"A product engineer doesn't necessarily think about the front end or backend split. They think about everything that it takes to ship a feature and deliver customer value end to end. Across the entire product."

Is front-end vs. back-end an antiquated way to structure engineering teams? With AI augmenting skills, a new model is emerging: the product engineer.

This week, Andrew sits down with Lee Robinson, VP of Product at Vercel to crack open the future of the web. As a respected educator and voice in the webdev community (check out his YouTube!), Lee shares his unique perspective on building both cutting-edge tools and high-performing teams.

As the VP of Product, Lee charts the evolution of developer roles and illustrates for us the rise of "product engineers" who own features end-to-end. Learn how AI tools are not just augmenting specialists but enabling designers, PMs, and founders to build "personal software." We also cover changing team dynamics and get Lee's advice on navigating the hiring process in the AI era, including: why personalization is key for candidates, how managers can spot authenticity (hint: AI-generated cover letters are obvious!), and why building in public is critical for career growth today.

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Transcript

Andrew Zigler: 0:06

Welcome to Dev Interrupted. I'm your host, Andrew Zigler.

Ben Lloyd Pearson: 0:09

And I'm your host, Ben Lloyd Pearson.

Andrew Zigler: 0:11

This week we have the scoop on another AI mandate making waves in the industry, and a new competitor in the language learning space, along with some major restructuring and workforce changes at some pretty recognizable tech companies. But Ben, I'd say our first story, well, maybe it's more like a social story, not a new story. What's going on with you?

Ben Lloyd Pearson: 0:31

Yeah, I wonder if it's a representation of things to come. So I, I had a post on LinkedIn about fake accounts on the platform, and it attracted an AI bot that I interacted with. It was actually kind of cool.

Andrew Zigler: 0:42

Oh, weird.

Ben Lloyd Pearson: 0:43

Yeah. So, yeah, I mean, it just, it just started when like someone pointed a mean comment directed at me. And which, you know, I brushed those things off, but I looked at their profile and like immediately got suspicious.'cause it had some telltale signs of being a fake account. the biggest one being that they just use a stock photo, which I mean like, it's 2025 if you're gonna fake an account, at least get an AI generated profile picture, you know?

Andrew Zigler: 1:04

Ooh. Ooh. That, that's bespoke. So this account had a stock photo as its profile image, not something that's AI gen. Yes. Vintage. Vintage. I love that.

Ben Lloyd Pearson: 1:12

fake accounts.

Andrew Zigler: 1:14

Okay.

Ben Lloyd Pearson: 1:14

but, but you know, I made a post just like reflecting on this, I was like, wow, this is kind of weird, that somebody would, use this account. looks like they put effort into making it 'cause it had like 300 connections and whatnot. and it looked like it was a human behind it and not ai. But in the comment section on that post, there was this AI sales rep that showed up to call out the behavior of fake accounts. And I honestly found it to be hilarious because it self-identified as being AI powered. like this is a GPT generated comment and was calling out the practice of using fake accounts. Like it was really kind of incredible.

Andrew Zigler: 1:48

very meta, and this was happening on LinkedIn.

Ben Lloyd Pearson: 1:51

Yeah. And I'm like, I'm sitting there just like wondering like, are we

Andrew Zigler: 1:54

I.

Ben Lloyd Pearson: 1:55

entering a future where AI is inserted into every facet of our lives, whether we like it or not. Like so far, with this one bot, I'm okay with it because it was like this positive experience, but you know, I still withhold my, the right to change my mind on that one.

Andrew Zigler: 2:10

Yeah, I think this is a good call to action for the real humans listening to us now on the podcast. Go interact with Ben. That way he doesn't get buried underneath the hoard of robots on LinkedIn, please, we're, we're sharing cool stuff on there every week, and, we need other humans, you know, here hand in hand with us to help build real good content for the world.

Ben Lloyd Pearson: 2:27

They're gonna see that I'm someone that will comment back and engage with them, and then other ones are gonna show up, and that's all my fee's gonna become if I don't get more humans involved with this.

Andrew Zigler: 2:35

Yeah, I think that's definitely, sadly sometimes where things are going, but that's the value of a good, authentic connection, right? When you find someone you really jive with online and just sharing cool stuff with them. That's what I love about things like LinkedIn, just finding other people to nerd out about with.

Ben Lloyd Pearson: 2:48

yeah. Absolutely. So, so that's my, my personal AI news for the week. So let, let's talk about this, AI mandate that you brought up.

Andrew Zigler: 2:57

Oh yeah. So I opened up with another AI mandate, making a bit of a splash in the tech world. Uh, this latest one is from Duolingo. Um, other companies, you know, we've been covering on the pod. You know, we've been talking about Shopify's mandate. Duolingo is very similar in regards to, Changing how they structure the work that they assign to their employees, particularly their contract employees. And if it's a work or a job that can be done with ai, they're going to pursue technology and routes to better get that kind of process online. Uh, this represents, shifts that we're seeing everywhere across the industry. Some companies are being quiet about it, some companies are being fully open, having mandates about how they're restructuring. The way to work. So if you even checked out the latest one from Duolingo, it's definitely worth a read. Duolingo has massive impact on language learners across the world. It's almost impossible for anyone to not know what Duolingo is because it teaches folks that communicate in. You know, multiple languages. it's also a really effective learning tool in general. They have great practice, great user experience. And so here's another company, um, that's large with a lot of consumers, a lot of daily active users on their applications, making the call for AI powered, workflows within their company to get ahead, in the space that they. Already have a lot of control on. Ben, did you hear about the new, uh, the new AI language learning app that that hit the world from Google recently?

Ben Lloyd Pearson: 4:17

Yeah, well, I was gonna say, it kind of surprises me, like it almost feels like Duolingo is a little late to the game on this one because

Andrew Zigler: 4:22

Hmm.

