >> breaking news. That's like what a [62:46] departure from from this how many years [62:49] ago did you write this? 13 years. [62:51] >> Yeah. 13. [62:52] >> Wow. That's um that's something that's a [62:55] sign of the change we're living through [62:58] that now there's some [62:59] >> Hold on to some of them. [laughter] [63:00] >> Yeah. So interesting. There's a few [63:03] thoughts I had here while you were [63:04] talking like this is almost a discussion [63:06] around what should AI do? Where do you [63:09] want AI to be involved and where you not [63:11] want it involved? One framework I've [63:14] loved is this idea of you want AI kind [63:17] of in the middle of stuff. you want to [63:19] be at the top like coming up just like [63:21] here's kind of where we want to go and [63:22] here's the idea here's the what I'm [63:24] thinking and then AI does a bunch of [63:26] stuff and then you review iterate until [63:28] it's done [63:29] >> sandwich [63:30] >> the AI [63:32] >> sandwich Lenny [63:33] >> the human sandwich [63:35] >> yeah dude [63:36] >> oh man [63:37] >> okay we're getting there we're getting a [63:38] metaphor [63:38] >> answer the other is something Tara I [63:41] just thought of as you were talking so [63:42] Tara shared this really good perspective [63:45] that humans are going to ne are going [63:48] be necessary to to help guide us towards [63:52] the world. We want to have a product we [63:55] want to build versus the most optimal AI [64:00] version. I think as a longtime Airbnb [64:02] person, uh, no, nothing personal, but [64:05] Booking.com, if you've seen it, very [64:07] different experience than Airbnb. [64:09] Booking.com, their whole philosophy, [64:11] let's optimize the [ __ ] out of every [64:13] second of interaction. So, it's just all [64:15] these upsells and pressure and stress. [64:17] Just like, "Oh my god, only one spot [64:18] left. You have five seconds left. Just [64:21] book a 100 times. 100 people book it." [64:23] It's just like stressful. [64:24] >> It's so stressful, but so effective. You [64:26] go there, you're like, "Oh [ __ ] I got [64:27] to book this right now." [64:28] >> You're like, I didn't even know I was [64:29] booking it, but I booked it. [laughter] [64:30] >> I'm going to Japan. There's only one [64:33] spot left. [64:34] >> But it's so good. It's like so effective [64:36] at getting you to book uh booking.com [64:38] appropriate, but and it worked and it's [64:41] doing great as a business. So, you know, [64:43] good idea. Good stuff, guys. Uh, Airbnb [64:46] has always been we don't want to become [64:47] that. We want it to feel really nice, to [64:50] have a great experience, feel feel good. [64:53] Um, so I think that's that's a big part [64:55] of the answer as you were talking made [64:56] me realize is humans are there to guide [64:59] towards what the world we want. [65:01] >> Yeah. And to some extent where you're [65:02] talking about is taste, you know, that [65:04] like there is a big difference between [65:07] something that's okay and something [65:09] that's phenomenal. I think it's even [65:11] beyond taste just a I think it's like a [65:13] vision. It's like what is your vision of [65:15] where this should be? Because you could [65:16] say, you know, people at booking.com, [65:17] they have taste for a specific type, you [65:19] know, it's like a different kind of [65:20] taste. [65:22] >> But it's like, yeah, what is what do you [65:24] want? What do you want to be? [65:25] >> What do you want the world to look like? [65:26] I like that. I'm into that. [65:29] >> Yeah. I also just think like we got to [65:32] accept that at least for the moment like [65:34] this is a bunch of interns, you know? [65:35] This is a bunch of junior employees. And [65:37] like if you're if you're outsourcing [65:38] your vision or the future of the world [65:41] to a bunch of summer interns, like woof. [65:43] like we got problems, you know. So, like [65:45] I think I that really like the human [65:48] brain is powerful at a lot of things. We [65:50] are powerful at a lot of things. You [65:52] individually are phenomenal at a set of [65:55] things. Like do not outsource that. Like [65:58] you can enable it, you can amplify it to [66:00] use your data, but don't outsource it to [66:02] these weird robots that you know are [66:04] effectively summer interns. [66:06] >> The trick is as it gets better, can you [66:09] hold on to things you want? You know, [66:11] there's like parts of our job we love. [66:13] Like engineers used to like, you know, [66:16] in like a lot of engineers used to love [66:18] to sit there and kind of write our code, [66:20] I think. And I wonder if you can hold [66:22] out and just like, no, I love this. I'm [66:24] not going to let AI take this on. [66:26] >> Yeah. I have two reactions to that [66:27] because I've been thinking about it a [66:29] bunch uh since I had that conversation [66:30] with that engineer. Like the first is [66:33] like will there