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- [00:00]
A
Stevie's platform ran because it was a really good criticism of Google. It was a really realistic picturing of Amazon, including Jeff Bezos not giving a shit about your day.
- [00:10]
B
He still doesn't.
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A
Did you write these kind of things all the time?
- [00:13]
B
I was fed up. I've been there six years and I still couldn't get a platform out of anybody. I went nuts. And then a bottle of wine later I told him how it was.
- [00:20]
A
But you were actually right. In hindsight, I was right about all.
- [00:23]
B
Of it, but they never said sorry.
- [00:25]
A
Steve Yegi is widely known for his writing and rants in software engineering. His blog post get that Job at Google was circulated by Goog HR for hiring purposes for 15 plus years. And his Google Platforms rant written a decade ago is still heavily cited across the industry. Steve worked for seven years at Amazon, 13 at Google, and is now building AI tools at Sourcegraph. In this direct conversation with Steve, we cover the infamous Google Platform rant and why Steve thinks Google is still terrible at building platforms, why Steve unretired from tech and coding. Thanks AI Tools, why Steve thinks more devs should vibe go together with AI and many more interesting topics. If you're interested in how AI tools will change how tech companies operate, how US developers can keep up with them, or why the core DNA of tech giants like Google and Amazon seem to change very little over 20 years, then this episode is for you. If you enjoy the podcast, please subscribe to it on any podcast platform and on YouTube. So Steve, just welcome to the podcast. It's so nice to also meet you in person.
- [01:24]
B
Greg, thanks for having me again.
- [01:25]
A
So the first time I ever came across your blog was this Stevie's blog rants. This was around 2010 because I read this article called get that Job at Google. Back then I was trying to get my first job outside of abroad, basically the first job in the uk and I looked for the best preparation materials and the two things that helped me most was a course at Stanford about cracking the Google interview and your article get that Job at Google. And what really stuck with me, this article is still up there and I just tweeted recently that I think after like almost 15 years that's still very relevant. One of the things I really liked is you put this important takeaway is if you don't get an offer, you may still be qualified to work there. So don't blow your ego at all. What motivated you to write this article?
- [02:16]
B
Getting turned down by a bunch of places. No, it's true. Actually, a lot of my friends got turned down. I knew they were good. So I saw the false positives, sorry, false negatives. Because they were so scared of a false positive. And they just, they were Google and they could just turn people away. Yeah, and this is turn great talent away.
- [02:35]
A
This is Google in 2008. So like this was. They barely went public. They were the hottest thing. What are openais to?
- [02:41]
B
I joined in 2005 actually.
- [02:43]
A
You joined in 2005?
- [02:44]
B
Yeah. So by the time I wrote that, I had seen three years of interviewing there and I knew what it took. Right. And I don't think it's changed that much in the last 15 years or whatever.
- [02:53]
A
This episode is brought to you by Work OS if you're building a SaaS app, at some point your customers will start asking for enterprise features like SAML authentication, SCIM provisioning and fine grained authorization. That's where Work OS comes in, making it fast and painless to add enterprise features to your app. Their APIs are easy to understand and you can ship quickly and get back to building other features. WorkOS also provides a free user management solution called AuthKit for up to 1 million monthly active users. It's a drop in replacement for Auth0 and comes standard with useful features like domain verification, role based access control, bot protection and mf. It's powered by Radix components, which means zero compromises in design. You get limitless customizations as well as modular templates designed for quick integrations. Today, hundreds of fast growing startups are powered by WorkOS, including ones you probably know like Cursor, Vercel and Perplexity. Check it out@workos.com to learn more. That is workos.com if you want to build a great product, you have to ship quickly. But how do you know what works? More importantly, how do you avoid shipping things that don't work? The answer Statsig statsig is a unified platform for flags, analytics, experiments and more, combining five products into a single platform with a unified set of data. Here's how it works. First, statsic helps you ship a feature via feature flag or config. Then it measures how it's working, from alerts and errors to replays of people using that feature to measurement of top line impact. Then you get your analytics, user account, metrics and dashboards to track your progress over time, all linked to the stuff you ship. Even better, statstic is incredibly affordable with the super generous Free tier, a starter program with $50,000 of free credits and custom plans to help you consolidate your existing spend on flax analytics or A B testing tools. To get started, go to statsic.compragmatic that is S T A-T-S-I G.compragmatic Happy building. Yeah. And one thing that you wrote about is this thing called the interview anti loop, which I never heard about until then. What is it and does it still exist?
- [05:01]
B
I mean, I made it up, but I mean it's a phenomenon that I observed that everybody knows about that it was the one thing in that post that recruiting and HR were a little, A little, you know, I mean, worried about me publishing it. And I was like, well, there's no point in doing the post if we don't talk about it. Right. Let's just be. It'll give us some credibility.
- [05:19]
A
Yeah.
- [05:19]
B
And I think it did ultimately. Right. Which is, look, you could just get unlucky and accidentally get the six people at the company who just disagree with you the most on everything technical. Right. And it's just like just bad luck.
- [05:31]
A
In fact, I think a lot of tech companies have this policy, or at least used to have it until recently. Maybe they'll do that. You can reapply after six months. Exactly. For this reason.
- [05:42]
B
Yep. And I knew a bunch of people who reapplied at Google multiple times. One, one guy I knew got in on his fifth attempt and then went on to get promoted really fast and rise up the ranks and everything. It was very obviously a false negative, but it just took a bunch of tries to get in.
- [05:57]
A
So a super critical criticism that a lot of people who read that article have is like, well, oh, if this is what it takes in to get Google or meta or whatever, which is, you know, it's my, my skill, not my matter as much as the interviewers. I don't want to do that. Like, I really appreciate that you just, like, you didn't hold back and you just kept it real. But what is your take on people who are like, well, that's not fair, it's not meritocracy, that kind of stuff.
- [06:23]
B
You know, interviewing is not really a very good signal. I empathize with their viewpoint. In fact, at several points in my career, I've sort of kind of given up on interviewing and just said like, you guys do it. There's a lot of people who think they're really good at it and they think that they know how to do it well and so on. Even though the statistics at Google, they ran many, many statistical analyses and found that there isn't really a lot of correlation between, you know, how you score and whether you get an offer and whether you get an offer and whether you do well and so on. And so I kind of lost faith in the process a little bit. I noticed that I was a referral, I was a reference, I should say, for, for a buddy of mine who was applying, who's applying at Anthropic interviewing recently.
- [07:03]
A
Right.
- [07:03]
B
And I got a call. Right. Just a regular reference call. Yeah. And. And the person was the hiring manager, not like, not a recruiter. And the hiring manager talked to me for probably at least 40 minutes. Digging into all the things that you don't pick up in an interview. Right. Because he recognized, just like we do, that interviewing is a really flawed process and it's a trade off that the company has to make between sort of like effort that they expend trying to find good candidates and being really accurate in their assessments. That's a trade off.
- [07:35]
A
Yeah. And then interesting enough, some people are saying, I guess a lot of people are saying this is unfair. There's also criticism of coding, interviews, lead code, et cetera. And they're like, why can't these companies just ask me to do the work? And then plot twist. Some companies are doing that these days like linear. And some of the formal companies are like, who have a strong enough brand. They're like, we will pay you your like day rate, week rate and for a week you will work with us remotely. Now of course. And it's, it's. And you know, I'm actually talking with the engine manager was on my team. Their first engineering manager is like, you can use AI tools like they're immune to everything because you're actually doing the work. Now the downside is you, it's a week of your life. Right. And people are like, well I can't interview at five different places. And I feel, you know, there's all these trades, I thought, well yeah, but now it is real world, right. So there's this spectrum of interviews and as, as you said, like in the end just I guess pick your poison. Right?
- [08:29]
B
That's right, that's right. And I know I. Look man, I've been in the industry for 30, 35 years. I've seen people try all sorts of different variations on trying to improve this. Like the first company I worked for required you to do a six month co op before you could get a full time offer there.
- [08:42]
A
What's that?
- [08:42]
B
Geoworks.
- [08:43]
A
Geoworks.
- [08:44]
B
And they had probably the highest hiring bar I've ever seen. And, and they got acquired by Amazon and Amazon was just blown Away by their hiring bar.
- [08:50]
A
In fact, we should probably mention, I mean, I think you and me have both seen this, but there's this like open secret in the industry where if you go to the website for like Google meta, a bunch of big tech, even Microsoft, you're not going to See Software Development Engineer 1 advertised because they fill all those up with interns. So the internship is actually a recruitment operation.
- [09:10]
B
It is, it is, it's. It's a really cutthroat college hiring is super cutthroat in the industry. And the companies like Microsoft, you know, and Google, they sort of dominate it. They have the resources to build all the relationships with the schools and it's. Yeah. So they, they get the cream of the crop, you know.
- [09:26]
A
Yeah. And then they fill up an entry level.
- [09:29]
B
I'm really proud of any intern that goes off to a startup. Really.
- [09:32]
A
I actually just talked with someone. She'll be on the podcast. She had return offer from Microsoft and Google and she talked with her mentor at Microsoft. It's a good mentor. And the mentor was saying, like, look like you can do big tech, but like with startups you have a very different skill set. And she thought about it for a long time and in the end she took a risk and she went to Coda. She's now at OpenAI actually. But I think that experience helped her and she talked through her mentality and I was like, wow, she sounded like a wise, experienced person. And yeah, I did not expect it because it was like it was paved.
- [10:07]
B
I see a lot of this too. I mean, college kids are savvy these days. They know that stuff's really in Flex. And in fact, all the stuff we talked about, even many of the things that we talked about in the blog post that seemed timeless about getting a job at Google, getting a job is just hard as a software engineer right now.
- [10:24]
A
The other thing that really resonated with this article is you wrote, I'm going to quote it, when you get an offer from a tech company, you just happen to squeak by. And at the time when I read it, I didn't really believe it from outside. But now that I've also, I've gotten jobs, I've been a hiring manager and made so many offers. People who are coming in and they're like, oh, I smashed the interview. Actually, like out of maybe a hundred interviews roughly that I've been the hiring manager at Uber, there was like two. That was like we had more than one person do a double thumbs up. We had thumbs up, double thumbs up. The Rest were a mix of like, thumbs up, thumbs down. And then we came to a decision and it was like it could have gone either way. Like, one went into the debrief. So, like, I now really appreciate it. I feel this is one of the things which is hard to believe from the outside.
- [11:14]
B
The best story is when I was at Google, I was on their, you know, their hiring committee, which is a blind, you know, double blind. They don't see the candidates or the. They don't know the interviewers who's doing it. They're just reading feedback packets. And the interviewers don't bias each other. And one day they didn't experiment with us. Okay. Because we were the ones that ultimately made that decision that you just talked about.
- [11:34]
A
Right.