Ben Lloyd Pearson: 4:22

about linguistic apps, like the apps that focus on like linguistic like services. You know, like that's kind of what GPTs are specialized at. And yeah, this story about Google, like what's going on there?'cause maybe there's some

Andrew Zigler: 4:34

I.

Ben Lloyd Pearson: 4:35

pressure here as well.

Andrew Zigler: 4:36

Yeah, there's this new tool, from Google. I don't even want to call it a product because it's really like an experimental lab feature you can go play with. in one of Google's product labs, uh, it's called little Language Lessons and it uses generative AI to make practicing languages really easy and personal. it's a collection of like bite-sized learning experiences, that are built using Gemini models, powered, by Google and each experiment explores a different way, that AI can support real world. Learning. Um, I really like the little language lessons. I went and I played around with it. It's really effective and personalized, but the best part about it is that they deliver these experiments into your whole Google experience. And so, it, it really goes to show that when you're on a platform. As of wide reaching as Google, the idea of embedding everyday learning experiences into that is just, uh, there's so much potential for people to build new skills in ways that they haven't before. It actually, reminded me of very recently, Dev Interrupted was invited. As some of y'all noted Atlassian team, uh, the closing keynote there, um, I listened to Sal Khan, the CEO, founder of Khan Academy, iconic Learning Institute for People online, as well as Ben Gomez. Ben's, Google's, SVP of Learning and Development. And they talked extensively about how the future of learning is gonna be with AI powered assistance that can bring lessons to where you are.

Ben Lloyd Pearson: 5:54

seeing this phrase like all over social media recently about like how AI won't replace you, but people using AI will, and I feel like it's, it's a little overused at this point, but the interesting part about this story is how it actually kind of almost refutes that statement because here we have an entrenched, service provider, Duolingo. In this space, and then a major company like Google, literally deploying an AI service that could theoretically wipe out this company altogether. You know, so I, I kind of get the, the pressure that they are probably feeling at Duolingo given this new competitive, offering from Google. I've been expecting AI to disrupt education practices basically since I've got my hands on it for the first time. And, you know, I've got a young kid that's starting to get into the public education system, and I have started to think recently, how different it's gonna be for my kids because we are gonna have these opportunities for personalized AI or personalized education from ai. And I think, like, this doesn't stop at, for school aged children either, AI can be such a powerful tool to learn quickly you don't fall into like many of the pitfalls that, tend to make some people lazy with its use. but you know, with that said, Google has had some very public flops in the AI space and. not to mention how often or how frequently they launch a product only to kill it off like a year later. So, you know, I'm gonna withhold judgment on what's act, who's actually gonna prevail here until we have a better, sense of the effectiveness of this survey. But, you know, Andrew, I'm almost wondering like, is there this emerging trend of B2C companies being the ones that are the most at threat from AI disruption? simply becausemaybe maybe there's less of a moat. That can be, you know, eaten away by AI services.

Andrew Zigler: 7:43

I think it's a good theory. ultimately when you're B2C, uh, you're dealing with a lot of potential consumers or buyers of your product. So the risks you can take, um, are a lot different compared to like a B2B space where you are typically more incentivized to build a highly specialized and durable tool that another business could run and scale with Oftentimes an individual consumer doesn't care a lot about scale or even longevity as long as it solves the problem or Amuses them for the immediate thing they're trying to do. It's a whole different market space, so they're allowed to iterate a lot faster, and if anything, I think we're just seeing trends that will eventually make their way more into B2B practices.

Ben Lloyd Pearson: 8:22

let's take a step now into the, the big corporate tech world where we've got some stories about major restructuring

Andrew Zigler: 8:28

Oh yeah. So we're talking about a, a recent shakeup at Intel. if you've been following the news, they've had a new CEO. They've had a lot of internal restructurings and changes recently, Intel, notably being one of America's, chip foundries. It has plays a very pivotal role and. America being able to, produce chips at scale as well as have its own kind of chip manufacturing, processes. there's a lot of things at stake both for the business and just for the country in general. A lot of people feel about the intel, news, right? Which is why it gets so heavily reported on, and people are so deeply invested in the moves that Intel makes. a lot of this actually is structured most recently around, like sweeping measures that have been announced in Intel, including some number of layoffs, the company restructuring, getting rid of some of its non-core products, and also expanding its return to office mandate. this is something we've been seeing pop up more and more in the tech industry, um, even similarly, just the moment ago, we talked about Google. Google is also telling many of their remote workers to come back to office three days a week, or they'll be losing their job, you know, by the middle of of summer they're putting their foot down and ultimately saying that in-person collaboration is an important part of how they innovate and solve complex problems. That's not the first time, of course, that we've heard, industry leaders, CEOs, and executives talk about the return to office mandate.

Ben Lloyd Pearson: 9:50

this is a battle that's continuing to wage between tech workers and, and their employers. But you know, the, the thing that really stuck out to me about this intel story was their focus on, reducing layers of middle management within the organization. Like the CEO mentioned, there's sometimes as many as eight or more layers of hierarchy within an organization inside of Intel, which is pretty extreme, I feel like. as someone who has previously worked the big corporate tech life, I've actually seen companies, that are like this and how it actually can put them in a situation where they're. Ill-equipped to move quickly. there are lots of managers, not a whole lot of doers by comparison. my advice, and I think this advice is a little more important in this day and age is that you can never stop being a doer. even if your job is strictly to manage people, you should always have something in your professional life where you are the individual contributor that's producing Like I think in this AI future that we're all entering into. anyone who is purely a manager is probably in a tenuous position. Like I, I don't want to say that AI is gonna take their job because, you know, nobody really knows. But, I think the future is gonna value people who can create versus those who can, you know, manage. also just one final point, like, man, don't do return to office. Like, it, it just, I don't, I'm not convinced at works. You're, you're really putting a lot of pressure on your employees and particularly considering that like you, you know, just put, just think of a person who might have to, who got hired remote and might have to relocate. To an office, like they don't really have a whole lot of guarantees that their job is gonna be there in six to 12 months. these companies have a long history of laying people off on regular basis. There's, there's no guarantee that moving to an office is gonna guarantee your employment for the long term.

