2026: The Year The IDE Died — Steve Yegge & Gene Kim, Authors, Vibe Coding
By AI Engineer
Summary
## Key takeaways - **Cloud Code Fails Developers**: Cloud code ain't it. Developers aren't adopting it because they're too hard with cognitive overhead; they lie, cheat, and steal. [01:07], [01:15] - **AI Tools Like Dangerous Saws**: Claude code is very much like a drill or a saw, an electric one; untrained engineers can cut their foot off, but skilled ones do precision work. [01:45], [01:53] - **2026: Grinding Machines Write Code**: All code within a year, year and a half will be written by giant grinding machines overseen by engineers who no longer actually look at the code directly anymore. [02:38], [02:49] - **OpenAI 10x Productivity Gap**: At OpenAI some engineers use codecs and others don't; the difference in productivity is so staggering they're having alarms at performance review time and may fire 50% of engineers. [03:07], [03:28] - **Senior Engineers Resist AI**: Who is refusing it? It's the senior and staff engineers, just like Swiss craftsmen rejected cheap quartz watches that killed their industry. [03:36], [04:04] - **Abandon IDEs by 2026**: Give up your IDE. If you're using an IDE starting on January 1st, you're a bad engineer. [06:38], [06:49]
Topics Covered
- Full Video
Full Transcript
[music] Hey everybody. Um, really happy to be
Hey everybody. Um, really happy to be here. I'm going to be talking the first
here. I'm going to be talking the first half. Co-author here, Jean Kim, is going
half. Co-author here, Jean Kim, is going to talk second half. All right. Looking
forward to it. Cheers. All right. Today,
I'm gonna Well, we're going to talk real fast. This time's going to go down fast.
fast. This time's going to go down fast.
Uh, I'm going to talk to you about what tools look like next year. Last year, I was talking to you all about chat and everybody ignored me and now everybody's using chat this year and it's like we're
gonna we're going to fix that right now.
All right. So, here's what it's looked like. I'm going to tell you right now,
like. I'm going to tell you right now, everyone's in love with Cloud Code.
There's probably 40 competitors out there. Cloud code ain't it.
there. Cloud code ain't it.
Completions wasn't it. I love cloud code. I use it 14 hours a day. I mean,
code. I use it 14 hours a day. I mean,
come on. But it ain't it. Developers
aren't adopting it. I'm going to talk about why in this talk. I'm going to talk about what you can do about it and what what to look forward to. But the
reason is they're too hard. Okay. Uh
cognitive overhead. Uh they lie, cheat, and steal. Gene and I talk a lot about
and steal. Gene and I talk a lot about this in our book, all the different ways that they can lie, cheat, and steal. And
>> [clears throat] >> uh most devs just don't like this.
I have come to understand that claude code is very much like a drill or a saw, an electric one, right? How much damage can you do as an untrained person with a
drill, right? Or a saw. Yeah. How much
drill, right? Or a saw. Yeah. How much
damage can you do as an untrained engineer with claw code? It's real
similar. Yeah. You can cut your foot off, but you can also be really, really skilled with it and do really precision work, right? like a craftsman. The
work, right? like a craftsman. The
problem is software is infinitely large.
Our ambition is infinitely large. And so
the analogy that I want to share with you is next year will be the year from moving from saws and drills to CNC machines. A CNC machine, you strap a
machines. A CNC machine, you strap a drill on and you give it coordinates and it moves it around and very precise, right? We've been doing this for
right? We've been doing this for centuries and we're not going to stop this year.
One thing I hear people say is, "Well, the models are plateaued." This is real common. Your engineers are probably
common. Your engineers are probably saying this, okay, even if they plateaued, we have still discovered steam and electricity, and it's going to take us a little time to harness it. But
it's strictly an engineering problem at this point. All code within a year, year
this point. All code within a year, year and a half will be written by giant grinding machines overseen by engineers who no longer actually look at the code
directly anymore.
Weird new world. That is where we are going. Oh my gosh. Yep. This this slide.
going. Oh my gosh. Yep. This this slide.
So Gan and I talked to Andrew Glover who I don't know is he here from OpenAI and he said that they have this incredible dichotomy unfolding at OpenAI where you know some percentage of their engineers
are using codecs and then some other percentage a larger percentage are not using codecs and the difference in productivity is so staggering that they're having now alarms going off at performance review time because how do
you compare these these two engineers who are the same level, same title, same everything and one of them is 10 times as productive as the other one by any measure.