- [11:34]
B
The thumbs up, thumbs down type thing, not the interviewers. Google has a separate committee that actually looks at all the feedback. Right. And the recruiters did an exercise with us where they presented a bunch of packets, hypothetical packets, say, of candidates who had been rejected or. Or accepted. Actually, they didn't even tell us. They just said these were just a bunch of candidates. We're going to go and do the process on them. We had feedback on them, though. Okay.
- [11:58]
A
Yeah.
- [11:58]
B
We went through and we evaluated them all and decided we were going to not hire 60% of them. All right. Have you figured this one out yet?
- [12:05]
A
No, no, we were.
- [12:07]
B
We were reviewing our own packets. Yeah. So we voted not to hire 60% of ourselves.
- [12:13]
A
Yeah.
- [12:14]
B
Okay. And it was a very sobering realization. And the next week or two was like the best time to apply to Google because we were just like, come on, crew. I mean, it was nuts.
- [12:22]
A
Well, because 60% is almost a coin toss. A coin toss is 50%. You're a little bit better.
- [12:27]
B
Right, Right. And so, I mean, the whole. I don't know, the whole process is also so heavily biased towards whether you like the person or not. You know, a lot of the decisions made in the first 10 seconds they say, yeah, but.
- [12:38]
A
But, you know, my takeaway. And I think different people take different things. But the reason that really helped me, not just at that time when I got this first job in the uk, but actually I read it later when, for example, later applied to Facebook. I, I narrowly didn't. But I didn't get that rejection act, helped me get that position at Uber, which all of these are just Kathod. And, like, what I took away from it is this is how the process is. You might not like it, but you can either just complain or think it's unjust or you can know it's unjust and you know that you just need to try hard. And when you do get it, you know, don't take it for granted.
- [13:13]
B
So how did getting rejected by Facebook help you get a job at Uber? Because if it's helpful, I'll go get rejected at Facebook.
- [13:20]
A
What was helpful is I did a bunch of time preparing for Facebook. It was very clear at the time that they actually send me materials and the preparation did not go to waste. So I learned how to do the algorithmical coding. Big O. I knew some of that before, but I really refreshed it on the spot on Facebook for the system design. I thought I nailed it because I heard the question before and I just drew up it was design Instagram. I got this, you know, no conversation with the person. And later I kind of got some feedback on like, you know, what I didn't do. And so by the time I got to Uber, I actually heard that like, again, not many people got double thumbs up, but in hindsight I kind of got the. I did get like two or three double thumbs up because I have practiced. And also I think the other thing is at Uber at the time, this was Amsterdam. So in London, a lot of people knew how to interview Amsterdam. Uber struggled to have people who, you know, understood these interviews. So I guess I stood out because I prepared year earlier so the preparation does not go to waste.
- [14:20]
B
So yeah, the preparation is so important. So important. But boy, what do you prepare for now? Like, I've got a buddy who's out interviewing right now. He's just very senior engineer and he says that the teams are all asking, they want somebody to come teach them AI. That's what everyone's doing. So they want someone who knows AI because they don't. That's the theme, right?
- [14:41]
A
Yeah.
- [14:43]
B
So what do you prepare for?
- [14:44]
A
Well, I just talked with someone again. She'll be on the podcast janvi, who interviewed 46 AI companies. She's the engineer who went to Coda, became an AI engineer there. So she interviewed 46 and she said it's a mess. And this is for mid level, so we're not talking staff level. But a lot of them are still doing the usual lead code style interviews. And then they might ask a few things about AI. And she said that there is one new type of project that she actually really likes is a project especially for AI. You know, build something based on AI and she says she loves it because she can actually show off what she's capable of doing. It seems it's a Mess. I don't think people know what to do and I don't think even a lot of companies know what AI engineer is. We'll get into this, but before we go. So you wrote get that Job at Google in 2008 and 10 years later you wrote another one called get that Job at Grab. You were at Grab. Now you would think that these two are kind of connected. But get that Job at Grab was more of an article about the job market at the time. In 2018 you wrote a quote because something very strange is going on in industry. It started maybe a couple years ago and it escalated a lot around a year ago and then went completely crazy about six months ago. What happened is this global demand for software engineers completely outset supply. And I think it might be happening because we missed a market correction sometime in the past five years. The article was basically a bit of a heads up saying the market is really hot. And now that I read it back, I was a bit of amazed because you wrote this one or two years before anyone mentioned it. It was happening. It was heating up to be the hottest job market. And you know, we saw it in 2021, it was the peak. You saw this and you were pretty much advertising it to anyone who was actually listening to whatever you were. You're preaching.
- [16:32]
B
Yeah, well, I mean they're the early warning system. The recruiters are, that will tell you what's going on with the market. Market. Right. Because they're directly in touch with the hiring managers who are the ones who are, you know, in touch with the people with the budgets who are deciding what the company is going to focus on. And so the recruiters, if you're in touch with your recruiter network. Right. You know, kind of what the trends are and all that stuff. And so I started noticing that the world was running out of engineers. Yeah, that's fundamentally what was happening back then.
- [16:57]
A
Yeah. And, and I mean, you know, like you also, I think some people were externally it looked a bit surprising because you were, you're doing great at Google and you went to this scale up Grab. I mean they're growing fast. But I think some people are thinking, well, why is TV going after Google to Grab? Why were you going by the way?
- [17:14]
B
Wow. Well, you know, I mean Geo Works, Amazon, Google, all really similar in a lot of ways. You know, GeoWorks was, was more like device software, but still. Right? Yeah, you know, Grab Grab. I had a buddy from Google who was CTO there, right. Theo and Vasilakis. And he was like, man, this is an Adventure you got to come. So started chatting with them and realized they were on just this. I mean, that Southeast Asia in general is just this incredible productivity explosion. And it just, it seemed fun. Right. And it turned out to be actually really fun. It was. And then Covid killed it.
- [17:48]
A
So, you know, back, back then like this, get that job, job grab. You did describe how the market was, was. Was really heating up. And you know, some things happened in Covid. But what you wrote here is so. So now there's a gut of investor money as creating a lot of startups. A lot of startups, including some very big ones. And they're gobbling up all the eng. And now it's a fight.
- [18:08]
B
Yeah, it got worse after that.
- [18:10]
A
Yeah. I was asked like, how did you see it play out and how does it continue all this today? Because I feel today we might see something similar in a different area. Right?
- [18:19]
B
Yeah. I mean, there's a lot of investment coming in for sure. It's coming in hot. Right. We went through a huge spike right after I posted that, because shortly afterwards was Covid. Right. Two years later we had the stimulus package and that gave everybody a lot of money. And that was like tons of startups appeared because of that.
- [18:38]
A
Yeah.
- [18:38]
B
So so much great time, founders and so great time to be a remote engineer, basically. Right. Then the stimulus package, the stimulus money went away and things started to kind of crash. And then AI came out and everybody got really uncertain. And so it kind of dipped a little. It has dipped. I think if you just look at Indeed's report, you can see jobs have dipped pretty heavily since their peak in 2021 or 2022. But we also see a productivity explosion on its way, like a boom of jobs coming. So it goes up and down. But yeah, I think at the time, at that time in 2018, the market was showing signs that it was going to. And that's what. Look, that's what everybody wants. They want to predict what's going to happen. Not just that they know what stocks to buy. Right. But also how to make the right decisions for their companies or their careers. And right now I think you and I both agree that things are kind of headed back up right now. Yeah.
- [19:33]
A
And we'll get into that. But I want to go back to a second time that. So the first time I came across your blog, I didn't really even connect the name with the face back then was get a job at Google. The second time was a few years later, which was this Google platform rant which was published on Google Right, yeah. So it was an internal facing document. Apparently you wrote a lot of these or just like rants or like meant for Google internal only. And somehow it was set to. Anyone could read it on the intro and Hacker news jumped on it and as soon as it went out, you know, people archived it as well. First of all, how did this rant came along? Because this rant has been so referenced it's now I think on GitHub as well as TV's platform rant. Because it was a really good criticism of Google. And not just that, but it was kind of a really, really realistic like picturing of Amazon, including Jeff Bezos not giving a shit about your day. Which I think, you know, people were.
- [20:39]
B
Like, he still doesn't, you know. Yeah.
- [20:44]
A
But it just felt very real and raw and clearly it was, I understand it wasn't meant for public consumption but you know, like, hey, did you write these kind of things all the time? Like, because we only saw this one thing and I've heard that you had a history of just internally just keeping it really real.
- [21:03]
B
I had other ones internally, sure. None of them were quite that, I guess accusatory or whatever. I mean like I was really taking Google to task because I was fed up. I'd been there six years and I still couldn't get a platform out of anybody. Right.
- [21:17]
A
Yeah, like Google to ship a proper.
- [21:20]
B
Platform that even internally, like the code search team didn't want to give me an API. It's inconceivable today that you'd give somebody a rest API to your stuff. Right. That's the way we think today. Yeah, well outside of Google, inside of Google, who knows, they're just not really big on internal services. They're just like use our product.
- [21:37]
A
Yeah.
- [21:38]
B
It drove me nuts. Completely nuts. I went nuts. And then a bottle of wine later, I. Yeah. Told them how it was.
- [21:46]
A
Yeah. So let's recall some of that part because I'm going to link it obviously so people can read it. But first you started summarizing on what Amazon did. Right. And what you observed throughout your time. Right. You were early Amazon, right?
- [22:00]
B
Yeah, early ish. Yeah, I got there in late 1998. It was pretty small back then. We were in one building in downtown Seattle, just a three story building.
- [22:09]
A
Wow, that's it.
- [22:10]
B
A four story building of which we occupied three floors I guess is accurate. And yeah, there was just one data center at the time and it was just a very small. It already had a cult like sort of feel to it.
- [22:21]
A
It.
- [22:21]
B
Right. An electric feel Yeah, I mean, a sense that there was something really magical going on.
- [22:29]
A
So was this still the bookstore part or was it already expanding beyond books?
- [22:36]
B
When I joined, we already had music and I think we were just launching video. Yeah. So I think we had just brought our tabs. It was really early on. I have to go back, look at the history.
- [22:47]
A
Yeah. And then like, you know, you said that. That basically Jeff Bezos mandated platforms, APIs. What did you do there?
- [22:57]
B
You know, it's interesting because I. Everybody thinks that there's a real memo. The memo was. I don't. There wasn't. Jeff wouldn't write an actual memo. Right. Why the fuck would he do that? He just tells people stuff and it happens. But the customer service organization in particular was. I was in customer service tools at the time. I may have been running customer service tools at the time. Bezos would sit with us every week in a meeting and we would look at the top 10 reasons that customers were contacting us. Right. And he'd want to know, why are these customers still contacting us? Saying they're getting triple charged for their books later. That kind of thing. Right. Number one was always, where's my stuff? Right.
- [23:36]
A
Yep.