Andrew Zigler: 11:40

Yeah, it goes beyond being a bit of a bummer. There's actually a lot of research We've also covered on Dev Interrupted about these returns to office mandates affect company morale. employee productivity, employee health and mental wellbeing, but also more importantly, it goes counter often to the thesis that executives charge in with about, it's an important way of innovating and solve complex problems when in truth, the best way to solve complex problems and innovate is to give people the space that they need to do their best work. That often doesn't align perfectly with, being in the office. So, if you are, in a company that has returned to office mandate, or if you're balancing hybrid schedule, or otherwise having to change how you work, reach out to us on LinkedIn. We're always talking with folks about how their tech world is kind of moving around them. We'd love to hear about how it's impacting you and hear your side of the story too.

Ben Lloyd Pearson: 12:34

and my final point on this is, we've covered today how so many companies are being disrupted by this ai. if you're losing your best employees because you're forcing them to relocate to keep their job, you're just increasing the odds that they're gonna go someplace else and disrupt you, now is the time to have really talented people working for you so that as AI disrupts you or as it disrupts your workflows, you have the right people in the right places to be impactful with it. So, Andrew, tell us about our guest today.

Andrew Zigler: 13:05

Yes, in just a moment, we're bringing Lee Robinson, the VP of Product at Vercel, onto the podcast. Stick around.

Ben Lloyd Pearson: 13:13

What's after copilot? Join LinearB for a live workshop, exploring the next frontier of AI in software development. Learn how enterprise teams are going from assistive tools to agentic AI to boost productivity, orchestrate workflows, and improve business impact Andrew Zigler will host some of the biggest names in AI as they dive into real world stories and new frameworks for AI first engineering. Head over the show notes to reserve your spot today.

Andrew Zigler: 13:43

hey everyone, if you've been listening, joining us today is Lee Robinson. He's the VP of Product at Vercel. Vercel is the company behind Next.js and so much more that's powering the modern web. And if you've been a long time listener, you'll remember something that Vercel CTO, Malte Ubl said on the show back in October. He said, iteration velocity solves all known software problems, but here's the thing, velocity only matters if your team can keep up with it. Shipping fast isn't just a systems problem, it's a people's challenge. And that's why I am really excited to have Lee here today because Lee's been at the forefront of building not just great developer tools, but also rethinking what a modern engineering team looks like in an AI driven era. And he's not just doing it, he's teaching it too. I'm a big fan of how Lee educates his audience on YouTube, so be sure to check him out there. And Lee, welcome to the show.

Lee Robinson: 14:38

Thank you for having me. Looking forward to talking.

Andrew Zigler: 14:41

Yeah, let's dive right in on, on some of the things that you're seeing. I wanna start with, something you mentioned to me that was really thought provoking about, uh, how you're shifting from a traditional front end backend role division and how you think about. How teams work together. And instead, you're finding yourself, evolving into thinking about a product-focused engineer, someone who does maybe a little bit of all of those things.

Lee Robinson: 15:05

Mm-hmm.

Andrew Zigler: 15:05

does this product, perspective mean for you at Vercel?

Lee Robinson: 15:10

I'll go back a little bit to when frontend engineering started to become more popular at the time, 10 plus years ago, 15 years ago, frontend engineering wasn't really, I. Honestly thought of as the same level of caliber of difficulty as backend engineering or infrastructure engineering. It was web developers who wanted to write their HTML and their CSS, and they weren't really building the applications, Over time, I think as more and more complex applications on the web started to get built, a lot of engineers realized, wow, the front end is actually pretty difficult. There's a lot of things we need to consider when building these very, stateful, interactive complex, fast web applications. And to do that, a lot of people wanted to specialize so. Let's call it 2010. I think we started to see a lot more specialization around, I want to be a senior, you know, software engineer focused on backend, and I want to be a senior software engineer focused on the front end and working with JavaScript or TypeScript or more than just a web developer or a web designer. And over time, what started to happen was. I saw teams put up these walls between where the front end was and where the back end was, and it's a little decoupled from the reality of how software actually gets shipped. not like you just build something on the back end and throw it over to the front end, and then it just magically gets implemented. You often have to go back and forth. Maybe the API contract looks a little bit different and you need to make some changes. Maybe you needed a bit more data. it's really a lot more fluid between the different parts of the client and the server. And in that world it makes a lot more sense to think about features and products more holistically, more end to end. So throughout the 2010s, what I started to see a lot of was more people making the distinction of product and platform engineers. A product engineer doesn't think about necessarily the front end or backend split. They think about everything that it takes to ship a feature and deliver customer value end to end. Across the entire product. Much more common at a startup because you kind of have no choice but to be a product engineer For some of those early developers, you're, you know, you're doing many different things, but increasingly I saw product engineering being a more prominent specialization as companies got larger. Because there was this split between, I work on features end to end on the product across the front and the back end, and then other folks who kind of self-selected into the DevOps or infrastructure type worlds. And so I. I saw that shift happening in the 2010s, then enter the 2020s, and we saw the AI revolution, right? We saw ChatGPT we saw all these new AI models, and increasingly what mattered more than ever was the product code, right? It didn't really matter if you run an engineer or backend engineer. All of a sudden, if you're kind of, if you're an amazing backend engineer, you're maybe not as great at front end. You're terrible at CSS, that's fine. I just work with an AI model. It helps me make pretty decent looking front ends. It helps me understand how they work and I can actually deliver value to my customers, to the product across the entire spectrum of code on the client and the server. So in an AI first era product engineering is more important than ever. Dare I say. It's basically the only thing left. When you're working with ai, you have to think about the entire experience from end to end.