And the answer is they're freaking out and they may have to fire 50% of their engineers. And this is unfolding at
engineers. And this is unfolding at other companies, too.
Who is refusing it? It's the senior and staff engineers. How many minutes are we
staff engineers. How many minutes are we at?
>> Eight [clears throat] minutes.
>> We're perfect. This is just like what happened to the Swiss mechanical watch industry over a couple of Well, it was built up for a couple of centuries and then courts killed it, you know, within
a couple of years. And what happened was the craftsmen were doing the same thing our staff engineers are doing today. No
cheap.
That's word for word, right? That's what
they say.
All right. I didn't know where to put this slide. This is this is Claude's
this slide. This is this is Claude's view of what next year looks like. And I
I was just like, what do you think it's going to look like? And it actually does kind of look like this. Most of the words will be spelled correctly in in next year. But this is a lot prettier
next year. But this is a lot prettier than cloud code.
Yeah, this is what it has to look like.
Some form of a UI, not an IDE. This is
the new IDE. Okay. And people are building it. In fact, I think the
building it. In fact, I think the company that's the furthest along in this is Replet, who just talked to you.
I think it's amazing what they're doing.
It's absolutely bravo, right? We should
not be all chasing tail lights and building command line interfaces anymore. All right. and and more
anymore. All right. and and more importantly, Cloud Code and all of its, you know, competitors, they're all doing it wrong because they're building the world's biggest ant. Okay, this is my my
buddy Brendan Hopper at Commonwealth Bank of Australia, right? He's like,
"Nature builds ant swarms and Claude Code built this huge muscular ant that's just going to bite you in half and take all your resources, right? I mean, it's a serious problem, right? If I say please analyze this codebase, I, you know, go to the expensive model." If I
say, "Is my git ignore file still there?" I've also gone to the expensive
there?" I've also gone to the expensive model, right? Everything that you say
model, right? Everything that you say goes to the expensive model. So, what's
going to happen? Whoa. What happened? Oh
gosh, my slides are all messed up now.
>> Can you guys see them?
>> No.
>> Oh, this always happens to me, man.
There something going on. All right. So,
I thought of a really cool analogy called the diver the diver metaphor, which is your context window is like an oxygen tank. Okay. This is why these
oxygen tank. Okay. This is why these things are fundamentally wrong. Cuz
you're sending a diver down into your code base underwater to swim around and take care of stuff for you. One diver
and we're like, we're going to give him a bigger tank. 1 million tokens. He's
still going to run out of oxygen. Like
you don't, right? You should send a product manager diver down first and then a coding diver, right? And then
a review diver and a test diver and a get merge diver, etc. Right? Nobody's
doing this. Everyone's building a bigger diver. I don't know my slides are all
diver. I don't know my slides are all messed up. My my my talk is almost done.
messed up. My my my talk is almost done.
But um what we do is as engineers, task decomposition, successive refinement, components, black boxes. This is how it's going to be
boxes. This is how it's going to be built in the future. And it's going to be built with lots and lots of agents, not just one agent.
All right. Until then, I think we're out of time, but so until then, learn cloud code. Give up your IDE. Swix told me he
code. Give up your IDE. Swix told me he wants some hot takes, so I'll give you one. If you're using an IDE starting on,
one. If you're using an IDE starting on, I'll give you till January 1st.
You're a bad engineer.
There's your hot take. All right, folks.
[applause] All right, cheers. Well, that that was actually my talk. Um, [clears throat] uh, learn coding agents and Oh, yeah.
Then there's this guy. Speaking [snorts]
of bad engineers, so this is this is Jordan Hubard. uh who uh who's at Nvidia
Jordan Hubard. uh who uh who's at Nvidia and he tweeted LinkedIn a really nice post on how to get the most out of agents and this guy responded with this right this is everyone in your or this
is 60% of your org right here this guy's not an outlier okay the backlash is very real against this yeah and this is going to be a problem I'm not going to I'm not going to share with you I don't have time to share how to fix it but it's
something you should be aware of and anyway I'm going to turn it over to my co-author Jean we had a lot to talk about he's got a lot to go so let's turn it over to Jean >> yeah Thank you, Steve.