- [23:36]
B
Customer service had a really interesting need. It may have been Jeff, you know, I've never thought about this before, but it may have been Jeff's sort of affinity for customer service, wanting to be the earth's most customer centric company, that led him down this path of forcing people to open up their APIs. Because the customer service team kept saying, we can't make any changes to Obidos, you know, our web server, because that's their code. We can't get into the supply chain code. We can't get into the fulfillment center code the customer, we can't help the customer. And Bezos was like, all right, tell you what, right. I'm going to blast anybody standing in the way of that. And what that turned into was, well, you need to provide something to the customer service technical team that's not them going and linking against your code and trying to get it to run locally in some different environment. Right. Which is what they were doing with this awful C code. So. Yeah, so that's kind of the origin story.
- [24:25]
A
Yeah. And then this was like around early 2000s, right before we even had things like services or microservices.
- [24:31]
B
Yeah, well, back then, the services were things like, they were proprietary protocols like Corba, like Solco and Teleria and the pub sub things. And they were all really nasty binary formats. And there was this Possibility to do rest. And it had been invented at the time, but everybody was kind of pooh, pooing it, saying, no, no, nobody really kind of understood it.
- [24:53]
A
No type safety, no protocol.
- [24:55]
B
Yeah, yeah. It took years, but turned out, yeah, that's what you need. You need an API. And that was the origin of my rant too. Right. Which was I talked about Amazon does stuff mostly wrong.
- [25:09]
A
This is how you started your memo. So that was actually fascinating to read. I think it was clear that you were. You were on Google's side, right? Like you're trashing Google. It very clearly came through that you actually wanted to shake things up. Like, hello, like the memo. When I read it, it felt like, hey, we should be better than Amazon. Here's all the reasons and here's the things that they're doing better. And it's not that hard. We just need to do that well, and then we will be better. Right?
- [25:35]
B
I mean, it made sense, right?
- [25:37]
A
Yeah.
- [25:38]
B
And I just felt like we were good at everything else. We were good at a lot of stuff. Google was extraordinarily good at a lot of things that Amazon had no clue had be to. To do, really. And it took Amazon years to catch up to Google in a lot of things.
- [25:51]
A
So let's talk about that. What were the things that Google is just really good at?
- [25:55]
B
Like, Google had one service called Stubby. I think I even mentioned it in the post. Called Stubby or, sorry, Chubby. Chubby was the locking service. Chubby and Stubby, they went together.
- [26:06]
A
The locking service.
- [26:07]
B
Yeah, the locking. A distributed locking service. Those are not easy to implement. Okay. We're talking, you know, Paxos times 10. You know, make sure the thing stands up all the time. It had seven nines of availability, which is. No, yeah, yeah. It's just like basically 30 seconds of downtime every 10 years. Okay. It was a very reliable service.
- [26:24]
A
Oh, wow. Okay.
- [26:25]
B
Now with one example, five nines is.
- [26:27]
A
Hard to get to Amazon.
- [26:29]
B
Seven. Yeah. Five is almost insane. Seven is just like, what? So that was just one example. BigTable early on they had like, free, basically, like, unlimited NoSQL storage with some pretty good query facilities for Everybody in the MapReduce infrastructure. Google invented it, you know, and on and on and on. Right, right.
- [26:45]
A
So, like, really, really good hardcore engineering problems solved in a, like, way that is like, just tough, tough to do.
- [26:53]
B
I was very impressed. I slapped myself, like, my forehead sometimes when I was like, I'd see some of the stuff they did. I got there and I'm like, why didn't I think of this like I had this game that I had a custom RPC protocol. When I looked at Google's which is now grpc, it was called Protocol buffers and stubby back then. You look at it and you're like, oh wow, it's a forward compatible protocol. I can add stuff to it without breaking it. But it's binary and high performance and it was beautif is beautiful. Surprise. More people don't use it, to be honest. So yeah, they did a lot of things really well, but they didn't do platforms well at all. It wasn't part of their DNA. They just didn't get it.
- [27:26]
A
And they didn't do internal or external.
- [27:28]
B
Or Neither, neither, neither, neither.
- [27:31]
A
And then so you wrote this rant which again, like, I think if you're listening to this, you need to read that rant that it is like one of the best things I've read. It's also very entertaining by the way. What was the impact? Because obviously you sent it internally, it now leaked externally. So clearly, you know, people were making fun of, fun of Google. Did it achieve that shakeup effect? And how high did this thing get? I'm pretty sure it must have gotten pretty high.
- [27:56]
B
Well, I mean, Google had a very open culture, so it got brought up at the next tgif. Right.
- [28:01]
A
Thank God it's Friday, right? It's Google's iconic Friday meeting. It's like all hands.
- [28:06]
B
Ish. I remember Ben, the guy that was in charge of our fulfillment center. Not fulfillment centers, sorry, our data centers at the time, he stood out there and said, well, you know, we all read the rant. So you know, they got a kick out of it. Right. You know, Vick Andotra was pissed. I mean, he was really, really mad, right? Yeah. Because I had like told him he had an ugly baby and very, very, very loudly in public. And yeah, you know, and, and I had used his ugly baby to do it.
- [28:35]
A
This, this was the developer saw google.com baby or something else.
- [28:39]
B
Google+. Oh, Google+. I called Google+ ugly, right?
- [28:43]
A
Yeah.
- [28:43]
B
And you know, and he was like, he was really gunning for that, the headspot at the time. And he had planted the seed of fear in Larry Page. He was like, facebook's gonna kill us. Facebook's gonna kill us. They're gonna kill us. Right? We had to have a Facebook, which is stupid for many reasons, some of which. Oh, so I'll tell this again. I'll say this again. That blog rant, that famous rant was actually part 2 of an 11 part series that I had meticulously planned out and I never finished. Cause I accidentally published the second one externally and the implications were actually so big that I was kind of like in hiding for a while. But yeah, no, I was actually picking apart Google dimension by dimension. And platforms was just one of the dimensions where it was failing.
- [29:26]
A
But you were actually right. In hindsight, I was right about all.
- [29:29]
B
Of it, but they never said sorry. I was also right about not getting into publication ads. I was right about a lot of things at Google, but I'm not very good at convincing people that I'm wrong.
- [29:37]
A
So tell me that story, because you've told me the story once in the newsletter and we mentioned it super briefly. You killed publication ads. And this was like, as. As I remember, like, what happened is you joined Google and then what did you do?
- [29:51]
B
First time I went around to all the projects, I was allowed to pick whatever I wanted, and I picked print ads because I thought it sounded like a cool challenge. I became a domain expert over the next six months, learned everything there was to know about magazines and newspaper publication ads in the United States and concluded that we were never going to make a dime. That all of them hated us and blamed us for the declining revenues and they wouldn't want to talk to us. And we were. And I wrote it up as a big decision tree. I said we could try this. We tried this. It didn't work. Tried this. The whole thing. I mapped out the entire decision tree of everything you could do. And they said, well, what about illegal stuff? And I was like, I'm not going to entertain any of that stupid stuff, all right. It was like, they didn't put that in writing, but it was like, what if we just sucked up the phone book type stuff? Right?
- [30:32]
A
Yeah.
- [30:34]
B
So I declined. And then they got mad and they sent it to other teams and the other teams failed and came back to me for my postmortem.
- [30:41]
A
So they tried to make it work.
- [30:43]
B
They tried again in Mountain View and then they tried in England and they couldn't do it because I was right. I never got so much as a I'm sorry or a thank you or anything like that. No.
- [30:52]
A
Yeah. But like, you concluded this is not worth it. So you.
- [30:55]
B
You.
- [30:55]
A
Well, first of all, you said, like, if you. If you were you, you wouldn't do it. And then you moved on to the next thing, and then they failed to retweet. Well, like, sounds like twice.
- [31:04]
B
I did make a proposal in the postmortem which was very similar to what ultimately Turned into Group Groupon.
- [31:09]
A
Yeah.
- [31:09]
B
Yeah. So, you know, I mean it wasn't like complete shooting it down. You could do one thing, but I said, you will need a sneaker network of like 8,000 people somehow. Right. Which was what Volt Groupon ultimately did.
- [31:20]
A
It's fun to be right. It sounds like, you know, you just like, you know you did the best that you could, you gave the best. And then you also like, sounds like you were like, look, if you want to try it, like do it. But like, I don't believe, like, I believe this will not work. I believe we could try this and then just leave it at that. Right. Like, you know, you did what you believe then.
- [31:39]
B
Yeah.
- [31:39]
A
What do you think happened to Google? Like, I, I remember, you know, Google launched Wave, which kind of like died down pretty quickly.
- [31:47]
B
It.
- [31:47]
A
It was supposed to be the next email that, that was the first time I was like, I, I remember like this early 2010s, Google could not do anything wrong. And every, every time they launched something, I was like, wow, this is the next big thing. They launched Google app engine. I was like, it's the, the coolest thing. And I onboarded and it was so cheap. It was ridiculously cheap. Later I figured out why, because they were subsidizing it. But Google Wave was the first one where I remember all the online portals, TechCrunch, etc. Was like, Google has replaced email. And we're like, oh, wow, Google has replaced email. And you tried it out and didn't work. And then Google came along and I think we understood from the outside, not as Googlers as like that Google was trying to really take on Facebook and if they didn't succeed, you know, Facebook would win. And I don't think we. From the outside, it seemed like it was kind of going to go and going. Yeah, it was pretty ugly. But then, then it just kind of stopped. You were on the inside, like, how did this play out? Because I think we've heard there's books about Facebooks went all in wartime. They were working hard and they actually saw this as a major threat and it energized them. What do you think might have been drawn there? Or how much vantage point did you even have on this?
- [32:56]
B
I mean, I was there. I talked to people who were in the heat of it. Wave was targeting a space that ultimately got solved by Slack. Slack was the right form factor and Wave wasn't. And when I saw Wave, I was totally unimpressed. But it was like they had cast a spell over everybody. And I Didn't see what, I didn't get it right. But I got slack instantly. Right. We all did. So it was very similar. I think it was Google had trouble, struggled to find the right form factor. This was why I wrote that 11 part series. It's because I knew that if they basically acted right then and got Reddit, just took them, just bought Reddit. Okay. And took over that sort of, that social network, they would have had something. They would have had something. This is long before Reddit was in the top 10 in the U.S. right? This was. Right, this was. Reddit was hot. That only were like tech geeks. Right?
- [33:47]
A
Yeah. Digg was also big back then.
- [33:51]
B
Digg? Yeah, pre digs blow up or whatever.
- [33:55]
A
Oh yeah.
- [33:56]
B
So I wanted them to, I wanted Google to start either build a Reddit that was done kind of like slightly better because you know, Reddit evolved and even they want to change it or something, fix a lot of things because it had to be different from Facebook or people wouldn't be able to migrate because the network effect fundamentally. Right. And Google just, I mean it's so weird, man. Companies are like people, they're like human beings. They like, they like, they just, they make decisions and the decisions can be just absolutely terrible and everyone around them knows it and they're all embarrassed and they try to tell the company and the company's like, don't tell me what to do.