be a a sort of like [66:37] whiplash back? Like you see this in art, [66:40] you see this in a lot of things actually [66:41] you see in a lot of different parts of [66:43] tech where like the trend is like all AI [66:46] everything AI will there be like the [66:48] handmade like somebody was talking to me [66:50] about like AI is going to make all this [66:51] art and but does doesn't that increase [66:53] the value of like true humanmade art you [66:56] know that you know it was made by a [66:57] human that you know it was crafted by [66:58] hand like I have that same question I'm [67:01] not an engineer so I I'm not trying to [67:04] to say this but like will something show [67:08] back up where the value of human written [67:10] code or something like that suddenly [67:13] gets valuable again or trendy. [67:14] [laughter] Um so I'm curious about that. [67:17] Um because I've seen those whiplashes [67:20] enough times in life that um it's hard [67:23] sometimes to know like what's a trend [67:25] and what's permanent particularly in [67:26] this state. [67:28] Um, but I guess the other thing that I [67:31] think about a little bit is like yes, [67:34] you loved that and yes, you were [67:36] extraordinary at it and that is amazing [67:38] and we should grieve it. We should [67:41] grieve that maybe that's going away and [67:44] you know there's this guy Chip Connelly. [67:46] What am I saying? You know him well [67:48] >> who I yeah he's coming on work life soon [67:51] and I loved the conversation with him. [67:54] He was talking about like midlife but he [67:55] was saying like sometimes you need to [67:56] throw a funeral for things. Do you know [67:58] what I mean? And I was like, "Yeah, man. [68:00] Sometimes you need a The funeral is [68:01] there for a reason." Um, so like, let's [68:04] take a minute and mourn what was, but [68:07] then let's ask what could be like what [68:10] could you love that way again? What [68:11] could you be extraordinary at that way [68:13] again in this new world if the robots [68:16] are doing X, Y, and Z? And I think both [68:18] things can be true. Like you can be [68:20] really sad about what you've lost and [68:23] there can be opportunity in what's [68:25] coming. Um, but we got to be able we got [68:28] to make space for both, you know, and I [68:31] think sometimes we're not allowing the [68:32] grief because uh we're just like just [68:35] get excited about the future people. [68:37] >> Such a powerful way of thinking about [68:38] it. Just accepting it is going to change [68:42] and just like grieving it. That was [68:45] nice. That was a nice world I had. [68:48] >> I miss it. [68:48] >> Maybe I didn't appreciate it as much as [68:50] I should have. [68:50] >> Totally. [68:52] but then not fighting the change that is [68:54] coming. And I love this idea of just [68:57] like coming back to the original idea of [68:59] the Legos concept is being comfortable [69:01] with ch your job changing and knowing [69:06] it'll almost surely be okay and growth [69:09] comes from trying letting go and and [69:13] that kind of stuff. Another thought I [69:15] had as I'm thinking about this, [69:16] something I've been noticing. So, you [69:17] know this whole like hacking this like [69:19] open AI model trying to hack into [69:20] hugging face and the swarm of thousand [69:22] agents just coordinating without anyone [69:25] knowing just like we will solve this [69:27] very impossible problem by [69:29] >> interns. [laughter] [69:30] >> Very very very uh motivated interns. [69:33] >> Yeah, exactly. [69:34] >> I love how motivated this AI is to like [69:36] solve the problem. Yeah, I'm gonna uh [69:40] the good news I'm feeling there's always [69:42] this question of we talked about this in [69:43] the last podcast this idea of are we [69:44] going to be in a slow takeoff or a fast [69:46] takeoff. Are we going to get to an AI [69:48] that just accelerates to this extremely [69:52] super intelligent and then we are in big [69:53] trouble because we have can't control it [69:55] or are we going to be in the slow [69:56] takeoff where we kind of watch it [69:58] develop and we catch it as it's doing [70:00] that stuff like we did with this hacking [70:03] incident. Feels to me like we're [70:04] definitely in the slow takeoff moment. [70:07] It feels like every of these like, "Oh [70:08] shit." We're just like, "Okay, look, we [70:10] got it. We see it. We're evolving. We're [70:12] learning." Obviously, there's always [70:13] this fear. Okay. But until it hits this [70:16] uh self reinforcement loop that trains [70:20] itself and then it becomes super [70:22] intelligent, for sure, maybe it'll [70:23] happen. Feeling right now it's not on [70:26] track to do that. And so that feels nice [70:29] to feel like, okay, it's not going to [70:31] your job's not going to go away [70:32] tomorrow. we have time to adapt and [70:34] learn and see how all this goes and it's [70:38] not as crazy as people thought it might [70:40] be. [70:40] >> Well, and I think that is really [70:42] important to name, you know, because [70:46] there was maybe more like three or four [70:49] months ago or six months ago than there [70:51] is now. But but there is this feeling of [70:53] being left behind, you know, and there [70:55] was a really strong narrative out there [70:56] that was like you're you're too late. [70:58] You're already too late. You know what I [71:00] mean? like um if you're not automating [71:02] every single part of your life and [71:03] managing 26 agents and I don't even know [71:05] you know like um that you're behind and [71:10] every single conversation I have with [71:12] every leader every manager at you know [71:15] all of the big labs every company is [71:17] like we are early this is like whatever [71:21] sports ball game you want to be in like [71:23] this is inning one period one like yard [71:26] one um [71:29] We're early and the the future is ours [71:33] to shape. You know, it's yours. Like you [71:35] can um my friend Max Mullen said like [71:39] the distance from beginner to expert is [71:41] really short. Um and and I think that [71:43] goes again to the fear narrative where [71:45] I'm just like we need to be encouraging [71:48] people to be part of shaping the future, [71:49] not just making them terrified of it. [71:52] And I feel like [71:55] that is on all of us, you know, to some [71:57] extent. Um but to it is a slow takeoff [72:00] and it isn't like the future is next day [72:04] next next month like it is it's going to [72:07] take years to really understand what [72:09] this new tool this new technology all [72:12] these fun interns can actually do and [72:15] and also what they're best at. Um, I [72:18] think that is a really powerful message [72:20] because it helps people feel like, oh, [72:22] okay, like I am part of this, not like [72:25] sort of holding on for dear life while [72:27] being dragged, you know, by a plane [72:29] that's taking off at 100 miles an hour. [72:31] >> I completely agree. My last podcast [72:32] conversation, I don't know when will [72:34] come out when, is is about this fear of [72:35] the permanent underclass that if you [72:38] don't catch up, if you're not on top of [72:39] this, you're going to be left behind. I [72:41] think there is definitely a part of that [72:42] in a sense of many companies are doing [72:45] extremely well and people that have [72:46] joined those companies are going to be [72:47] very successful and some companies [72:49] aren't and there's this like whole other [72:51] discussion around this the socioeconomic [72:54] divide growing significantly in the [72:56] world and just what what that causes in [72:59] a world where there are many wealthy [73:00] people many more than there have ever [73:01] existed that's its own thing we don't [73:03] need to get all into that [73:04] >> well I hope you do [73:06] >> okay [73:06] >> many episodes on that someday Lenny like [73:08] I think it's [73:09] >> but I it is another area where I'm like [73:11] I'm not sure we know what's real yet, [73:13] you know? I think it's obviously like [73:15] one of the most important conversations, [73:17] but like what is real and like what is [73:19] the future actually going to look like [73:20] to me? Like the stories out in the [73:23] world, they're not real yet. Like we [73:25] don't know. Um [73:26] >> it's true. [73:26] >> And I I think that's important to name. [73:29] >> Oh man, that's a that's a big big topic. [73:32] The the interesting part you mentioned [73:33] there's that I wanted to follow thread [73:35] on is this idea of you're not behind. Uh [73:38] what really helped me see this is uh Ian [73:40] Silber, head of design at OpenAI, was on [73:42] the podcast recently and he made this [73:44] really good point. He's like this is the [73:46] best time in history to be a designer. [73:48] If you just came in fresh as a new grad [73:50] into design and just become really you [73:53] just start with all these tools that [73:54] designers have now. You can accelerate [73:56] so quickly and learn to do design faster [74:00] than anyone's ever learned to do design. [74:02] And I feel that with like Rockbot [74:04] recently came out. There's all these [74:06] like skills people have built over time [74:07] with like codecs and cloud code. Like I [74:09] I'm such a pro with all these tools and [74:11] now it's just the tools are getting so [74:13] much smarter. You don't need a lot of [74:15] the scaffolding that people have built [74:16] over time. Like if someone were to start [74:18] fresh today and try Grockbot or even in [74:22] codeex like you don't need to have spent [74:25] years being on top of all of the news [74:27] and all of the uh updates to it. you [74:30] could just dive right in and build as [74:33] much as people that have been on it for [74:35] a long time can build. I feel like the [74:37] actual main skill to build, something [74:39] I've been thinking about, I