[applause] >> Yeah, by the way, um I have let me start off by introducing myself and then I'm going to share a little bit about like what it's been working like uh what's been like working with Steve on the VIP coding book. Uh and so just a little bit
coding book. Uh and so just a little bit about myself. I've had the privilege of
about myself. I've had the privilege of studying high performing technology organizations for 26 years. And that was a journey that started when I was a technical founder uh of a company called Tripwire. I was there for 13 years. But
Tripwire. I was there for 13 years. But
our mission was really to understand these amazing high performing technology organizations. They had the best project
organizations. They had the best project due date, performance and development, the best operational reliability and stability and also the best posture of compliance uh security and compliance.
So we want to understand how did those amazing organizations make their good to great transformation. So we got
great transformation. So we got understand how did how do other organizations replicate those amazing outcomes and so you can imagine in that 26 year journey there are many surprises. Among the biggest surprise
surprises. Among the biggest surprise was how it took me into the middle of the DevOps movement which is so uh amazing because it reshaped technology organizations. you know, it changed how
organizations. you know, it changed how test and operations worked, information security. Um, and I thought that would
security. Um, and I thought that would be the most exciting adventure I'd be on in my career until I met Steve Yaggi in person. And so, I've admired his work
person. And so, I've admired his work for over 11 years. And so, some of you may have read this memo of Jeff Bezos's most audacious memo of how in early 2000s they transformed from a gigantic
monolith that coupled 3,500 engineers together, so none of them had independent action. And uh he talked
independent action. And uh he talked about how all teams must henceforth communicate and coordinate only through APIs. No back doors allowed. Right? Uh
APIs. No back doors allowed. Right? Uh
anyone who doesn't do this will be fired. Thank you and have a nice day.
fired. Thank you and have a nice day.
And the amazing person who chronicled says number seven is obviously a joke because Bezos doesn't care whether you have a good day or not. And this is actually enforced by Amazon CIO then Rick Del. And so it turns out this memo
Rick Del. And so it turns out this memo that I've been quoting for 11 years uh was written by Steve Yaggi uh which was meant to be a private uh memo on Google+ which was made public which landed him on the front page of Wall Street
Journal. Um and so I finally met him in
Journal. Um and so I finally met him in uh June and it turns out that we had many things in common uh but one of them was this uh love of AI and this sense that AI was going to shape coding from
underneath us. And so one of our beliefs
underneath us. And so one of our beliefs is that uh the AI will reshape technology organizations you know maybe even 100 times larger than what agile cloud CI/CD and mobile did you know 10
years ago um and that these technology breakthroughs not just reshape organizations but they reshape the entire economy the entire economy rearranges itself to take advantages of these you know wild new better ways of
uh uh producing things and and uh so over the last year and a half we've had a chance to look at these case studies I think give us a glimpse of what these uh what the shape of technology organizations look And so I'm going to share with that what we've learned. But
here's maybe a hint. So some of you may know the work of Aen Cochraftoft. He was
a cloud architect at Netflix, right? He
was what who drove uh the uh entire Netflix infrastructure from a data center uh back in 2009 to running entirely in the AWS cloud. And so he wrote uh some months ago in 2011 some
people got very upset in uh infrastructure and operations because they called it noopops, right? And
everyone laughed back then, but he said, "Oh, don't you know uh it's happening again. And this time it might be called
again. And this time it might be called no dev, right? Not so funny now, right?