- [34:30]
A
Yeah, that was, feels like it. So, so now looking back so many years later, you know, you've left Amazon like, I don't know, like 10 plus years, even more. Same with Google. How do you think Amazon, 20 years. Yeah. How do you think both Amazon and Google have changed, but also in what sense have they not changed?
- [34:52]
B
I think Amazon's changed way more than Google. You're the first person ever to ask me that. So thank you. Amazon has improved dramatically in almost every possible way that you could improve.
- [35:01]
A
Really?
- [35:02]
B
Yeah. Amazon has always executed better than anybody on earth. But they found a way to do it without, you know, having all of the flaws that I mentioned at the beginning of my post. Right. Yeah, they've. It's really, it's quite nice now and people that I know who work there are pretty, pretty satisfied and they're doing well and they still execute well. They're a company that makes good decisions by and large, just like Apple. Of course they fall on their face once in a while. What company doesn't, right? Google has not changed since the fucking day I joined. End of story.
- [35:37]
A
So recently someone at Google was asking me about like what do I think about Google's developer story? And I said like do you want me to be honest? I said developer what? And my example that I showed this person is flutter versus react native. Now react native is about 10 full time people at Facebook and a few other in the core team and maybe a few other people from some other companies, maybe like 15 person. But Facebook invests like 10 full time people. And if you go to the showcase page of React Native which is where you show you immediately see logos, Meta, Microsoft, Amazon, I think they have some one big just like flagship apps and then you have oh and then you have Shopify. You have like all these big companies and you know you will find the blog post Shopify says, why we went all in on React Native. Why we have thousands of developers working on React Native and you have all these case studies. React Native is inside of Meta's Facebook app. It's inside Instagram. It doesn't run the whole thing, but it's in there obviously their ads up. And then you go to Flutter. Now Flutter has at least 50 full time people, so five times as many. And you see some small Google apps on the top, it looks nice but then you scroll down and it looks like an intern made that page. Like you have some random Chinese app that you never heard about and then BMW which is a brand that you know it's somewhere in the very bottom. And like there's no apps, there's no big apps, there's no big logos outside of. And even for the Google logos, Flutter is not using any of their flagship apps apps. So I'm like startups who are deciding which ones to use just based on this, they will go for React Native. It actually has the street cred. And I asked someone at Meta like how did you guys pull this off? Like with a smaller team you executed clearly what I think is better in terms of you got the big customers, you're building for big. He said at Meta everything is about impact. And the React Native team, the first thing they did is drive impact. They got React Native inside the biggest apps into Instagram, Facebook, etc. And then the rest came because Shopify is like, well if it's used inside of Facebook with I don't know how many thousands of developers we can use it as well.
- [37:48]
B
Yeah, I mean look, Google can't afford to be disintermediated in the mobile space. They can't afford to just become the plumbing that people can swap out and that's always been an existential threat for them. The Facebook application is a platform itself, and you can write applications inside of it. And so if you're writing for the Facebook platform, and you're the New York Times or whatever, who cares if you're running on Android or iOS? And that's Google's worst nightmare, right? And that's why Facebook, in the age of AI, hasn't laid off the react native team, because that's their basically, hey, you don't own Android, we do. Right? That's their play. And so Google, they'll never give up on it. What happened was, unfortunately, Flutter's not from the Android team, and that pissed the Android team off, because Android has politics. Android was an acquisition. The guy that ran it was very particular about them being sort of in charge of their own destinies and not beholden to anyone else. And he kept Android sort of running the way that they ran it inside. And they made all the decisions, and the buck stopped there. Flutter came along and sort of threatened their dominance as the platform, and it pissed them off. And Google has been sort of unable to reconcile those things even since 2018, when I was looking at this problem. 2017.
- [39:03]
A
Yeah. And one of my biggest question marks about Google and why they have not changed this is. Is around their cloud platform. So when I worked at Microsoft, well, I like to say Microsoft, it was Skype, they just bought Skype and they left us alone. So it was Skype. And then when they turned Microsoft, I kind of. I was like, all right, this is. I don't like that much. But they gave us a mandate. They said, you need to use Azure. And we were one of the first, like, we were the new purchase. So they just dumped it on us. Azure was not ready, and I was sitting next to the data team, the Skype data team, who had all our data centers. And they're moving over and they're saying, it's just a huge pain. It's like, we don't want to do this. But it was actually Ballmer was forcing it on them, and it was this blood, sweat and tears. And eventually they moved. But what I've seen is, like, over time now when I talk with teams at Microsoft, what are you guys using? Obviously, they're using Azure or Bing might not be using it, but it's fun. AWS is using aws, and I talk with teams at Google. What are you guys using? Borg? Like, hold on. Why are you not using gcp? Well, it doesn't scale. It doesn't have the things we need. And how you can you be gunning to be number two or one day maybe number one cloud platform if your own company comes up with excuses. And I never understood, I tried to ask this, like on back channels from people working at gcp and they always come up with excuses. But I don't understand how is it that it's the only cloud company that does not use its own cloud service for their flagship service, for the flagship products?
- [40:28]
B
I think it's all just who's been the most successful IT marketing and convincing people that they're using their own clouds. But they are all, all currently huffing their own farts. Amazon doesn't use aws.
- [40:40]
A
No, I heard.
- [40:41]
B
So Sable ain't aws.
- [40:44]
A
Okay.
- [40:44]
B
I mean, like, right, for the retail side, for the ad side. I mean, like, of course they want you to use aws, but all the core, the core, core, core stuff and they haven't migrated, man. So like, it's all frou frou as far as I'm concerned. Right? It's all like, I think it might.
- [40:57]
A
Have changed because it is less. They had a name for the old stuff and I think more and more.
- [41:02]
B
Things are moving over. That's fair. Never bet against Amazon. AWS may have actually graduated to the point where they can actually use it internally. The hurdles for Google were insurmountable.
- [41:14]
A
So maybe this is fair, by the way, so maybe this criticism is not entirely fair, because what I understand is their infrastructure is way bigger and more complex than anything else.
- [41:23]
B
It's sort of fair to say that Google's cloud runs on top of Google's infrastructure, which actually does scale the biggest in the world. Much bigger than Amazon.
- [41:32]
A
Well, one thing that I am wondering, because I'm still waiting for what will the tool or platform be that Google releases that their internal tool teams use it, and they're like, oh, we have 100,000 or like 50,000 or 100,000 software developers inside Google using it. You should use it. Microsoft did this with Visual Studio.
- [41:51]
B
Non Googler.
- [41:52]
A
No, it's not some Google tool. I'm thinking, thinking, could we see this maybe with some AI tools, you know, like AI coding tools, et cetera. Like, could they finally do this? Or maybe this is just not a Google way to do it. They'll be like, all right, we have our superior internal tools and we will build an external thing. You know, we have Borg. We'll build kubernetes for everyone else.
- [42:09]
B
I don't. I just. I don't think Google understands developers. I don't think they ever did.
- [42:16]
A
Ironic.
- [42:17]
B
It's really closely related to Their blind spot around platforms. Right, right. If you don't get platforms, it's because you don't understand developers.
- [42:23]
A
It's just ironic because Google, like no company or few companies treat developers as good as Google does. Right. In terms of.
- [42:30]
B
Yeah. And few companies, few companies have built a platform as incredible internally as Google's is. You know, at, at the sort of foundation level.
- [42:39]
A
Yeah. You unretired, you retire for, for, for, for some time and then you unret because of. Well, initially Source Graph, but then also AI. What made you kind of come back into the game?
- [42:53]
B
It's not a binary thing. I've been gradually unretiring, if it makes any sense. And it's because at first I was like, you know what? I'm really climbing the walls. I really want to just go work with some people. And so that's where I wound up at sourcegraph. That was familiar ground, right? That was Google code search for everyone else.
- [43:10]
A
Yeah.
- [43:11]
B
And then shortly afterwards, the AI showed up and I was like, like that was like the next step up is, oh man, maybe I better get back into coding again for a while because this looks really different.
- [43:21]
A
So, so fun fact is, last time we talked about three years ago, you were head of engineering at Source Graph. And actually people told me at Source Graph you came in, you made some changes which were actually like pretty well received. But like, you shook up. You introduced where people could job there, that kind of stuff. And then next thing I know is like, oh, you wrote this. Like you write about everything. Which, you know, if we'll link some more things. But I love writing it. But you wrote, wrote about like, oh, I'm stepping down as heavy engineering because I'm going back to coding, which was not what I would have expected again from just.
- [43:53]
B
And I view that as another step in me sort of coming out of retirement. Right. Because I had given up on coding. It wasn't worth it anymore. Kent Beck had given up on coding. A lot of my old buddies and colleagues. Right. You know, it's just like environment setup is just over the top these days. Right. And you know, just building a simple web app, you probably have to use, you know, 25 different frameworks, many of which have incompatible competing, you know, whatever.
- [44:18]
A
Yeah. And as soon as you update to the latest react thing, all the routers breaks and you have to relearn again.
- [44:22]
B
Who wants that? And so at some point you get tired of it and you're just like, I'm done, man. I can't. This isn't, it's not worth it. Right. And AI completely turned that on his head and I saw it coming as soon as ChatGPT came out, I was like, oh wow, look, you can write an actual function that's reasonably good, right? And then when 4.0 came out then I was able to project forward with an exponential growth and say, uh oh, uh oh, you know, it's coming. So now I'm getting sort of like more and more fired up with each passing month.
- [44:50]
A
This episode is brought to you by Sonar, the creators of sonarqube, the industry standard for integrated code quality and code security that is trusted by over 7 million developers at 400,000 organizations around the world. Human written or AI generated. Sonarqube reviews all code and provides actionable code intelligence that developers can use to improve quality and security. Early in the development process, Sonar recently introduced SonarQube Advanced Security, enhancing Sonar's core security capabilities with software composition analysis and advanced static application security testing. With advanced security, development teams can identify vulnerabilities and third party dependencies, ensure license compliance, and generate software bills of materials. It's no wonder that sonarqube has been rated the best static code analysis tool for five years running. So join millions of developers from organizations like Microsoft, Nvidia, Mercedes Benz, Johnson and Johnson and ebay and supercharge your developer to build better, faster with sonar. Visit sonarsource.compragmaticsecurity to learn more. One thing that has we've talked a lot in the industry and everyone's talking about it is how AI will first and foremost, I think like experienced developers, we can get there, but how will it impact junior developers? And you wrote this again, controversial title, the Death of the Junior Developer, but interesting enough when you read closer. A lot of your articles are like this, by the way. Like there's a title which you think like, oh, it's the end. But a lot of them are wake up calls. To me, when I read it properly, it wasn't like, oh, there's no more junior developers. It was a wake up call saying, hey, if you're a junior developer, you need to get your stuff together quickly and whatever the junior developers before you were, it's not going to work for you. So like, what is it that you've seen and like, did something inspire you? Did you like see some young titans who are actually just doing great with these tools?