Andrew Zigler: 18:48

Absolutely. That's really insightful and there's actually a lot in there that's really good to unpack. I think it's good to zoom out and look at this timeline that you've given us.'cause it's really helpful for understanding how that's evolved. my background in tech and kind of how I got started in it is in web. Dev and web design. So like I know this evolution in the 2010s that you're talking about, it was when I was learning a lot of my skill stack. And that was something that I noticed immediately is like you described, you have the people who just want to, write their HTL and CSS and you had the people who wanted to interact with the server and it didn't really feel like those worlds were going to meet. But over time. All of those walls fell down, but they started to fall down long before AI got on the scene. This isn't AI coming in and turning something else upside down. This is a natural evolution of how like web technologies evolved because more of the things that you used to have to confine to a server got brought into the browser. You were able to write them as apps and they were able to live alongside the design and the HTML, and that kind of opened up this whole new paradigm. You started to see like the full stack engineers, right? You see people kind of. Combine both of these things. But now you have the opportunity to go really deep on your specialization and have the thing that really you love and that like draws you to what you are are doing in software development.'cause every developer, you know, at the end of the day, they wanna write good code. They want to ship their product, they wanna make something great. And when you're using a tool like this, like AI to augment. The parts that you don't know or that you're not good at now, suddenly you can fly because you can focus on the things you're great at. You can get that kind of, uh, support that you would need from like a team. But then alongside it, the tooling that you're building your website with has evolved and caught up with you too. So, now if you wanna do it all on the server, you can. If you want to do it all in the website, you can. You just pick where you want to go and you build it., Do you think that based upon this, that teams will evolve to, instead of being backend and front end and DevOps teams and platform teams and all these like different kind of specialized teams into just being a cohort of maybe like more product oriented engineers who take roles and responsibilities as needed? Do you see more of like a, it's like a communal group of developers rather than everyone kind of has their, their work silo.

Lee Robinson: 21:06

So, I will first caveat with saying there will always be specialists There's always gonna be that person who is the. Absolute master of infrastructure, master of frontend master of backend, uh, amazing product manager, amazing designer, you know, a 100x designer. Those people will always exist and they're going to be more powerful than ever with AI enhanced tooling. However, I think across, you know, one to five person startups all the way up to kind of growing SMB companies, small to medium sized businesses, all the way up to like very large enterprises. I think the makeup of how the team is structured is changing a lot because of AI tools. for context, one of the, the products that Vercel builds is called v0.dev. It's a product that helps you build. Applications completely with ai. So you might call that an agent, depending on what your definition of that is. But you write in, you know, I want to build an app that does x. It generates the code and it helps you make something that's quality, that works well, that has a nice design, great ux, and you can just iterate on it by writing in the chat and asking questions. And what we've found from talking to a lot of the. millions of people who use this product now is they're not traditional developers, right? A lot of the people who are starting to use these tools, V zero is not the only one, are product managers,

Andrew Zigler: 22:29

Yep.

Lee Robinson: 22:30

designers, founders, people, tech adjacent. Maybe

Andrew Zigler: 22:35

Mm-hmm.

Lee Robinson: 22:35

have a, a normal job working in tech. There are people who are, sometimes technical, or interested in becoming. Even more technical, wanting to learn how to really create and build products and. These AI tools are giving them the power that they didn't have before to not only generate and build apps, but really ask questions to understand how it works. Because that's often one of the trickiest parts is like, yes, maybe you could use the no code tools of the past that took a spreadsheet and generated some UI from it. But one, you didn't really understand how it worked. It was kind of a black box and two. It was hard to get that fine grain customization when you wanted to like eject out and do something a little off the beaten path, like there maybe wasn't a switch or a toggle for it in the ui. I give that backstory to say I've been fortunate enough to talk to many teams now, ours as well internally, who are going through this shift of what does the world look like you have these type of tools and you know that they're just going to get better, they're the worst they'll ever be. In a year. It will be 10 times better. In five years, it will be a hundred times better. So what do you do as you start to think about not only how you structure your team right now, but how you plan for the next year and five years down the road, how you think about your career long term. And on one hand, as an individual, I can empathize a lot with people's anxiety over this because it's a little bit of a soul searching exercise if your identity has been tied up in. I write code. I'm a front and engineer. I really like building, pretty pixels on the screen. It's a little bit of a strange feeling to know that AIs are getting very good at doing that type of work. Like, weren't they supposed to fold my laundry? Like, why are they doing my job? Um, and I think what it has done is it has both. Raise the floor and the ceiling for the type and the quality of applications that people can build. But what it's also done is it's kind of normalized the ceiling of what people across developers, marketers, product managers, any of these type of folks, it's leveled the playing field of what they can create. So for example, I'm a product manager. I have a very good product sense. I talk to customers. I know what they want. I have these ideas in my head. actually, I thought about learning to code in college. I took that one class on Python and then I kind of gave up on it, I would love to build more apps. Maybe I prototyped some stuff in Figma, but you know, I don't really spend a lot of time on it.'cause I'm trying to be a great product manager. I have great product sets. these AI tools come along and all of a sudden the like. Wire frame or napkin drawn ideas that I hand off to my Dev team. I'm actually building functional working prototypes that you can click around and try in the browser. Sure. They're not, perfect. We might not actually ship that code, but it's real. That's kind of this gateway to actually, I can build my ideas. I can just take this nebulous thing in my head and turn it into real working software. I have a blog post on my site called Personal Software where if you extrapolate this out over a longer time period, I do think we'll enter a world where if you are so inclined to want to create your own software for any. anything really. If you wanna make your own app for recipes for your meals, because you're wanting to become a chef, you're wanting to make your own music player that's, perfectly tuned to exactly the music you listen to and the features you want, you can just build it. And you might not have ever written a line of code before and that's fine. So all of that context to say the makeup of the teams is then shifting to where you see more and more people. Who maybe focus a bit less on the code as their full-time effort, and they're more of an architect or a planner or a product thinker. They're much closer to the customer experience. They're much closer to the product experience on delivering actual value to people who are giving them money. And I think over the long term it will change even further the, the way these teams operate.