So it's it's interesting, right? Because
we heard this amazing presentation from Zapier about like how support ships and turns out designers are shipping, UX is shipping, right? Anyone who's been
shipping, right? Anyone who's been frustrated by developers uh who, you know, say get in line and you have to wait quarters or years or maybe never, right, are now suddenly in a position where you can actually vibe code your own features into production, right? And
that reshapes technology organizations and reshapes, you know, potentially the entire economy. And so uh uh Steve and I
entire economy. And so uh uh Steve and I we've had the privilege of watching what happens you know when we change uh you know the way we uh deploy right it wasn't so long ago and 10 years ago uh I wrote a book called the Phoenix project
where it was all about the catastrophic deployment would you believe uh that it was you know 10 years ago 15 years ago most organizations shipped once a year right and so I got to work on a project called the state of DevOps research it
was a cross population study that spanned 36,000 respondents uh from 2013 to 2019 and what we found uh this was Dr. Nicole Forsrin and Jez Humble. Um,
and what we found was that these high performers ship multiple times a day, right? They can ship in one hour or
right? They can ship in one hour or less. And you know, back in 2009, people
less. And you know, back in 2009, people thought, "Oh my gosh, multiple deployments per day, right? That's
reckless and irresponsible, maybe even immoral, right? What sort of maniac
immoral, right? What sort of maniac would deploy multiple times a day, right? And yet, it's very common place
right? And yet, it's very common place these days. In fact, if you want to have
these days. In fact, if you want to have great reliability profiles, you want to have short meantime to repair, you have to do smaller deployments more frequently." And I think we're now
frequently." And I think we're now seeing these kind of case studies that show that this better way of coding, right, where you don't type in code by hand might be, you know, just a vastly better way uh to create value. And so
our definition of vibe coding that we put into the uh vibe coding book was that it's basically anything where you don't type in code by hand. And so for some of those of you who don't understand that, that's like sort of a uh typing an ID hunched over, right? And
you're actually moving your fingers, right? That's sort of like how some
right? That's sort of like how some people go into a dark room to develop photographs, right? Believe it or not,
photographs, right? Believe it or not, some people still do that. Um and and what I that's a great definition that we uh loved until uh Dar Ammedday u uh CEO
and co-founder of um Anthropic he gave us an even better definition right the vibe coding is really the iterative conversation uh that results in AI writing your code and he said it's on one hand a beautiful term because it
evokes this different way of coding but he said it's also somewhat misleading because it sounds jokey right uh but he said you know adanthropic there's no other game in town right I just thought that was just a beautiful way to evoke
you know how important uh vibe coding is. Uh this is Dr. Eric Meyer. Um you
is. Uh this is Dr. Eric Meyer. Um you
he's probably considered one of the greatest programming language designers of all time. Uh he was part of Visual Basic, CP, Link, Haskell. He created the hack programming language uh that migrated millions of lines of code at
Meta, you know, within a year uh bringing static type checking to a bunch of PHP programmers and he said we are probably going to be the last generation of developers uh to write code by hand.
So let's have fun doing it. Um, so one of the things and uh when uh Steve and I started working on the book last November was uh watching him spend hundreds of dollars a day on coding
agents uh and just seemed so strange right um you know and so he's maxing out not just you know the uh the monthly subscriptions right but he's actually you know going way above and beyond that
and yet uh you know things that we're hearing now is that as an engineer part of my job is that I need to be spending as much on tokens per day as my salary right so you know that think about like $500 to $1,000 a day, right? Because
this is the mechanical advantage, the cognitive advantage that these tools are giving us, right? And as an engineer, right, I'm going to challenge myself to get that kind of value to deliver value to people who matter. Um, and so in the book, we talk about, you know, why
people would do this, right? And the,
uh, acronym we came up with FAFO, right?
Uh, the most obvious one is F for faster, right? Yeah, that's obviously
faster, right? Yeah, that's obviously true, but I think it's the most superficial and um part of why we do this because uh the second one is it lets us do more ambitious things, right?
Uh the impossible becomes possible. Uh
so that's one end of the spectrum. On
the other end of the spectrum, you know, the uh the tedious and small tasks become free. One of the things I uh the
become free. One of the things I uh the uh interview of the cloud code team that I just loved was uh I think it was Katherine, she was said um uh one of the things we've noticed is that you know
when customer issues come up uh instead of putting them on a jur backlog and you know arguing about it in the grooming sessions and so forth right we just fix it on the spot right and ship to production or whatever um you know
within 30 minutes right and so yes it gets recorded but you know that whole sort of coordination cost you know just disappears right so again the impossible becomes possible right and uh the
annoying things just become free. The
second A is uh um you know the ability to do things alone or more autonomously, right? And so um you know there's really
right? And so um you know there's really two coordination costs are being alleviated here. One is you know if you
alleviated here. One is you know if you ever have to wait for a developer or a team of developers, you know, to do what you need to do, right? You have to communicate and coordinate and synchronize and prioritize and cajul and
escalate, you know, do all sorts of things to get them to care about the problem just as much as you do, right?