tweeted [74:40] this, but I feel like it didn't get [74:41] enough traction because I think it's [74:44] very important. I feel like the biggest [74:46] skill to build right now is when you're [74:48] about to do something to ask yourself, [74:51] can AI help me with this thing? [74:53] Because once you get good at that and [74:55] I've been getting I that it's like I [74:57] think about the stimulus and response [74:58] kind of thing with meditation like you [75:00] create more space between stimulus and [75:02] response if you learn to be aware of [75:05] what's going on outside. feel like you [75:06] need to insert can AI help me with this [75:08] which sounds like dirty and like what [75:09] the hell why would you want AI but I [75:12] feel like that's a really new skill [75:14] because then you can start as these [75:17] tools get better you can start to [75:19] leverage them in all these different [75:20] ways that I think is what separates a [75:22] lot of people right now like oh [75:23] >> totally [75:24] >> and I um you know it goes to that point [75:26] about the walls like I think those of us [75:29] that have been around a long time and [75:31] there's a way that things were done [75:32] right there's a way that product was [75:33] built there's like um all these ways, [75:37] right? Those are walls. They're walls [75:39] that are old. And like part of what we [75:41] need to do and I think part of what [75:43] you're saying is like you're actually a [75:45] little bit in as an at an advantage if [75:48] you don't know those walls exist, right? [75:50] Like if you approach the world as if [75:52] like you know engineers didn't have a [75:54] different role from X or Y or Z or like [75:56] this is the way things are done. there [75:58] is an advantage to like being able to [76:01] say what if like what if I just did it [76:04] or what you know and to just try and to [76:07] your point to always think like hey like [76:09] what's the best use of my time and then [76:12] what you know could an agent or a robot [76:14] do for me and I think that's like [76:16] partially the point about the learners [76:17] right like if you're able to shed the [76:20] sort of things you think you know and [76:22] lean into like the possibility and the [76:25] first principles thinking which I know [76:27] you have a great article about too like [76:28] that that I think is going to define the [76:31] future. Those are going to be the people [76:32] that are going to shape what this thing [76:35] looks like. [76:36] >> Yeah. There's also a thread here around [76:39] ambition that's been coming up a lot in [76:41] the podcast kind of connect. [76:43] >> Yeah. This idea that now that it's so [76:45] easy to do whatever you want, just [76:47] describe it and it's built. [76:49] >> The thing that we need to in addition to [76:51] asking ourselves, can I help me with [76:53] this thing? [76:54] H what's kind of the like how do I be [76:56] more ambitious with this idea because [76:58] the tools can now just do so much and [77:00] they're just like waiting for you to [77:02] tell me something more ambitious than [77:03] that like that's all you got for me and [77:05] we're not human nature doesn't like [77:07] we're not used to end product teams and [77:09] business just like thinking about the [77:11] most ambitious version of a thing we're [77:12] thinking about MVP and what's the [77:14] quickest way to get this out and now [77:16] feels like the push is how do we be [77:18] think big what's like the hardest thing [77:20] we can ask this a to do because it may [77:22] actually just achieve out of one ask. [77:25] >> Yeah. And I'd also nudge on the idea [77:28] that like, yeah, you can just like type [77:30] something into existence, but one of the [77:32] other questions you need to ask yourself [77:34] is like, is it good? Do you know what I [77:36] This is like the the slop and the [77:39] accountability thing, which is like, and [77:42] if ambition is wrapped up in like how do [77:44] I build something phenomenal that's [77:46] going to endure, like that I'm [77:49] interested in. If it's just like how do [77:50] I make more [ __ ] and put it out in the [77:52] world? Like one of my questions, this is [77:54] really frontier Lenny is like what is [77:57] the AI slop version of startups? Like [78:00] are we about to see a [ __ ] ton of [78:02] companies just shipping stuff out into [78:05] the world that's going to last for like [78:07] six or 12 months and then just disappear [78:09] or get irrelevant? Like [78:10] >> definitely. [78:11] >> So, okay, great. That doesn't sound fun. [78:14] like how can you be the pioneer of the [78:17] enduring thing the thing that's going to [78:18] still be around in five years you know [78:20] that's going to matter that's going to [78:22] be great um not just exist and again it [78:25] goes to the difference between just like [78:26] productivity right like I built a thing [78:29] and what is good like what is