Andrew Zigler: 26:55

There's so much good stuff in there. I wanna unpack some of it because you covered a lot of really great points that I really identify with that I'm also seeing as well when I talk with people, when I interact with folks that are adjacent to tech especially, and how they approach the tools and what they can create, it's actually quite profound what someone can build with little to no technical knowledge. and then what impresses me even more as like a former teacher, like being in a classroom is I was like. Wow. It's, it's really hard to, you know, I, I maybe couldn't teach my grandma Python very well, but I could probably teach my grandma what makes a good product and what makes a bad one, and how to iterate through it. Right? She can cook a recipe in the same way that I could explain to her how you make something good, and that's a huge unlock, right? It's like now suddenly you have this whole field of. we call them whatever you want, but some people will call'em like citizen developers. I think it's just like the new norm of access to technology, of being able to go to something like you described of like V zero, and type in a concepting and get it back. I liked how you framed it. I liked how you defined it as. Personal software. the term I've been using and we've been kind of talking about a bit on Dev Interrupted, is disposable software of like, you just almost need it for a one-off purpose. Or the idea of something before that. Like, oh, you know, you do it once and it's a little annoying, you do it twice and now you're like repeating yourself. Do it three times. Now I need to automate it. Well, maybe this would be what you'd build around, like time number two. You're like, I did it the first time. I kind of knew what I need. If I could just build this little eject like tool or toy to like just do it when I need it on demand. Now I don't have to think about like. Automating it. Maybe this isn't worth automating. Um, I, I'm wondering too about how do you see teams and stuff take advantage of things like automation, to improve their productivity and their developer experience?'cause I can't think of something that's, has a faster shipping timeline that has a, better workflows and pipelines than web Dev, which has always been on the front line of those kinds of tools. So like what? What kind of things are you seeing?

Lee Robinson: 28:49

Yeah. I think for a lot of the, people who just have an idea but they don't know how to build it, there's always been this like long running meme or joke of, have that friend who's the idea guy and they're like, I have an app. I need, I need a guy to build my app. Like, can you

Andrew Zigler: 29:06

Yes.

Lee Robinson: 29:06

app?

Andrew Zigler: 29:07

Yes. You took this right out of my mouth.

Lee Robinson: 29:09

because,

Andrew Zigler: 29:10

made this same joke. It's so good. Yeah.

Lee Robinson: 29:12

I, I think that for, I, I believe the kids are calling them Normies, for the general, population for most people.

Andrew Zigler: 29:20

Yeah.

Lee Robinson: 29:20

they go to the app store and they download apps. they use a lot of websites too, but I think a lot of people are exposed to their phones and downloading an app on their phone. They download Instagram or whatever. for these people they thinking, I have this idea. I wanna build an app, or I want to build a product based on that. They don't really know exactly how to go from A to B, like draw the rest of the owl meme. Like, okay, I think I know what I need to

Andrew Zigler: 29:47

Yeah.

Lee Robinson: 29:47

to talk to somebody to actually get it done. I think what these tools are doing is they're allowing people to actually take that first step and just try something out, and maybe it's not perfect. Maybe it's, you know, still needs some work, but they've got something that they can then iterate and build from. I know at least for myself, whenever I'm learning something new, it's the, like, when, you know, there's this really complex and difficult and daunting task. It's very easy to get stuck in knowing I've got a lot of stuff to do. How am I actually gonna get to the end? And the only way for me personally is like making very small incremental steps and then having some kind of reward system along the way where I'm like, oh wow, okay, awesome. Like, I, I did it.

Andrew Zigler: 30:35

Yeah.

Lee Robinson: 30:36

works. as a personal anecdote, when I was learning to program, somewhere along the way I started to get into app development.'cause I thought, this seems really interesting. I'll, I'll learn how to do it. And the speed from Idea to published app was just so incredibly slow that it really just took all the wind outta my sails for wanting to build app development. Not only was it very hard for me to come up with ideas and then turn it into code and iterate on the idea and then actually get it distributed on the App store. But then once it got out there, I was like beholden to the strange Apple rules. and if you made a mistake, now you had to push a new version and that version had to get updated. And it was like, oh my gosh, this is just, this is a lot. And it really made me. Like re fall in love with the simplicity of the open web. Anybody can just publish stuff. You don't need permission from anybody. Anyone around the world can buy a server and put their site online. They can upload files to A CDN and distribute it around the world. They can use a service like Vercel, it's got a free tier, and get a site online. They can use a tool like v0 or others and just type in their idea. Click a button to deploy to Vercel and it's live. And I think that of tool will really democratize the power of the open web, which is that anybody can build any idea without having to ask anybody. That's what gets me really excited I think about this next generation of tools.

Andrew Zigler: 32:07

You really couldn't have said it better. I also really like the idea of now the ideas guy and they have everything they need to execute their idea. and I'm sure you'll see a lot of interesting, fun ones. I.

Lee Robinson: 32:17

link to v0,

Andrew Zigler: 32:19

Yeah, precisely. It's like, yeah, it's, it's his dream come true. and so along the way, you know, there are those obvious wins, about the building, but also when teams are working and they're deploying, you called out a really good. key differentiator of the open web. But what I like about it too is that, anyone can build on it. You can get on there fast. it's not a closed garden. You don't have to be beholden to someone else. and so that really levels the playing field, but that also allows for really rapid iteration. You know, you pointed out how there's like so much tooling and so much, opportunity available. Specifically to take advantage of these AI tools on an interface like the web, because it's evolving at light speed, it's evolving as fast as people can upload stuff to it. So, along the way the fundamentals become even more important because now you've built this like, this one-off app and you've ejected it and you have your proof of concept as you said, you know, you're like tinkering with it. It works. but now you need to take it from. 80 to 90, and then you need to take it from 90 to a hundred. And those are two very different, like leaps and bounds in the development process. and for hobbyists or citizen developers, you know, they've never taken anything from 80 to 90 to 90 to 100. That's a whole new territory for them. they've been focused on zero to one. This whole time. And so when you talk about that, what kind of opportunities and games do you see for teams that are taking things from 80 to 90, 90 to 100, 99 to a 100, you know, are there, specific kind of tools or orchestration or ways that teams like, talk about what they're doing week to week that you see really kind of like shine in terms of high performing teams?