- [46:45]
B
Man, you've hit on a question that is just so fundamental and foundational to our industry right now. It's shaking the industry, that question. And the answer is, I mean, the shortest way that I would think about it is AI is not easy to use and the more senior you are, the more likely it is you're going to notice when it's being bad, when the AIs become naughty. It's just common sense. And the AI is very naughty and in very subtle and insidious ways. And even as they get smarter and they are getting exponentially smarter and they will be frighteningly smart within a year, they will still, I mean software is always bigger than they are, right? And they will still make silly, do silly things. And it's just going to bias towards more senior people. But it's not really seniority. We learned it's nothing to do with junior and senior. It's really more about who is demonstrating the ability to work well with AI and get good outcomes in software. And that could be anyone who could be a product manager. So I think there's a big shakeup coming where the roles change and everybody becomes, becomes more focused on what they're building instead of like who's building it. And have you heard about the collapsing the stack stuff from Scott Belsky?
- [47:53]
A
Can you refresh to know basically like.
- [47:55]
B
There'S a line of thinking that we've over specialized and everybody's like incredibly domain expertise specialized. And you got these senior engineers at Google who know exactly how the Fuse file system drivers work for every version of the Linux kernel, right? It's like we don't have that anymore. We don't need that. That's, that's stupid. That's going away. But all the specialization is going away because AI is democratizing all of it. You can't hide that knowledge.
- [48:17]
A
This is interesting because I just talked with someone I think a week or two ago about how what has changed in software engineering even before AI and what has changed back in early 2000s when you looked at software developers, you had the Java developer, you had the dot net developer, you had the Python. And these were different people. It was the Java developer would not do.net even though they're pretty similar. So there was a. And we had we on the backend. Languages were specialized. Fast forward to even before AI, like 2015 or 2018 when we had a big hiring firm. When I worked at Uber, we no longer Uber was seen as like oh, this completely changed. We didn't care if you did Java or. Net or whatever. You come you know one of those languages, you'll pick up whatever we're doing. And at some point my team was doing Go Python Node JS and what else we're still doing something else but we're doing all of it. So we started to have less specialization. So I wonder if this thing started earlier and maybe AI actually just makes it more viable that now until now we've had a front end engineer would not touch back and they might understand the concept of APIs, but now they actually can. In fact, when the product manager can.
- [49:26]
B
Actually create pull requests, we see that now. Right. Like at Sourcecraft, one of our UI designers is now sending pull requests for the UI instead of asking engineers to do a deal.
- [49:35]
A
And are they an engineer any good or they're actually decent or.
- [49:38]
B
Yeah, look, I mean it's all over the map. It's just like I believe this is the new role for junior developers is they're going to be mentoring the next layer down of non technical or technical adjacent people who are now starting to contribute PRs. Right. And they'll be the ones who are like helping them fix the security issues or whatever else they have with their basically teaching junior developers because they're still trained engineers so they can teach like a UX designer or product manager. What are the right questions to ask the AI about your thing to know whether you're done or not yet. Right. You know, give you those kinds of skills.
- [50:12]
A
I like this because I think we all know things will change. I think we're all struggling to like put the finger. Exactly. I mean you clearly have a bunch of conviction which I think is great because I think you need conviction in this areas of going around them. And I have been so, you know, you work at Source Graph, you guys are heavily using your AI. In fact, you have your own AI tool but you've been using the existing tools from the beginning. And most of the stories I'm hearing so far about a non technical person doing technical stuff is at AI companies where they're surrounded by these people. Windsurf co Founder CEO Varun he told me that they have, I think it was a salesperson who had a sales tool and they just kind of vibe coded it with Winston. Sure. It had no state, it was super simple thing. It's not complicated. But that person did it. And I wonder if we might be seeing these type of AI or just very sharpie environments lead the path of what the legacy or larger companies will be in 10 years.
- [51:14]
B
Yeah, absolutely man. We're seeing it everywhere. I mean we're seeing companies where marketing teams are writing their own outbound campaigns software, you know, we're seeing product teams, you know, bypass vendors. They don't have to re up with Their renewal of the contracts with some crummy vendor software because they wrote their own and had somebody from engineering just vet it and be like, okay, yeah, you can make these two changes and then you can.
- [51:37]
A
I want to ask you a little bit about that because I'm a bit skeptical about that. Do you, have you seen like specific examples of what they replace? Because for example, with workday you're not going to replace that which has all the compliance, a lot of state, a lot of regulation, a lot of ongoing maintenance. Like that is not what you're going to. But what are the things that you've seen?
- [51:56]
B
Well, this was a. So imagine a company with a lot of really bad actors coming in and trying to crawl over the site and find fan bad ways to basically siphon money out. So they have many, many different kinds of teams that are looking at different kinds of fraud and different kinds of attacks. And there are lots of kind of bespoke tools. And so you get into this long tail of little vendors that offer these crummy tools that are really expensive for some very vertical domain specific. And so the product team at this one company was like, screw it, we're going to ask AI to be build it. We'll give it the specs, we know what we want it to do. And they built it, you know, in Python, you know, and so it wasn't production software, it was software that they use as their investigation trying to find bad actors. Nevertheless, it saved them from a re up with a contract that was rather expensive and it gave them, they were happy, right? You know, they had full control over the software. They can make it do whatever they wanted at that point. So what they were starting, I mean this is just one of probably a dozen examples I could give you.
- [52:48]
A
But we're seeing, but let's, let's carry on that thought because you know me, we built software. We've seen the internal tool that the team has built. In fact, you know, Google is famous for building all the internal tools. What is the next step? So like can we just move? Because we know what's going to happen, right? As experienced people who are working software. So what's happening next year when there's like more functionality to be added, how far might be able to take it and what's going to be the breaking point? Because this happened before AI, right? Like one internal developer wrote it and at some point it, it becomes like just a pain, right?
- [53:20]
B
Yeah, look, I predict I, I'm going to go around on the record and I'm going to Predict that there is a new role, a new category of roles that's going to emerge that are the Winston Wolfs that are going to come in and fix shit that you broke with AI. They're going to be fixers and they're going to come in and they're going to be small and large.
- [53:35]
A
You name actually call them, let's give this role name, call it Fixers. A cool name.
- [53:41]
B
I don't know. Fixer sounds pretty good, but whatever, right? I, I do think of them as fixers. And is this sense that like you've made a horrible mess, you've realized that, that, that this company that promised the world to you because like something like 60% of all the world's programmers are systems integrators. They go to big companies that are desperate and they say, we can make your systems talk to each other and it'll be really expensive and 70% of the projects fail, but companies go for it anyway. That whole, that whole economy of rich countries sending work to poor countries, the architects and all that. Yeah, that's all getting turned on, potentially turned on its head because we don't know who's going to be doing the work now, the actual implementation. Right. Is it the rich countries that are going to do it for themselves? Now a lot of economists are looking at this problem right now, right?
- [54:18]
A
Yeah, but we've seen this with outsourcing. Don't forget the whole idea with outsourcing from the 90s. I kept hearing like, oh, all the highly paid developer jobs will go to India or Asia because it's cheaper. And then it happened, but also didn't happen. Right?
- [54:33]
B
Yeah, that's how. I mean, look, I think, look, it's going to ultimately be cheaper. If a human being needs to babysit 10 AIs to get a product project done, it's going to be cheaper to have that human being be in Vietnam than in, you know, in the uk.
- [54:44]
A
But, but what the reason we have developers sit next to the business, because when we're sitting next to it, you can actually talk to them. And that, that communication that I, I've seen this, you must have seen this a lot. So when I was at Uber, we, we did this round robin and Uber still does it to this day, just like HQ is there in San Francisco and it's, it's very expensive to hire. Amsterdam is half the price and India is one third of the price. So there's this round robin of like, okay, let's hire people in the US and like, oh, it's expensive let's hire in India. Okay. We hire for a while. Well, it turns out you can get, like, less experienced people. There's communication issues. It's kind of breaking down. Let's now hire an Amsterdam because it's closer. It's kind of midway, and then it comes back at somebody. Let's hire. And it just, like every few years it goes to the next one and it's just repeat like. Like they're cutting Amsterdam and now they're actually hiring. I'm like, right, yeah. It's been like four years.
- [55:35]
B
Outsourcing is one of those classic expansion contraction cycles that a lot of companies just go through periodically, along with centralizing and decentralizing QA or centralizing. Decentralizing TPMs or whatever. Like, they just, like, they'll try both and the grass is always greener. They can never make up their minds.
- [55:53]
A
So your new book is. The title is Vibe Coding, and it's a heated debate if you should even call it Vibe coding because of definition. So let's start with. What do you define as Vibe coding?
- [56:06]
B
Vibe Coding is when the AI writes the code.
- [56:08]
A
All right?
- [56:09]
B
There's a reason that that definition is going to win. You can't put an if clause in a slogan. Use Vibe Coding. As long as you're doing a fine print, which is what they're trying to do, is they're trying to put a condition on it.
- [56:22]
A
I agree, by the way.
- [56:24]
B
Do that.
- [56:24]
A
No, like, cat's out of the bag. That's how I've heard people use it as well. It's like, you know, like, some people use it for prototyping. The point is, like, yeah, you're kind of like, I'm in this vibe. I'm telling. I'm letting it go. It often is an Asian mode, you know, where it kind of goes and does stuff. But it might also be. I might kind of rein it in, but it's just like, you know, like, vibing, like. So I think this stuff, I think because a lot of people are pointing to, like, the Andre Carpath, like, tweet or however he defined it. And yeah, I think it'll just come into, like, whatever.
- [56:56]
B
The question is, is it giving you a buzz? Like, for real? Because programming can give you a buzz when you get into flow, right? You can get an actual buzz going. And you know what? It is insanely addictive. Claude Code and Friends Source Graph amp. You know, try them out because, wow, they're like a dopamine hit. It's like a slot machine. They're literally Addictive.
- [57:16]
A
I mean, Ken Beck told me the same thing and I've experienced the same thing. Like, I have this side project which I just don't like to touch because. So I try to build my APIs on the side and not pay vendors when I can, but it's just a hassle and some are on aws and it's a hassle to remember how I deploy. But with Windsurf, like, I had one of. I just built a small API on how people can claim perplexity and Kagi codes if they're paid subscribers to the newsletter. And I connected with an MCP server, I connected my database, I can just talk to my database. And I asked it like, oh, how many people have requested codes? And they're like, oh, today there's like, like the last 10 days. Like, oh, nine days ago there were like, 20, 30, a thousand, 2,000, 3,000. I'm like, hold on. Like, what is going on? Like, that doesn't look normal. I was like, can you analyze the patterns? Unusual patterns? And then it told me how, you know, like, there's the same email with different cases and I needed to code a fix for this, but I was about to have dinner and usually, like, if I don't have like 30 minutes to code or an hour, it doesn't make sense. I had like 10 minutes and in that 10 minutes, I got like a fix done. I went and had dinner. I actually was, you know, present on the dinner. And I came back and I, I got back into. And in a total of 30 minutes, I did stuff that would have taken me, like, even if I had the hands on, like, two hours easily. And. And I felt like, hold on. I'm no longer worried about, like, falling out of the flow. So, like, there is a lot of new stuff that it does make make you more productive. And, you know, as experience, experienced developer, like, it's amazing. Now I understand why Kent Beck is saying in 52 years, he's never felt this good about or this excited about writing code.