And you know now you know with these amazing new miraculous technologies you can do them by yourself right so that's one coordination uh tax the other one is like even if you get someone to uh care
about a problem as much as you uh they can't read your mind right and what we're finding is that these LLMs are just amazing intermediation vehicles right um you know just through an LLM you can coordinate with other functional
specialties right through a markdown file right that's not the end right but it's just this amazing way uh to have these high bandwidth coordination so that you can essentially read each other's minds, you know, because shared
outcomes require shared goals and shared understanding. The second F is fun,
understanding. The second F is fun, right? Is that Steve says vibe coding is
right? Is that Steve says vibe coding is addictive. This is so true. I mean, I
addictive. This is so true. I mean, I cannot I think what I love about the book is that it's a story about two guys who both thought their best days of coding were behind them, right? And
found that, you know, it's entirely the opposite. Um, and I've had so much fun
opposite. Um, and I've had so much fun and uh, you know, I'm having to force myself to go to sleep at night because otherwise I'd be up till 2 or 3 in the morning every night. uh and you know so it's not all great but it certainly
beats being boring or tedious or you know horrible and then optionality you know one of the things that uh I love about Switch is that he has a shared love of creating option value and he told us last night that option value is
also important for poker players right because you never want to paint yourself in a corner so option value is um one of the biggest creators of economic value right modularity the reason why it's so
powerful is because it creates option value uh and so just the fact that you can have so many more swings at bat you can do so many more parallel experiments right this is what v coding allows so this is gives us confidence that you know this is not just uh this is a very
powerful tool um uh here's a quote from Andy Glover that uh Steve Yaggi said is that you know as um for people who have this aha moment and position uh you know I think
the instinct is how do we elevate everyone's productivity to be as productive as you are now being um you know that since you've had your aha moment so uh let me share with you maybe
some of our top kind of uh exciting case studies that kind of give us a hint of the future. So uh I brought him to this
the future. So uh I brought him to this conference called the enterprise technology leadership summit for uh 11 years now and Swix we had uh the honor of having Swix there talking about the rise of the AI engineer just this
amazing prognostication. Uh this year we
amazing prognostication. Uh this year we had a series of amazing uh case studies.
One was uh Bruno Passos. spoke this year uh last year at this conference and he presented on uh their in their evolving experiment to elevate developer productivity across 3,000 developers. Um
and this is at Booking.com, the world's largest travel agency and uh they're finding that they're getting double- digit increase in productivity, right?
Uh mergers are going in quicker, peer review times are uh smaller and and so forth, right? And so that's just we feel
forth, right? And so that's just we feel like that's a incomplete view of uh what people are achieving. Uh this is Shri Balakrishnan. uh he was head of product
Balakrishnan. uh he was head of product and technology at uh Travelopia. Uh so
they're a $ 1.5 billion a year uh travel company and one of the things that uh he said is that uh you know they were able to uh replace a legacy application uh in 6 weeks with a pair of uh with a very
small team. In fact one of his uh
small team. In fact one of his uh conclusions is that before we would need a team of eight people to do something meaningful, right? Six developers, a UX
meaningful, right? Six developers, a UX person and a product owner. And he said maybe these days it might be two. A
developer and you know a a domain expert. In other words, as Kent Beck
expert. In other words, as Kent Beck said, a person with a problem and a person who can solve it, right? Uh maybe
maybe a pair of those teams, right? And
so that's going to reshape I think you know how they can go further and faster.
Uh so again, maybe just a hint of what teams will look like in the future. This
is the one that excites me most. This is
Dr. Top Pal. Uh he helped drive the DevOps movement at Capital One. Um and
he's now at uh uh Fidelity. And so um among other things he owns an application uh that is the application you go to asks which applications you know the 25,000 applications there have
log 4j right and uh it's his team and he's had this vision of what this application should look like uh but every time he asked like can can we build it his team would say it would take about 5 months right and we'd hire
need to hire a front-end person and [clears throat] he got so frustrated that he spent 5 days just vibe coding it by himself right uh you know directly accessing read only the neo4 4j uh
database um and put it into production, right? And so I think we're seeing a
right? And so I think we're seeing a world where um you know leaders even leaders with their own teams are frustrated saying hey I can do this uh can I do this better myself not better
just can I prove that it can be done and uh by the way what happened afterwards um he was looking around who can help me maintain my application production and all the senior engineers like not me. So
enter uh Swathy the most junior engineer on the team uh who is helping maintain this application and probably outarning you know everybody in the organization uh and interestingly uh he he's also