Lee Robinson: 33:55

Yeah, so my personal experience is that, AI tools and especially around code generation, are very helpful from going from zero to one or from zero to 50% In your analogy. From the 80% to a 100%, it's a little more difficult because at that point you need to have more of an opinion about what exactly you're trying to build and what you need to get done. At that point, it's more of a consultant that you're asking questions to versus the actual implementer of the idea. So I think especially for larger teams who are working on more of the 80 to 90%. It's mostly done. We just have to like add the polish on top. the biggest unlock of AI, honestly is just automating the simple, repetitive things that maybe would've taken an hour that now you can get done in five minutes and then you free up that time to go back and do other work that is furthering actually building the product. One of the things that we talk about with v0 a lot is this idea of code last so different than. A no code or low code tool. Code last is yes, we still care about the code. We still want to have high quality code that works and compiles and uses the latest tools and is accessible and performant. It's just not the first and foremost thing that you're concerned about when you're trying to build a great product. It's make it work, make it right and, and then make it fast and making it work is a lot of iterations first. So. I think if you apply that same kind of code, less code last mentality to the entire software development lifecycle, yes, you're still gonna write code, it's still gonna have code review, you're still gonna work together on teams. Like none of that stuff really goes away. It's just your relationship with the code is changing a bit more.

Andrew Zigler: 35:47

Yeah. Instead of it being the thing you have to do first and then really lay down a thick foundation with, it's now just another ingredient.

Lee Robinson: 35:53

Right. And there's also different. You know, caveats always apply. If you're working on mission critical production software that handles payments, like you're probably not vibe coding out AI generated code there, you're probably

Andrew Zigler: 36:08

hopefully not.

Lee Robinson: 36:09

particular about the code that gets shipped. You have multiple reviews, you have lots of processes in place. You have testing, you have, multiple stages where you're validating changes before it actually goes live. But I think. Often when I talk to people about this, they think there's some kind of inherent, like either or of either you can use AI or you can't. And what I found is even in those mission critical production workflows, AI can still help me generate a bunch of unit tests. I'm still gonna validate and make sure the tests are right, but it's helping me just move quicker on what I already know that I need to do. Now, the biggest objection of AI generated tools in general that I do strongly agree with that I don't think anybody has really figured out is what do you do about the newer, I don't even know if I would call them developers, but the people who are just getting into learning how to output code, how do you help them get over the compiler errors, the stack traces, the debugging, like, I don't know if that's what you were thinking in terms of the 80 to 90%, but like the rest of the job. I think the tooling there in the ecosystem is still. Super early. I have confidence. it will get better. We will get tools that make that easier. It's just not, we're not there yet.

Andrew Zigler: 37:29

Yeah. it's like solving those harder problems are almost more like dealing with AI as in a consultant level, you're posing a high level thesis about what you've built and about what it could do. And then really taking a deeper look at are there changes we need to make to account for that? is this infrastructure really going to, accommodate it? it's like you're asking a, a different. level of questions. And like you said, that tooling is still early, people are still figuring it out. But what's important is that zero to one is getting lightning fast as you're, as you're calling out, which is opening a lot of doors. And another topic I just wanna touch on because I know this is really top of mind for you, is about. You know, opening roles right now and hiring engineers and actually building out, engineering teams, these product engineers, as you put it earlier, in our conversation, and, and something you called out to me in our chat is that you recently opened a role that got like over a thousand applicants. Like you're flooded with people who wanted to work at Vercel, which, you know, makes sense. Vercel's a, a, a global name in terms of its presence. And, I wanted to un, I wanted to kind of like, dig into that a little bit, learn about your experience. what are like some early ways you're re-approaching the hiring process in like an AI era.

Lee Robinson: 38:33

So my biggest AI hot take that, it spans across multiple different categories. The best practices from pre AI still matter, and they're actually more important than ever in a post AI world. So, me explain. With

Andrew Zigler: 38:54

Yep.

Lee Robinson: 38:54

before ai, it was really like referrals were your best source of candidates. They always were. That was your highest, you know, highest quality pipeline versus just inbound applicants. still true. It's actually more true now than ever before. And hiring is one category where, where it works, but that also applies across so many different things that I've just been reusing that for. I don't know, 15 different categories, but yeah. Let's talk about hiring because it is very interesting how the landscape has changed a lot simultaneously. A couple things have happened. One, AI tools make it super easy to. Apply to just thousands of jobs. Like of course before you could go through and click apply and, you know, connect your LinkedIn and submit a job application. And that was great. But you were still limited by human throughput, AI automation, browser automation, using an IDE to like create a little script that does it like much more accessible now, which means that you do see people, especially for technical roles, that spam apply to thousands and thousands of roles. which. On one hand, on like a human level, I can empathize with wanting a job and wanting to do whatever it takes to get that job. think my advice to people if they were in that situation is, I think you have the right feeling, but that's not the right solution to that feeling. the spray and pray approach,

Andrew Zigler: 40:21

Yeah.

Lee Robinson: 40:22

what I would recommend is. For those people, what I've found and the type of cold emails or cold, outbound to me that I get, that I, I feel more interested in and more likely to respond to that I've seen work for other people is very personalized, concise, interesting content, and you can't. Really use AI to send that. You can maybe use AI to help you refine it and edit it and give you ideas, but ultimately what I want to know is that this person really cares. They took time to craft something intentional thoughtful. Ideally have brought something to the table that has a hook. it's got my interest. I'm like, wow, look at this thing that this person built. they didn't try to send a 25 page memo. They said, Hey, I built this thing. You might find it very interesting if you wanna hire people who build things like this. Like sure, there is no shortage of hiring to be done for great builders. If you can build great products. you're gonna have a great time and getting employed at a bunch of different places, especially if you sweat the details and you really care about making something that's, you know, not just good but great, and not just great, but exceptional. so that would be my advice for that. the other thing is that I often see, even if maybe you don't apply to a thousand jobs with ai. Maybe only applying to 10, but you're using AI to like generate your cover letter or generate and update your resume. for a hiring manager who's looking at tens or hundreds or thousands of resumes, who's also using tools that are helping them kind of refine and focus in on the highest quality ones, it is alarmingly obvious. If you've used ai,

Andrew Zigler: 42:18

Yeah.