- [58:54]
B
A lot of your listeners listening to us right now have no idea what you're talking about because they haven't actually tried the terminal app versions of these things like SourceGraph AMP and Cloud Code and Codex from OpenAI or Klein. Right. You know, and by the way, Klein is going to start taking on real, real importance being able to run local models as soon as local models reach where cloudsonnet is today. Because cloudsonnet is very viable if you keep it on the rails. Because, look, let's face it, the Reason people are screwing this up and saying this doesn't work. And I don't understand why AI works and all these stories are bs. It's because it's very difficult to wrap your head around the fact that you can't get an answer out of the AI. All you can do is converge on an answer together with it. Okay. Even if it's an agent running off and doing things, you're still doing it together and you're going to eventually converge on the right answer. Hopefully most of the time. Sometimes you have to go try a different model, right. And you will very quickly learn the limits of their sort of cognitive ability and that will be the constraints that you have to work within. And it's not easy, man. It's not easy. People expect it to be easy. They want it to be handed to them.
- [59:56]
A
Well, and also people. I think there is this strange. I'm trying to put a finger on it, but like the first time I used ChatGPT, it was magic. It was like mind blown. I think most of listeners have had this experience. The first time I connected my MCP server, my database, in my case it was Windsurf. It could have been cursor, it could have been anything else. And I solved something with the agent. I kind of guided it, but I was just a bit lazy and I knew what I wanted to do and I kind of stopped it and got it done and it got it done so much faster. There was magic. But I have a feeling that with ChatGPT the magic faded after a while. It was magic initially, but then it's work. And I think somehow a lot of people either get disappointed after the magic doesn't continue. And my most surprising conversation was Simon Willison, who has been the creator of Django. He is a super productive developer. He writes so much code written for AI and he told me that this thing is hard and in two and a half years of nonstop using it, he keeps learning and to me there is this contradiction. It feels so easy, but it needs so much work. What is going on?
- [61:06]
B
Yeah, that is a really weird contradiction, isn't it? It feels like it's making your life incredibly easier and yet it's very, very non trivial to keep the thing on the rails. It's like a toddler with a chainsaw, right? Seriously. Okay, let me tell you why. I'll tell you one reason. This is from Jason Clinton. He's the cisoed anthropic and he was kind enough to share with us after I whined at Gene Kim's Engineering Leadership Conference a few weeks back. I whined that Claude had deleted all my tests and said, your tests are all passing now. Which is true. They had passed away like they were gone, dead.
- [61:36]
A
It deleted it.
- [61:37]
B
It deleted them. And it's like, all tests pass now. And it's like, well, God damn it. Right? I mean, you know, and so Jason told us. Well, what happened was Claude was trained on a reward function, and it wasn't trained not to hack that reward function. Okay? And so it will cheerfully hack it. And so that's the state of the art today, is it will tell you it's done. And what you have to do is say, no, you're not, and send it back to the drawing board.
- [62:00]
A
Ken Buck was literally saying the same thing. He calls it a genie, which is it grants your wish, but sometimes in unexpected ways.
- [62:06]
B
Basically, it's a monkey's paw sometimes, right? Yeah. You gotta be really careful how you phrase things. You know, how you know the moment, you know, you're a modern programmer, when you come down and sit down in front of your computer one day and realize you don't have any instances of any IDEs and open and you're writing more code than you ever have in your life. So if everybody listening in, if you've got an IDE open and you're looking at source code, you're doing it wrong. Isn't that funny? Man, people are going to be freaked out about this.
- [62:30]
A
So until AI really took off AI coding tools, one of the hottest topics that I discussed and I think was on everyone's mind is developer productivity. And specifically the question of whether should we measure PRs per developer or not? Because at Uber, they were doing it, and it was helpful in some ways. But I recently talked with a startup who is doing a developer productivity tool. They're launching a new startup, and I told them, they're like, oh, we're thinking of measuring PRs or not measuring it. I'm like, hold on, I think you're doing this wrong. If we're looking ahead, the question is not if developers are doing Hamit and prs, you will be able to do however many you want. But we need to think about what will productivity look like? Because now looking at the output of how much code doesn't tell me anything. What would tell me something is if I sat next to someone, for example, are they actually reviewing the code before it goes into the code base? Are they challenging the AI instead of just buying the LGTM looks good to me and sending it back and I'm not sure how this is going a little bit to end during leadership, but there is going to be this big question of what does. Actually, I'm going to ask you this. Fast forward to two years. Let's assume these tools evolve or they will not be worse, but they will be better. Better. What do you think a really productive software engineer will look like in terms of what they do, not what they measure, just what they do?
- [63:49]
B
Yeah. First of all, I got to share Kent Beck's toboggan analogy. He's like, using these agents is like being on a sled going down like a ski slope. You're going really fast. You're not really in control. You can steer it. And unfortunately that is the state of the art right now. That's what software engineers who are embracing this and they're spending thousands of dollars a week, right? Yeah. Which is why clients going to become so important, why local inferencing is going to be so important. The only way for vibe coding to become truly sustainable.
- [64:17]
A
Hold on.
- [64:17]
B
Is for it to be local inference.
- [64:18]
A
I'm going to stop you there. You're saying they're spending thousand dollars a month. Who a week? A week. Who's. Who's spending it? Because now what I'm reading is like, oh, we're not really going too much over with like the $100 Cloud Pro subscription.
- [64:31]
B
I personally get a bill from Anthropic for $220 about every day and a half or two days. It's absolutely insane. Insane.
- [64:37]
A
So I am desperate as a professional developer.
- [64:41]
B
Yeah.
- [64:41]
A
And you're seeing this with like teams that you're working with. Like, you have some insight into a lot of other engineering teams, right?
- [64:48]
B
Well, yeah, we have people use an amp. We know how many tokens they're spending. They're token pigs, man. These agents, they solve problem. All the problems you've ever heard about with AI, they solve by just brute forcing it. Oh, I hallucinated something. Let me fix it. Oh, that was a hallucination too. I'll fix it again. And. And they keep going until they get it right at your expense. But it's still way faster than you could have done. So you can't not program this way.
- [65:12]
A
But this thousand dollars, are vendors swallowing it or companies are actually being built for this publicly? I haven't heard too much chatter about this. Maybe it's because it's mostly indie devs sharing on social media and corporate devs. They might not just care.
- [65:26]
B
No corporate devs. Look, you know who's using These coding agents right now in corporate operations, the CTOs, for some reason, we've noticed a pattern where the CTOs are all the ones who kind of get it, right? The global network of CTOs, they get it, they understand what's happening, and they understand the terrible, terrible economic trade off they're going to face, which is how many engineers do you fire in order to pay for the rest of them to have AI? Because it's very, very, very expensive right now. This is why I keep bringing up client and local inferencing, because you're going to find real fast that as soon as you start running four agents, you will find. Feel like Poseidon, like navigating the seas, right? You'll feel like a deity. Right? How productive you are. 20,000 lines of code a day I've written for an entire week, sustainably. But it will cost you. You'll have to do a bank heist.
- [66:10]
A
Yeah, but where does all these lines of code go? Because one example that stuck with me recently, it was on Twitter. I'll have to credit whoever it was, but they told their agent, look, I want you to solve this problem, which is, let's not do two things at once. Basically, locking. And the agent spun up a new Redis server, added a new service that implemented optimistic or pessimistic locking. It was like 4,000 lines of code, and it was a Rails project. The person was like, hold on, maybe don't do all that. And then it kind of went on and did something in Redis. And in the end, because this person knew Redis Redis, it just needed to use a keyword that does the locking. And then it kind of told, just do this. But the point is, these agents can write a lot of code. And I'm wondering about two things. One, how sustainable is it? Because we've seen junior developers, even before AI, just like spitting out code. And then what's going to happen with maintainability? And is it good code? Is it the code that you actually want? Because I'm also hearing that people are using agents are writing the first thing, but they're going back and they're kind of changing it to keep their coding style or to tidy it up, that kind thing of stuff.
- [67:22]
B
Yeah, look, I mean, the answer is you can do all of this as a professional engineer today, and you can get a gazillion prs through if your organization is willing to absorb to speed up the bottlenecks that emerge when you start generating code at that rate. And some organizations are, and some organizations aren't. Willing to let that speed up. And you're going to start seeing them separate very quickly. And of the ones who decide to do it, you'll see some of them turn into training wrecks that become very public potentially. And then you'll see some of them succeed. You really want to be in the I tried it and I succeeded category, I think. And that means you're going to have to take some risks. The only advice I would give people, I would say look, because our book is 300 pages. How do you write 300 pages about vibe coding? Can it really be that hard? And the answer is Gene and I spent five months, we wrote the book in a month after spending five months doing deep, deep deep dive, researching on how do you push the LLM and vive coding in different ways and found a bunch of anti patterns and found a bunch of patterns and found that it's extremely hard, it's non intuitive. Nobody's born knowing how to do it. It's completely new to humanity to have these sort of human like but non human, distinctly different helpers. And the best advice that I can possibly give you is give them the tiniest task, the most molecularly tiny segmented task you can give them and if you can find a way to make it smaller, do that okay at a time, keep real careful track with them on what they're working on at all times and then own every line of code that you ultimately commit. And if you follow those rules, then you'll be astoundingly productive without causing that. Man. Dude, I've already personally caused so many nightmares because Claude hacking its reward function and saying, hey, your tests are all done right? So I mean like this is not easy and it's not going to get any easier. That's the painful part, man, and that's what people are struggling with, is the AIs will get smarter and they won't hack the reward function anymore, but they'll have some other problem and there's always going to be another problem and it'll never be ready enough for somebody to come in and just like it just works. That's what everybody is asking for and what they want. And you hear on Hacker News, anytime anybody says I've been successful with AI, everyone says, well I tried it and I wasn't successful. They're not realizing that, that you can today, but it's not a freebie, it's a tool that you have to learn how to use.
- [69:39]
A
So in the book you use an example of when you kind of turned the page of like actually believing this stuff which was around your game that you have been building for. I remember actually when you retired, you announced that you're working on this game and you were making some progress and releasing it. What happened there in terms of using AI to get back to the game and what was the outcome or where are you with that game right now?
- [70:02]
B
So, and what is the game for.
- [70:04]
A
For those who don't know?