actually [78:31] worth it what's worth other people's [78:33] time [78:33] >> yeah I think that's a big [78:35] differentiating opportunity right now [78:36] instead of just shipping the thing fast [78:38] it's what's like a very good version of [78:41] this thing and and people see that [78:43] they're like oh wow this is different. [78:44] >> Yeah, exactly. I think that this goes to [78:46] the point of like what will matter when [78:49] it comes to human touch, you know, and I [78:51] I think a lot of that is going to come [78:53] down to like the question of like what [78:56] is good and what is worth it and what [78:57] endures. [78:58] >> Is there anything that we haven't [79:00] touched on that uh we should before we [79:02] try to summarize maybe some key lessons [79:04] from this free freewheeling [79:07] conversation? Well, the one thing I just [79:10] wanted to say is like [79:13] I was thinking yesterday because of a [79:14] conversation I was having is like what [79:16] what do I want every manager or leader [79:19] out there to know, you know? Um because [79:22] I think the world of the IC is honestly [79:26] a little more clear like you know you [79:29] are you are more productive and you have [79:30] all this this power and and agency [79:33] around um building and the world that [79:35] feels very hard to me right now is the [79:38] world of the managers and the leaders [79:40] because so much is changing so fast. [79:44] It's a little bit hard to know what to [79:45] tell people. It's a little bit hard to [79:46] know like what your team should look [79:48] like, what matters, what doesn't matter, [79:49] you know, all that. And so [79:52] I [snorts] guess like I wanted to say a [79:55] couple of things to the managers and [79:56] leaders out there if you'll give me the [79:57] sec. Like the first is like understand [80:00] that you're a role model, you know, and [80:02] that what you do and how you behave is [80:05] essentially showing your team um what [80:08] good looks like. And that means that how [80:10] you use AI trickles down, but also how [80:12] you sit in this moment, like how you [80:15] show up. And for me, what I want a [80:19] little more space for in the world is to [80:22] be able to acknowledge what this change [80:24] feels like. Um, I hope there's more [80:27] managers out there because of this [80:29] conversation talking about grief and [80:31] talking about the emotions that come [80:32] with change and talking about how hard [80:34] this is for people. Um, I think that [80:38] acknowledging what this rate of change [80:41] does to people's brains and [80:42] psychologies, like it just honestly even [80:45] acknowledging it makes it easier for [80:47] people. Like I said, I swear to God [80:49] that's most of what the Legos article [80:51] did is just tell people, hey, that thing [80:53] that you're feeling, other people have [80:55] felt it before you and it hasn't meant [80:56] that everything is going to hell in a [80:58] hand basket. You know, it's meant, oh, [80:59] you're going through a lot of change [81:01] really, really fast. Um, and it's scary [81:03] and hard. So the more that like leaders [81:06] can be talking about that, I think the [81:09] more sane everyone's going to feel and [81:11] less alone, you know, knowing that like [81:13] someone at XYZ company is feeling the [81:16] same way as you makes a difference. Um, [81:20] and I I guess the last thing I just say [81:22] is like I think everyone owns this to [81:26] some extent, but managers and leaders [81:28] more so. like [81:30] we need to hold on to the definition of [81:32] like accountability and what good means. [81:34] Like [81:36] I think that's part of the role modeling [81:38] like [81:39] what is right to give away to AI and [81:42] what do we still as humans and people [81:45] and workers need to own. Like we're [81:48] going to have to role model that and [81:49] we're going to have to create standards [81:51] for that. Um so that goes to your own [81:53] behavior but it also goes to how you [81:54] lead and how you talk about it. Like I [81:57] Clay put out like this beautiful AI [82:00] writing policy a couple um weeks ago I [82:04] think it was and it's so badass because [82:06] it's literally just talking about being [82:08] accountable for what you ship out in the [82:10] world and being accountable for what [82:11] good is regardless of how you made it. [82:14] And for today to me like that [82:19] feeling of treating AI as like a a [82:21] junior intern and realizing that it's [82:24] fundamentally just a tool to get work [82:26] done. But what matters is like the work [82:28] is still done mostly by the humans and [82:30] the human brains and we got to take care [82:31] of the humans and we got to help them [82:34] figure out how to navigate this wild [82:36] wild west that we are in. [82:38] >> I'm really glad you added that. It [82:40] connects to another really interesting [82:42] insight from the survey, which