Lee Robinson: 42:19

if you just take the output and you don't really change it. There's an increasing number of signals that I'm sure will only go up that say, okay, this is probably AI generated. It started with delve, you know, ChatGPT would output the word delve every five sentences. Apparently now

Andrew Zigler: 42:36

it's

Lee Robinson: 42:36

em Dashes. So

Andrew Zigler: 42:38

Oh yes. It was always em dashes

Lee Robinson: 42:40

So that, that one I'm a little sad about because I kind of like them and now

Andrew Zigler: 42:45

Yeah.

Lee Robinson: 42:45

an AI when I use 'em.

Andrew Zigler: 42:46

Yeah.

Lee Robinson: 42:47

kind of be aware of the zeitgeist there and what's changing? There's more words to, what you really want is, again, a consultant. You can use AI to say, critique my resume.

Andrew Zigler: 42:58

critique

Lee Robinson: 42:58

my cover letter, critique my

Andrew Zigler: 43:00

outbound

Lee Robinson: 43:00

email What could I do better? Could I make it more concise? Is there any confusing spelling or grammar? Especially if you're don't have English as a, you know, first language, if it's English as a second

Andrew Zigler: 43:09

language

Lee Robinson: 43:10

you can use that to help refine and curate. But if you just take the raw output from an AI model and send it over, your application will probably get passed.

Andrew Zigler: 43:20

Yeah, I think that's the key takeaway here. it's such a useful tool for kinda like, almost like rubber ducking your resume or whatever you're making. Like you could tell it to take the role of the person that you're going to send it to and ask, the kind of questions that they might ask you, and it kind of helps you refine. It's useful to use a tool like that in what you've called out almost like A private loop in order to iterate and get that really good version of yourself that you can share. I like how you called out too, that, the things that mattered most in hiring, they matter even more now. I completely agree. When I get a message, I can tell when it's AI generated versus when it's not. I can tell when it's a short, sweet, personal message from someone. Some, something that I like to do is even if I'm going to. Use, an LLM to help me like craft a message or prepare something. I love to go in and then like wreck it as a human. Like let's put some lowercase letters at the front of some of these sentences. why does this, I need to be capitalized? Uh, sign it off with a funny thing and drop a few emojis in it that the LLM wouldn't use. not an emoji that corresponds with a word it loves, but like one of those obscure ones

Lee Robinson: 44:18

my take here is if the best use of AI is, if I actually thought that it was written by a human, but it actually was ai.

Andrew Zigler: 44:31

Yep.

Lee Robinson: 44:32

if you have figured out your AI curation loop and your edit loop, where let's say 80% of the content was AI generated, but you still brought your own taste and curation and structure that, if you wanna use AI for that, that's great. But from my perspective, it still looks like a human crafted it, it's very concise. You know,

Andrew Zigler: 44:52

Yeah.

Lee Robinson: 44:52

is super intentional. You've sweated every single word in the sentence. that's the ideal case for me. Like I, I still use AI to help with my writing. and it's great at helping pick things apart. And I love, and I, I continue to take advantage of AI for that. It's just you're not done just when you have the first output.

Andrew Zigler: 45:11

Yes, exactly. I think that's the key thing. You gotta keep it iterating and you have to make it yours. Um, it's a tool, right? you can't send it right off the tool. You need to put your personal stamp on it. And when you talk about sweating the details, I think that's really important. Like, what are some key things that that. Make a candidate stand out. Once they get past this, like, you know, they, they're through the door. They've got your attention. What then about their skillset nowadays really stands out to you.

Lee Robinson: 45:36

Yeah, so for my role specifically, I'm focused on our developer experience teams at Vercel. And it's kind of more of a, a niched role than a general generalist engineer. So I can talk about what's worked well for my roles, for developer experience. There's really three parts that I focus on growing our developer community, teaching all the developers in the community through education, and then documenting how our systems work, whether that's API reference or just tutorials. the type of engineers who work on those type of teams generally have some public track record of their work, and if they don't, it's usually a red flag. So my advice to

Andrew Zigler: 46:21

Yep.

Lee Robinson: 46:21

looking to get into this type of work is you should work in public. You should share what you're doing online, whether that's code you're writing, whether that's articles that you've crafted, videos you've made, ideas that you have, V zero generations and apps that you shipped. All of that is great. What it does is, I get a resume and I'm like, oh, this person seems interesting, I will go Google their name or I will click on their portfolio link that they include in their resume. in the ideal case, I go out to their portfolio, I learn a bit more about them. I read some of the things that they've added to their blog or some of their posts. Maybe they have a newsletter and I read that, they have a link to the code or the apps that they've built. I'll go look at the code or I'll go try the apps. If I try out one of the apps, like a side project and. It just feels really good. Like it's so super high quality. The design is nice, like the, they've added these little details that nobody would do unless they really cared about making something special. get interested, I get excited. I'm like, okay, this person really cares about what they're doing. They care about the craft. They care about, you know, making something that stands out. And they're bringing the world along for that journey. They're making a name for themselves on the internet archive. that is a much higher signal for me than a specific employer or a specific bullet point on a resume. And honestly, like I've, seen good and bad from the biggest tech cos to the smallest startups and everywhere in between. So It's hard to index on a specific employer name. Generally, at least for myself, I'm biased more towards like small to medium sized companies. I just find that, there's nothing necessarily wrong with working at like the major tech companies. It's just often I think when you go there, you get indoctrinated into this way of working that is sometimes hard to eject out of.