getting more headcount because the number of consumers of this application just increased by 10fold right so who saw that coming right um so uh here's John Rouseer he's senior director of
engineering at Cisco security and he convinces SVP to um require 100 of the top leaders inside of Cisco to vibe code one feature into production
in a quarter that ended last month, [laughter] right? And so, um, you know,
[laughter] right? And so, um, you know, we're actually getting a chance to be able to survey those people, right? Who
finished? Uh, you know, uh, how many completed, didn't complete, partially completed, etc. And of those who completed, right, what was what aha moment did they have? Uh, as a leader, what's the magnitude and direction of
what they want to do? And so, we're going to go in and study that. And I
just I my prediction is that we're going to see parts of that organization get reshaped as leaders realize kind of what's possible. Everything from
what's possible. Everything from strategy to processes and so forth. And
so let me just share with you one um you know thing that really excites me which is uh I got a chance to uh get back into the state of DevOps research the Dora study with uh um the Google cloud team
and one of the things that didn't make into the report that I just found really exciting was around this. It was like what how much do people trust AI? And
we're using a very strange definition of trust, which is to what degree can I predict how the other party will act and react, right? Because the more you trust
react, right? Because the more you trust the other party, right, you can give them bigger requests, you can use fewer words, you have less need for feedback, right? It's the whole notion of finger
right? It's the whole notion of finger spits and fuel, right? Like you know how many of the 10,000 hours that requires to be good at anything have you used to get good at AI? And one of the stunning
findings was that it's this line. So on
the x-axis is how long have you been using AI tools? Y is how much do you trust it? Right? Right? And the longer
trust it? Right? Right? And the longer you use AI, right, the more you trust it, right? So every every person who
it, right? So every every person who says, "I tried it and it's terrible at coding," right? On what basis did they
coding," right? On what basis did they make that conclusion after maybe using for an hour or two? And what this shows us is that uh you know it requires practice, right? And and this is
practice, right? And and this is probably a teachable skill. Um so length of time on the x-axis is a very incomplete expression, right? It's like
frequency and intensity and how many hours, but it's there's signal there. So
it just shows that uh you know part of your job is to help other people have the aha moment and then help them you practice right so they get very very good at it so they can use every one of
these amazing technologies to achieve their goals. So uh I'll leave you with
their goals. So uh I'll leave you with one last kind of vision. Steve and I we did a vibe coding workshop for leaders um back six weeks ago and what was
amazing to me was in the 3 hours we had a 100% completion rate. Everyone built
something, you know, they built a data visualization tool. In fact, uh, one
visualization tool. In fact, uh, one person uh, built a an iOS app and another person actually got it into the review queue in the Apple iOS app store, [laughter] right? Which is which is
[laughter] right? Which is which is absolutely astonishing. Uh, and here's a
absolutely astonishing. Uh, and here's a guy named Roger Safner. He said, "I used to be a C MVP way back in the day. I
haven't coded in 15 years." Uh, and he's showing off an app that helped him automate the process of getting checked in to Southwest Airlines until the bot detection tools come off. But look at look at the expression on his face. And
so I think uh what we're seeing is like what happens when support ships right and support codes and ships when leaders code and ship. And there's no doubt in my mind that this will reshape uh technology organizations. If you're one
technology organizations. If you're one of those, Stephen, I want to talk to you, right? Because you are on the
you, right? Because you are on the frontier of something really, really important. I'll share with you a couple
important. I'll share with you a couple quotes. Here's from a technology leader.
quotes. Here's from a technology leader.
When I told my team that I wrote an app that, you know, an AI wrote 60,000 lines of code and I haven't looked at any of it, they all looked at me as if they wished I were dead.
Um, we've uh we've had these stupid problems in legacy applications that have been there for over a decade. We
got a group of senior engineers together. We used AI to generate a fix
together. We used AI to generate a fix and we submitted PR and the team accepted it. Right? Unlike the time when
accepted it. Right? Unlike the time when they said it was AI generated and they rejected it as AI slop, right? So this
is maybe happening in your organizations. Um, our code velocity is
organizations. Um, our code velocity is so high. Uh, we've concluded that we can
so high. Uh, we've concluded that we can only have one engineer per repo, right?
Because of merge conflicts, right? So we
haven't figured out the coordination cost uh mechanisms yet. And so like all these were some of the lessons that went into the vibe coding book. Thank you for everyone who were at the signing yesterday. And uh if you're interested
yesterday. And uh if you're interested in any of the talks we referenced and excerpts of our book in uh and basically uh all the links that are in this presentation, just send an email to real genelies.com
subject line vibe and you'll get an automated response in a minute or two.
So with that, Steve and I thank you for your time and we were around all week.
Thanks all. [applause]
Heat. [music]
[music]
Loading video analysis...