is that [82:44] the the one thing that you can actually [82:46] change to increase people's happiness [82:48] right now at work is their manager. [82:50] That's the strongest lever for happiness [82:54] at work. You can actually do something [82:56] about it. All this other AI stuff you [82:57] can't do a ton about. That's one. And so [82:59] it's and man, and most people's managers [83:02] are not good according to the survey [83:04] also. So it's [83:05] >> none of this is surprising. So [83:07] [laughter] taking care of the managers [83:08] is kind of a just a reminder that that's [83:10] you have a lot of leverage there as [83:11] well. [83:11] >> Yeah. Which by the way is like there are [83:13] trends inside of bigger companies to get [83:15] rid of management like to get rid of [83:16] whole management layers and I think it [83:18] is a huge mistake. Like I think it is [83:20] going to end up biting people in the ass [83:23] long term because [83:26] I see no signs right now that management [83:28] matters less. If anything to your point [83:30] I think it matters more. Um and uh you [83:34] know again I get the efficiency and the [83:36] cost savings and all that but I think [83:37] like at what cost you know what cost [83:39] that you can't predict. Um so I it [83:41] really resonates that management is [83:43] almost more important because it makes [83:45] people feel seen like that's what a [83:46] great manager does is make people feel [83:48] seen and supported and help them figure [83:50] out whatever mess they're in. You know [83:52] >> it's gonna be so interesting to see if [83:54] there's a backlash towards that like [83:55] like you know people have had great [83:56] managers they're they're rarely going to [83:58] be like I wish I had no manager. You [84:00] know, there's it's like people with bad [84:02] managers, which a lot of people are [84:03] like, "I don't need this person, but [84:04] they're they're so useless." [84:06] >> Yeah. They're in my way. They are a [84:07] wall. No, totally. I mean, I always say [84:09] you only get like a couple good managers [84:10] in your life, and when you find one, [84:12] hold on to it for dear life [laughter] [84:14] because you're only going to get like [84:15] two. [84:17] >> Oh, man. Scary. I've never heard that [84:19] advice before. [laughter] [84:21] Uh, anything else that you wanted to [84:23] share or touch on? [84:26] >> No, I feel like we I mean, it'll be [84:28] fascinating. We'll reflect on this in [84:30] six months and see what happen. [84:31] >> That's what I was thinking. [84:33] >> We're in the middle of it right now. [84:34] It's like Elizabeth Stone had a really [84:36] good way of framing it. We're in the [84:37] storming phase. [84:38] >> Yeah, dude. [84:38] >> And then there's the norming phase. [84:40] >> I know. [84:41] >> Like I have no idea what that actually [84:43] means, but it sounds right. Storming, [84:44] norming, and Yeah. [84:45] >> Well, there's storming, norming, and [84:46] then there's performing. But the other [84:48] thing that nobody tells you about that [84:49] framework is that you can go backwards. [84:51] Like you often go through cycles. This [84:54] is like a it's a model on team [84:55] development and [snorts] um you go [84:58] through storming and then you go through [84:59] norming and then you go performing, but [85:01] you can slip from performing into [85:02] storming and I feel like we're going to [85:04] see a lot of that. [85:06] >> Oh boy. Yeah. It's it's like very cool [85:09] to be living through this history, [85:12] >> right? It's like easy to take for [85:14] granted just how this is like it's like [85:16] we're living through, [85:17] >> you know? It's funny you say that cuz [85:19] that's actually something I else I [85:21] always talk about when I do these LEGO [85:23] speeches is like being inside of a [85:26] rapidly growing company feels like being [85:28] inside of a tornado. Do you know what I [85:30] mean? It's like it is so [85:33] absorbing and I don't know, shit's just [85:36] flying at you at all times and [85:37] everything's changing all the time and [85:39] it is so easy in that state to lose the [85:42] forest for the trees. like you can get [85:44] really bogged down or stuck in like [85:47] obsessing about this person or this [85:50] thing or feeling undervalued. And a lot [85:53] of what I say to folks in those speeches [85:55] is like you got to zoom out. You got to [85:57] think about what is the story that I [85:59] want to tell on the other side of this. [86:01] Like I want to, you know, it's less [86:03] about your title or all these things [86:05] than it is about I was here and I helped [86:07] build this. I talk about it as like a [86:08] giant Lego sculpture. So it's like [86:10] you're like let's pretend it's a tiger. [86:12] You're gonna you're gonna leave here [86:13] with this incredible story, right? You [86:15] built the feet and then you like were [86:17] part of building the