- [70:05]
B
Oh, the game's called Wyvern. It's a. It's a. It was a hobby game I started in 1995. It's a massively multiplayer, like you know, RPG online, you know, but it's 2D, all 2D, sort of pixie sprite graphics, super, super high speed animation though, with like spells flying around and stuff. It's a lot of fun, man. People love it. There's. They have a soft spot for it. People continue to play the game for literally decades. Oh wow. And I'd have. I have volunteer contributors working on it right now who've been working, working on it for years and years and years. So labor of love for sure. During that time when I said I was working on it during COVID I got it on Steam and I got a bunch of cloud overhauls done and modernized it and it was all really fun. But the player base got so excited about it and they asked for so much features, right? They asked for so much work from me that I buried. I suffocated me as the owner of the game, right? And so I gave up and that's when I was really done coding. And then AI is of kind come back and put it all back on the table for me. I realized, oh my God, this thing can churn through my bug backlog that the players had asked me to go fix, right? And I'll have time to spare, right? And this is why, I mean like this is why people are coming out of retirement right now.
- [71:15]
A
And then so on that game you went back and you started to implement certain features with AI.
- [71:21]
B
Yeah. So thing is, I can work. I've been working on source graph Cody coding on Cody for quite some time. And then the agents came in, out and I was like, you know what, I'm going to try it on a. Because all we had was a brand new code base. I want to try it on a crummy old Legacy code base. 30 years old is pretty crummy and pretty legacy. It really is, man. It was bad. So that's what I've been doing is I've been doing different things. I've been doing cleanups, I've been doing adding tests, I've been doing migrations. All the things that a larger company would need to do. Yeah. Because I have lots of experience with those at Amazon and Google and so on. And so you can scale it up. You can say, okay, I'm doing it for Wyvern. And this is what the experience you're going to get as a developer in a year and a half, two years working on a giant enterprise code base. Right. And the answer is it's going to be real different. It's going to be a lot of fun. It's going to be really hard still. And it's just a completely different role. You don't write code anymore. You build software.
- [72:11]
A
So on this game, but just going back, you're describing the AI, what to do. It turns out the code, you look at it, you test it, and then you. It put, push it, push it out.
- [72:24]
B
It is a very complicated process that's way too long to talk about here. It is built inherently on a foundation of distrust. You cannot trust anything. The LLM gives you anything. And that means multiple safeguards and guardrails and sentries and security and practices. And you have to train yourself to say the right things and do the right things and look for the right things. And it is not easy. And it has reinforced my belief that people who are really good developers are going to thrive in this new world because it takes all of your skill to keep these things on the rails.
- [72:56]
A
Do I hear it correctly that what we're kind of saying? Because at first I might have misunderstood you. First it's like, all right, companies, you should invest in it, you should do it, because otherwise you'll be left behind. But it might be a little bit like what we've seen with let's say early Google. Google was building out all their platforms and they're not really making a secret. Or let's say Amazon's a better example. They were like, like building all these internal APIs that talk to each other, which no one did. It seemed like a lot of work to do. And it didn't seem why you shouldn't just stick with what you have. But, you know, 20 years later, Amazon actually like built AWS. They have an organization that actually everyone talks with APIs. And some companies are still have not figured out. You know, like we can look at, for example, Google. So what we might be saying is like, look, this future is coming, but it's going to be a lot of work. Like start now because you will need to figure out so many things and it's not just going to be.
- [73:46]
B
That's right. The call to action is absolutely not. Give agents to all of your developers. That would be an apocalyptic event for your company in more ways than one. But what you should do is you should start getting some of your developers together to understand what is going to have to change in your company. And I don't just mean the technology and the IT stuff, employments and monitoring, I mean like the business processes. What's going to have to change if suddenly co generation is no longer the bottom bottleneck? Because it's historically always been the bottleneck and so we've allowed everything else to just kind of like coast.
- [74:21]
A
And this is why I really wanted to talk about your game because I think this was really helpful for me because what I'm trying to understand is what does it look like when we use these? And I'm glad that you said that it wasn't that, I don't know, all your bugs are now suddenly fixed magically.
- [74:34]
B
No, it's going to be years and years of work, but I'll be going 100 times faster. So it's fun.
- [74:39]
A
Yeah. But by the time you finish. Yeah, yeah. And in the book, like a thing that I liked again, I like you made a prediction about how jobs will be impacted. And I kind of thought, you know, we talked, we exchanged emails earlier and I kind of thought you're going to be. You would be saying there will be fewer jobs. In the book you actually say the opposite. You said that you think there will actually be a lot more developer jobs. Why do you see this? And, but what will change? They're not going to be the same things as today. Right, Right.
- [75:07]
B
It's so hard for people to get their heads around because what's happening is we're, we're, you know, commoditizing the creation of software just like digital cameras, commoditized photography. Right. Everybody can take nice professional pictures now. And that was inconceivable back in the 80s. Inconceivable.
- [75:23]
A
Yeah. I mean how, how much would have these things cost? Like you know, just 20 years ago.
- [75:27]
B
And by the way, everybody crapped all over digital photography for years.
- [75:30]
A
Oh yeah.
- [75:31]
B
And they were like, it'll never, it'll. There were of lot, a lot of, There was a lot of idle nevers being thrown around. Well.
- [75:35]
A
And Kodak went bankrupt on not believing it. They actually buried their own digital camera.
- [75:39]
B
Yeah, yeah, yeah, yeah, yeah. So like we're in that situation again. Everybody's Like AI will never, they are wrong. AI will ever. It will get to where all the places that you think you're, you don't think that it's going right now. And what's going to happen is your mom will be able to create software, okay? Your boss will be able to create software. Somebody at McDonald's will be able to create software. Like, literally, we're going to find all the Ramanujans, you know, the undiscovered real geniuses in the world, right? Because my friend Brendan Hopper, he's the head of technology, CTO for technology at Commonwealth bank of Australia, and he's got some amazing hypotheses about how AI is going to bring out a meritocracy, okay? Because AI is a spotlight. It shines on all the work that people are doing. And you can't hide shoddy work anymore. The AI will detect it if you're high, if you're, if you're hoarding knowledge. Like you're an engineer who hoards knowledge to keep your job security. That's gone. Now. The AI knows everything you know.
- [76:35]
A
Now, see, to be honest with, there are always these stories about doing so I never really believed happens.
- [76:41]
B
But it's a rare edge case. But there's other common edge cases where people manipulate the system to try to, like, benefit, you know, whatever they want instead of what's best for the system. The AI is eventually going to highlight that. And so all the people with merit, meaning the people who are good at using AI to get important things done, I guess, guess, are going to bubble to the top and there are going to be an astounding number of jobs because creating software is so much more empowering than creating pictures. If anybody can create a video, so what? But if everybody can create software, that's mind blowing. So, you know, what I think is going to happen is I think big companies are going to shed a lot of jobs. I think a lot of people are not going to work for big companies. There are going to be a bazillion startups.
- [77:16]
A
See, one thing that I'm not 100% on this is big companies are highly profitable, profitable. And I could see them shedding certain jobs but then replacing it. But they will want to keep their edge. They will, of course, want to try to increase profitability, but they're happy keeping it at level and having enough reserve to fight off the startups, right?
- [77:39]
B
Absolutely. I mean, that balance will always be there, that tension. But I feel like right now the calculus is not looking in favor of big companies bulking up any further. Like I don't see big companies getting bigger.
- [77:52]
A
Well in fact I just. We were doing a Google deep dive. I saw that Google peaked its headcount in 2022. It's been kind of like going slowly a little bit down. It was like 188,000 or something. So actually like it. And this is Google we're talking about which is profitability and revenue keeps going up.
- [78:07]
B
So yeah, right now companies are discovering the easy solution is you can do the same that you've been doing for cheaper by you know, losing some headcount and doing some stuff with AI. Right. And I think the more ambitious ones are going to do. They're going to be more ambitious.
- [78:20]
A
So you've done your game. I want to ask you about a metaphor that I've been thinking about and I asked you to poke some holes in it. The ones you see game development in game development. If you think back of what the biggest barrier of entry used to be to build a nice cool game, it was initially building the 3D engine. This is why Doom was massive. Wolfenstein, they built the engine and then they kind of built the game around it it but you know like that was like 90s.
- [78:50]
B
The guy's my next door neighbor by the way. Michael Abrash, the one that made Doom fast really and Quake a while and.
- [78:56]
A
Over time, you know, now we actually have software, Unity and Unreal Engine which take care of the engine. So you can now focus on the games and what this has resulted in. I've now interviewed a few people. Very small teams can also make really, really cool games if you actually want to build a game. I actually did a Unity tutorial. I could build a game. I mean I would need put in the work but it's no longer like it can look professional and all these things. And if I look at how the gaming industry has evolved, I'm following a little bit of the news. AAA studios are mostly struggling. Not all of them. GTA 6 is still doing great and some of them and the EA Sports, but some traditionally massive studios are struggling because it doesn't work that we throw a bunch of money and we get a bestseller. There's a lot more indie games, way more than ever. They're having trouble consistently. So I'm wondering if we might see something similar because again the game engine was central to all of this and now everything that is not the game engine is really important. Marketing story, all those things in software engineering, coding, being able to code was the bottleneck and now that will to some extent be removed. But software engineering is still. Everything around it still remains that for sure.
- [80:10]
B
That is absolutely true.
- [80:12]
A
True.
- [80:12]
B
So, yeah, we're going to see a lot more software get created, period. Just like a lot more small software. And we're going to see more indie games and we're going to see more stuff bubble up that's high quality. Somebody's going to find a way to organize it all, like the App Store, organized apps.
- [80:27]
A
Maybe we'll see a new starter for this, man.
- [80:29]
B
Dude, I'm telling you, man, almost every time I talk to anybody about this, we come up with a couple of new billion dollar ideas, right? I mean, it's like that. This is another reason I think there's going to be so many jobs is that this will create legitimate, real, actual GDP productivity. Nothing fake about it, nothing artificial. It will create real value. It's going to be an explosion of value, Right. It's going to take a couple of tipping points for the AI to reach this sort of mass market ability for people to be able to use it to create reliable software. But we're no more than two years away from that, man. And it's going to be like this incredible proliferation of just cool shit for you to try. There's going to be too much, actually. You're going to have to have AI to help you find your way through it.
- [81:10]
A
So in those two years, whether a listener is a less experienced engineer, especially if they're an experienced engineer, what would your advice be to prepare best to make the most of either being an AI engineer, working with these tools, figuring them out, what is the tactic? What is the advice that you give? You know, the engineers working, let's say a source graph. You know, where you're at, who you're around you.
- [81:35]
B
Yeah. So you know who. What's the guy that wrote the movie the Room? Tommy Wiseau, I think that's his name. Somebody asked him on Twitter, they were like, hey man, I want to start writing a screenplay. What should I do? And he said, start, right?
- [81:48]
A
Yeah.
- [81:48]
B
I mean, like for starters, if you're saying, oh, I don't know about AI, I'm not ready, blah, blah, blah, shut up. Okay, You're. That's done. You're done whining. Okay? Go learn it right now. I had the privilege of speaking with Dario amadei privately for 30 minutes about three weeks ago. Four weeks ago, he invited me to come chat with him. And I got to hear his sort of unvarnished view of the very, very near future from somebody who could arguably be considered one of the best informed people in the world.