Andrew Zigler: 48:20

Mm.

Lee Robinson: 48:21

when I interview folks who spent, you know, a decent chunk of time at the Googles or Metas of the world, I'm trying to understand, are you excited about and interested in going into the world of you have, a 10th of the team size and you don't have that dedicated internal tool that's very, very powerful that, a team of hundreds of engineers built. You don't have that anymore. you still excited about doing that?

Andrew Zigler: 48:44

Yeah.

Lee Robinson: 48:44

more on the like content side. It's like. There, there isn't a video editor, you know, there isn't another person coming to do this work for you. it's you, you're kind of doing it end to end. Are you excited by that or is that kind of scary?

Andrew Zigler: 48:57

so the journey that you've described, I really relate to it 'cause it's kind of like matches my own journey of coming into tech. I had a totally non-traditional journey and I started by building in the open and building an open source communities. just kind of hacking around with things and sharing it And over time you build a collection of stuff that's very personalized to you. And even maybe it's not, none of it's complete and none of it's even really all that great, but. All of it showcases over time your ability to build skills, to be fascinated by a problem, try to learn it. I still remember in the first interview that I managed to make all the way through to the CEO round. And when I was like really interviewing to get into tech, I, I remember going into the call and the CEO had opened up one of the games I had made, like in phaser or something, and was playing it and was like asking me questions about it. And that was his interview and I got that job. And so, I really can't stress enough the importance of building in the open about just building vulnerably too. Don't feel like you have to hold onto it until it's like perfectly mastered and ready to share, because that, I promise you, as a developer now, that will never happen. You need to share it. and that's how you can really showcase. Those skills. so everything that you've, kind of highlighted about what makes them stand out, that really resonates with me. really great call out. and so to wrap things up, I, I wanted to ask too about, for people already, on your team are already kind of using these tools. what are some. ways that Vercel is thinking about upskilling and coaching people that are already within an organization to succeed in an AI driven world. You, you referenced those engineers that are used to being in the big orgs and having a whole bunch of tooling. The same thing can be true within any org that's been around for a while. People get used to the way of things. So how do you shake things up in Vercel and get people excited about learning?

Lee Robinson: 50:35

Yeah. One of the things we talk a lot about internally at Vercel and, and sometimes externally, is this motto of you can just ship things. really what we mean by it is you have the agency to control your destiny. And that doesn't mean that you have to be a developer. It can be anyone at the company. You can just ship that blog post about how our system works. You can just ship that prototype of an idea for a new product we want to build. You can just ship this explainer video talking about how one of our, you know, framework APIs works. Like you have the agency and the control to actually go and do these things. You just have to have the kind of intrinsic motivation to get up and go do it. So a, a lot of what I think adapting for. A world with extremely powerful AI robots who can just have all of this knowledge of the world easily accessible, is recognizing that what separates you apart from everyone else is your commitment and motivation and relentless pursuit of excellence showing up every day. 1% better, reflecting on what was good, what was not good. Being very truth seeking and feedback to understand, okay, what was, what did I actually not do very well here? And like, please be honest with me. And AI is, is great for that too. It will

Andrew Zigler: 51:55

Yeah.

Lee Robinson: 51:55

roast you and give you feedback. and then taking that, like having this, you know, positive, constructive, optimistic view of getting better and, and going into the future and trying to just be a little bit better version of yourself. Than you were the day before. The way I, I like to think about it is not necessarily a, competition, even though competition is sometimes helpful for people. For me, it's, it's mostly self, and inward looking where my goal is that the next piece of content that I put out, whether it's a blog code, tutorial, video, whatever, the next thing that I put out should be my best work ever. And the one after that should be the best one I've ever made. I. And after

Andrew Zigler: 52:37

Yep.

Lee Robinson: 52:38

the best one I've ever made.

Andrew Zigler: 52:39

Yep.

Lee Robinson: 52:39

audacious goal. It doesn't always happen. Sometimes I miss the mark and I, I don't do as well, or sometimes I just accept there was a time crunch and I wanna get this thing out and, you know, I'm happy with the quality given the time constraints. But that goal, that vision is still what I want. I want to continue to produce stuff that I'm proud of, as if nobody was looking as if I was just doing it for myself. Would I rewatch and be like, damn, am really happy with that. I think if you apply that to everything across engineers, product managers, designers, product marketers, anyone else who works on technical products, you can build great teams who are really motivated in building things they care about. It starts with caring, I think.

Andrew Zigler: 53:21

Love it. I love, I love your obsession with building and, for going for the details and for iterating in the open.

Lee Robinson: 53:26

Mm-hmm.

Andrew Zigler: 53:27

has been a really eye-opening conversation for me. A lot of fun. There's been so much in here to unpack. You know, Lee, we're gonna have to have you back on here in the future to kind of check in on how things are evolving because, even now I'm like, I'm gonna go heck around in v0. I'm quite interested. But, uh, just to wrap things up. I I also wanted to ask, you know, where can people go to follow you, learn more about your work and what's going on at Vercel?

Lee Robinson: 53:48

Yeah. Uh, for all things Lee, uh, leerob.com, it's got links to all of my stuff. and Vercel.com. If you wanna learn more about Vercel v0.dev, if you want to become a vibe coder and just build your next idea. Um, yeah.

Andrew Zigler: 54:03

Amazing. Well, we'll put those in the show notes for our listeners. And hey, if you, if you've been listening and you made it this far, then clearly you loved this episode. I did too. It was a lot of fun. So be sure to check out the conversation on Substack with our newsletter if you're not already reading it. We publish this every Tuesday. and Lee and I are also gonna continue the conversation online. We're both on LinkedIn, so please ping us, reach out to us. We'd love to hear what you thought about today's chat. Until next time. That's it for this week's. Dev Interrupted. See ya.