face and then you [86:19] rebuilt the butt three times and then [86:20] you realized it like wasn't just a [86:22] tiger, it was like a whole zoo. Like [86:24] that is what it feels like to be inside [86:26] of um these rapidly changing companies. [86:29] And I wonder, you know, as you were [86:32] saying that, what I was thinking about [86:33] is gosh, imagine the stories we're going [86:35] to be telling in five or 10 years. Like [86:37] I was there when here's what I thought [86:38] that was right. Here's what I thought [86:40] that was wrong. I was the first person [86:41] to say this. Oh man, I was so wrong [86:43] about that. Like you are living through [86:46] history. Um that you will be telling [86:48] stories about uh to whatever you know [86:51] generation of new grads shows up in 10 [86:52] years. Um [86:55] what do you want your story your part of [86:57] that story to be? You know how are you [86:59] going to tell that story? I think there [87:00] is something about zooming out and [87:01] realizing like it is hard and there is a [87:04] lot of change going on, but there is a [87:07] crazy fun story that we're all going to [87:09] be telling on the other side of this. We [87:11] just don't know what it is yet. [87:12] >> Hopefully not just talking to our AGI. [87:15] >> Tell me more. Tell me more, Molly. [87:17] >> Totally. That's so fascinating. [87:19] >> Yeah, exactly. [laughter] [87:20] You're so smart. [87:23] >> Oh, man. [87:24] >> Okay, what if we do just like some [87:26] bullet points like takeaways for folks? [87:27] just like here's a few kind of key [87:29] things to keep in mind coming from this [87:32] giving away your Legos framework. Uh see [87:35] where your mind goes and then maybe I'll [87:36] add a few for my notes. [87:37] >> Okay. [87:39] To me like most important is change is [87:43] scary and hard but that doesn't mean [87:44] it's bad. That means you have to embrace [87:48] the emotions that come with it. But you [87:49] also have to lean into it and you you [87:52] should let go. Like yes, it's scary and [87:55] yes, it feels like there might not be [87:58] anything waiting on the other side, but [88:00] what's the alternative? To hold on to [88:02] this thing that might be slowly dying, [88:04] like that's not safe either. So leaning [88:06] into change [88:08] feels like to me the most important [88:10] thing for folks to take away. [88:13] Um, I think as part of that, I would [88:15] just say like grief is part of this and [88:19] sometimes grief needs a funeral or do [88:21] what you got to do, you know, to like be [88:23] sad. Let your teams be sad. Let the [88:25] people around you make space for that [88:27] because like there change with change [88:30] comes shedding things um that you loved [88:33] and that sucks. Um, I think like one of [88:38] the other things that feels like it [88:40] really came out, Lenny, is like there is [88:41] opportunity here. And we got to like [88:45] start ignoring or muting or whatever [88:47] some of this fear [88:49] narrative. Um, because right now the [88:52] data isn't saying like there are no jobs [88:54] for you. The data is saying like [88:56] actually there's going to be a lot of [88:58] opportunity created by this. [88:59] Particularly if you're willing to lean [89:01] into reinvention, right? what not what [89:04] was the form of your job two years ago [89:06] but what might it be in five years um [89:11] what else I guess like breaking down [89:13] walls is the other thing I was thinking [89:15] but what what what came to your list [89:16] >> well there's the minut kind of [89:18] perspective of imagine your job isn't [89:19] going to go away imagine your job will [89:21] continue but be different [89:22] >> yeah exactly I love I just it it was a [89:27] real mind change for me when she said [89:29] that because I was like whoa like yeah [89:32] What what is engineering going to look [89:34] like in five years? [89:35] >> Right. It's not going to go away. It's [89:36] going to be some different. [89:37] >> Maybe there'll be more of it. Like [89:39] journalism, there's more journalists out [89:40] there for better or for worse. [89:43] >> Yeah. And so far there's more more uh [89:45] PMs, more product more um engineers. [89:47] Yeah. [89:48] >> Like so far that's going well. Another [89:50] kind of takeaway is just be deliberate [89:51] about what you do what you give to AI. [89:54] And there's a few ways to think about [89:56] it. One is just like what is AI going to [89:57] do a terrible job at? Don't do that. [89:59] What is it you love that you don't want [90:01] it to take for you? How do you avoid [90:03] like brain rot and just overlying an AI? [90:05] It's like there's a few things there [90:07] just like AI is not gonna don't give [90:09] everything to AI. [90:10] >> Yeah. And I think also for a lot of us [90:14] acknowledging that AI is not this like [90:16] super intelligent being. It's like it is [90:18] much more like an intern. Um and that [90:20] means like literally think about it as [90:22] an intern. Like what would you give to [90:23] an intern and what would you never give [90:25] them? [90:26] >> I think that's the core of it. [90:27] >> Yeah. And I feel like well I feel like [90:29] we said this but like there just may be [90:32] some things we should never give away [90:33] and that is genuinely different like [90:37] give away your Legos but like be [90:39] discerning about what you should keep [90:41] and what should be human and what humans [90:43] are here for. Like I think that's part [90:46] of the like conversation for the next fa [90:48] you know however many years is like what [90:50] are humans uniquely good at [90:52] >> and what I think about there just like [90:53] very concretely in my mind is be the [90:56] person that guides what you're doing to [90:58] a place to your the vision you have of [91:00] the world you want not just the simplest [91:03] thing not the thing that AI is kind of [91:04] pointing to just like what do you [91:06] actually want and that's kind of our job [91:08] for a while [91:08] >> yeah and like at the individual level [91:11] how can this new tool this unintelligent [91:14] intern that you've hired, like let you [91:16] do more of what you love, you know, let [91:18] you bring more joy into the world. Let [91:19] you lean into the things that you love [91:22] doing. How can it amplify you? Um, [91:24] instead of feeling like all you're doing [91:26] is losing things to it. [91:27] >> What a moment in time we're in, Molly, [91:29] right now. [91:30] >> Trying to figure all this out. [91:31] [laughter and gasps] [91:31] >> We're going to rewatch this in a year or [91:34] two and make fun of ourselves. [91:35] >> Yeah, we're going to be We nailed it. We [91:37] got everything right. [91:39] >> Perfect. [91:39] >> Visionaries. [91:41] Oh, man. Well, with that, Molly, is [91:44] there anything else? Anything you want [91:45] to plug? Anything you want to point [91:46] people to? Anything you want to tell [91:47] people about that you're up to that [91:48] might be interesting, useful to them? [91:50] >> Well, I'll say two things. Like, first, [91:51] like um I get a lot of wisdom, but also [91:56] a lot of support for this kind of [91:58] conversation from the community and glue [92:00] club. And I think um if you're a leader [92:04] listening to this and feeling like [92:06] lonely and a little bit unsupported like [92:09] that is find a community whether it's [92:11] glue club or another one where you can [92:13] talk about this because I do think like [92:14] leaning on each other to learn like [92:16] what's real and what's not and what's [92:17] valuable and what's not like so much of [92:19] what we're doing in glue club is being [92:20] like is anybody else seeing this like [92:22] and that that is really valuable like [92:24] you can do it in in Lenny land as well [92:27] like but just get out there and talk [92:29] about what's real and what's not don't [92:31] just be stay in a sad lonely hole. But [92:33] the second thing I wanted to say, Lenny, [92:35] is thank you for making space for this. [92:36] I think it's important like there's so [92:39] much space right now for the like what [92:41] should I do and what you know what [92:43] skills should I get and what course [92:44] should I take and you know what tool [92:46] should I try next who's hot today but [92:48] like we aren't talking enough about the [92:51] human side of this and what it feels [92:53] like to be going through this for [92:55] everyone. And so I'm grateful that you [92:56] reached out and we talked about making [92:58] space to talk about this because I think [93:00] hopefully people will leave feeling a [93:02] little more like sane and like, oh, [93:05] everybody else is feeling a little crazy [93:06] right now, too. And there's lots of [93:08] people out there grieving and like [93:10] that's okay. Like that's normal. So, [93:12] thank you, Lenny. [93:14] >> Thank you, Molly. I think of these I [93:17] have a a term for these sorts of [93:18] episodes. I call them Trojan horse [93:20] episodes [laughter] where people come [93:22] for like all this tactical concrete. I [93:24] need to how do I use AI in this way? How [93:26] do I become a better PM? And then I get [93:28] there's these like [93:30] >> you get therapy [93:31] >> important episodes that slip right in. [93:33] Yeah, exactly. You're like, "Oh, okay. I [93:35] didn't know I needed that, but that was [93:37] very helpful." [93:37] >> Yeah. [93:38] >> So, well, welcome to the Trojan horse [93:41] smuggling in. [93:41] >> I love it. [93:42] >> Very timely with the Odyssey these days, [93:44] huh? [93:44] >> Yeah, dude. [93:45] >> All right, Molly. Well, thank you so [93:46] much for being here. [93:47] >> Yeah. Thanks for having me, Lenny. [93:49] >> Bye, everyone. [93:49] >> Bye, everybody. [93:51] >> Thank you so much for listening. 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