- [82:22]
A
Yeah.
- [82:22]
B
And Dario, you know, his vision of the future is a little bit more bleak than he lets on publicly. Okay. And he and Jason Clinton, his ciso, are both saying statements that are quite dire, like there will be badged AI employees by the middle of 2026. Competing with you. Right. Basically, is the implication there and other. Other implications like that, the Moore's Law of AI, how it gets. It gets four times smarter every 18 months. So if you do the math, three years from now, if they're IQ10 today, they'll be IQ160, if you want to choose some sort of rough measure of what 16 times smarter means. And it'll be too much for people. Dario told me, he said, look, he said, society is like an immovable force, an immovable object. And tech and AI are an unstoppable force. They just won't stop. And they're going to collide and it's going to be ugly because it's going to push society harder than society wants to be pushed, harder than society is willing to be pushed. And we're already seeing signs of it. We're seeing people revolting against AI putting up the. I'm sick of it. Right? He posted I'm sick of it. He never mentioned AI in the post. It was really brilliant. I love the post, by the way, the guy that wrote the ISO, because he's speaking for a generation of people who are tired of hearing about this shit, but unfortunately, you are never going to stop hearing about it. That is the way things are going to be done and in the very, very, very short order. And so my advice to you is get off your ass and learn it now. Now, now. Okay. Start vibe coding. Figure it out. There's a lot to learn. There's a lot of weird instincts you're going to have to, like, learn. A lot of stuff's not going to work the way you expect it to, okay? But you start now, and you'll be ready. Because Dario calls 2026 the end game. And he says it without a hint of drama. He says it casually. Oh, yeah, 2026 is the end game. You understand? That's how big this is going to be. And the first ones to fall, the first jobs are software engineers, right? So you need to be on top of it to take advantage of. Of the new jobs that arise, which are software engineer v2, which use AI and get amazing things done. You have to be one of them or you're going to get kicked out of Knowledge work altogether.
- [84:19]
A
Yeah, well this is going to be part of like I think it's clear that it's going to be, it reminds me a bit of the cloud where you know these days like yeah, every company uses a cloud, either private or public. And about 15 years ago it was like AWS and I talked with banks. Banks were like we will never use it, we will never onboard. We'll always have our data centers. And you know, there was a time where I think it was very valuable to get AWS certifications and you get hired and get a salary bump. So I feel there are levels where like I think it's clear to me that AI as infrastructure will be in every single tech company and of course it will be in every single non tech company and government and all it will happen. I don't see this time frame so I think we might disagree a little bit on how that is, but it will happen. And I think you're advantageous. Device is absolutely solid. Like get started now. In fact, what I'm seeing now and again, this was just this conversation with Jambi. Jamvi said that she saw chatgpt come out. She was at Coda Coda spun up in a few months an AI team and she said I'd like to be on that team. And they said thank you but no thank you, you don't have the experience. And then she thought for a while like I'm too late. There's people been doing it for five years since Transformers. What can I do do? And then she just went to hackathons. She just hacked on the side five months later. She was one of the best at the company and she got on the team early on and I, I think there's this thing of, of like I would suggest the listeners maybe you know, like put away the, the doomsday thing. But the point is this thing is happening and as you said now is the best time. Like, like learn it and also do get motivation. Like I, I, I do think the industry will change a lot. Like we'll probably look back at this time out, something big happened and we're in the middle of it.
- [85:59]
B
We are in the middle of it. And you know what the funny thing is? I mean the grass really is greener on the other side here. Like it is so fun, right? It's so, it's so fun. I'm having so much fun not coding but fixing my bugs and adding features. I love it.
- [86:14]
A
But I also feel sometimes you are coding, you know what you expect and you correct just so there's a lot of meta coding happening.
- [86:21]
B
Oh, yeah. I read a hundred thousand lines of code a day. Yeah, it ain't easy, right? I mean, it's exhausting because if you're not reading it, then stuff's slipping by you. You'll eventually figure it out that, you know, you want to try to catch things early. Yeah. But man, it's like, it's a. It's a different ball game and I love it. I'm having so much fun. And Gene Kim, my amazing co author, who's, you know, he's an author and researcher who I think probably knows everybody in the entire world who's everybody and. And he and I are both just unbelievably excited about vibe coding because despite the doom and gloom sound of what's happening, the only reason it's doom and gloom is people don't like change. They don't want to. They don't want to change the way they're working.
- [86:59]
A
I think so. And I've been guilty of this earlier, like when I, when I saw this big change come, at first I was like, oh, this is not great. And you know, when people are saying it'll eliminate jobs, I didn't like the message. It just felt like very threatening. I think as software engineers, we're kind of used to us automating a bunch of jobs like customer support and you know, like, oh, here's the cost savings of like, we need fewer customer. And we never fired customer agents. We just didn't hire as much. And I think this is the first time in history where our work is kind of threatening us. But what I came to realize is talking to you, talking to Ken back, seeing my experiences, if you are a good software engineer and you are open to learning and using these things and adding into your toolbox, you will be a better and more in demand 1. That's what I'm seeing from people. People who started to use this, they're now being hired as AI engineers. AI engineer is actually a software engineer who is able to use but understand the non deterministic part. They're going deeper into ML. So I think in some ways it's ironic, we might have had some stagnation for like 10 or 15 years where you could do the same thing and be more successful and staff engineers. Just. It was more about managing people. And I think for the first time in 15 years, we're shaken up. And to be a great software engineer, you need to learn, you need to let your ego go, which I think that's something you've always done really well.
- [88:19]
B
Yeah. I mean, why get your identity tied up in something that's actually kind of fragile, as it turns out. Look, the way I think about it, man, software is always so big. Remember when they're building the second Death Star, I think it was in Empire Strikes Back and it was half done. How big was that freaking thing? Right. That's a typical enterprise software project right there. It's a good visualization of it. Right. So what if you have these robots that are 20 times as productive as a human? You're still going to take freaking years and years and years to build it.
- [88:47]
A
And there will be architects overseeing it.
- [88:50]
B
Right. You're going to be very. Yeah, exactly. You're going to be very grateful that you have the help of these robots that are 20 times faster than human data coding or 100 times faster. You're still building Death Stars and it still takes years. So there's still jobs. They're just different. Traumatic events can increase your neuroplasticity. And you said we've been stagnating. Many of us had been stagnating. The reason I retired is I felt like I was stagnating.
- [89:12]
A
Yeah. I was thinking, I'll be honest. Now my publication, the Pragmatic Engineer, covers the trends happening. And I was just talking with my brother, he's also in tech, he's the founder of Crap Docs. And I was talking how, looking back, if AI did not happen, what would we be talking about? Is it how to more efficiently move monoliths? Microservices We've been talking about, about for a few years, how to measure developer productivity even a little bit better. How to scale teams better so that. How can you manage 10 teams?
- [89:42]
B
And can we switch to memory safe languages like rest?
- [89:45]
A
Yes. And I'm like, it was getting a little bit boring. So, you know, like, I think this is a good, good takeaway.
- [89:52]
B
Yeah, we were, we were, we were incremental improvement mode.
- [89:54]
A
Yes. And this is a step change. Yeah, absolute step change. So close off with some rapid questions, if you're okay with that.
- [90:02]
B
Sure.
- [90:03]
A
With all this AI stuff here, what is your favorite programming language? Or do you even have one?
- [90:08]
B
Wow. My favorite programming language. Oh my gosh. I don't even care anymore. I'm so. What used to be my favorite programming before all this AI stuff made it like kind of unnecessary? I really like typescript. Maybe I shouldn't, but there's something about it. I mean, it's just so flexible and expressive and I think probably I have to give it to Typescript.
- [90:30]
A
And what is an AI tool related to coding that you like and an AI tool that has nothing to do with coding?
- [90:36]
B
Okay, an AI tool for coding. You should try Source Graph amp. It just came out yesterday. I mean, come on, man. That's what I've been using. I actually turn all the permissions off and just let it run. But don't do that. But it's so, so good. Yes.
- [90:52]
A
And then until there's an RM dash.
- [90:56]
B
Rf, I've gotten pretty good at sandboxing, but I think I'm probably going to switch Docker containers anyway. As for an AI tool that's not related to coding. Yeah, boy, I tried Operator. I really want something like Operator that works, if that makes any sense. So hopefully some very soon upcoming version of it. But it couldn't do something simple like edit my Google Doc for me. Like it would look at it for 20, literally 20 minutes and then like, like just delete a paragraph.
- [91:23]
A
I mean, I think that's a good example of like we will have software explosion there. Someone will have to build it. Who's going to build it? Yeah, we know who's going to build it. And what's the book recommendation that you had outside of your read?
- [91:37]
B
Sapiens, man, such an awesome book.
- [91:39]
A
Well, Steve, this is great. I'm glad. I feel we went on a roller coaster. We went like high, then low, and then we ended up high again.
- [91:47]
B
Yeah, well, you know, change can be scary, right? But this is a very positive change in my opinion.
- [91:52]
A
And I think it's good to just like, I like that we. Let's just, you know, name what it is. It is change. And it is a big change. And I think what makes it scary for a lot of people, including, you know, my generation, I have not seen this change. Like people who have been around the dot com bust might have seen it. When I talked to Grady Booch, he actually told me like, oh, actually Ken Beck was saying we've seen this change. Like when we moved to, to microprocessors, for example, apparently it was a huge thing and everyone's world shook because they were so much faster now they were going to change everything. And then Kevin Beck said, yeah, everything changed. And then in some ways nothing changed.
- [92:32]
B
That's a good point. Everybody suddenly had a computer one day. I was there for that. And before that nobody had a computer and it was inconceivable. So everybody being able to create software is a really interesting step in that direction.
- [92:42]
A
Well, because back then, as I understand as a programmer. You had to go to work to these companies which had these massive computers and whatever. So it was only very privileged and then suddenly anyone could do it.
- [92:54]
B
Yeah, that's right.
- [92:54]
A
Or who had the money, who had, like, you know, rich parents or whatever savings.
- [92:59]
B
PCs were the beginning of the big boom. So we are at the beginning of a big boom. There's a lot of money to be.
- [93:04]
A
Made and PCs turned out to be pretty great for us software engineers.
- [93:08]
B
Yeah.
- [93:08]
A
All right, Steve, this is a fate.
- [93:10]
B
Okay. This is awesome. Awesome, man. Thanks.
- [93:12]
A
I hope you enjoyed this interesting and entertaining conversation with Steve. Steve Iran is a prolific writer and you can read more of his rants linked in the show Notes below. For more in depth reading about developer tools, the engineering culture at sourcegraph or the impact of AI on software engineering, check out the Pragmatic Engine Deep Dives, also linked below. If you've enjoyed this podcast, please do subscribe on your favorite podcast platform and on YouTube. This helps more people discover the podcast and a special thanks if you leave a rating. Thanks and see you in the next one.