# A16Z Strategy: AI Infrastructure, Media, and Talent Wars

**Podcast:** AI + a16z
**Published:** 2026-03-03

## Transcript

Today on the podcast, we're sharing a feed drop from Uncapped, where Jack Altman sits down with Martin Casado, A16Z general partner.
They talk about the shifting dynamics of venture capital, why media now matters in a way it never did before, how A16Z evolved from generalists to specialized platforms, the rise of AI infrastructure, and why talent competition might be more fierce than market competition.
Let's get into it.
The market is so big and it's growing so fast.
Even companies that seem like they're competing end up in totally different places just because so much white space is being created.
But they're all competing, like totally different companies and spaces are competing for the same talent.
So the first time I can remember where the actual talent competition is like way more fierce.
Martin, I'm really excited to be doing this here with you today.
Thanks for making time for it.
And one of the things that I was just chatting with you and laughing about, on my way in, there were like...
many other podcasts going.
There's like one like before and after us.
And I talked about this with Mark about how like podcasts are like this future thing of media.
And basically my question for you is sort of like, as somebody who's been on the inside of a firm that's dominated this, you do a lot of it yourself.
Like what's your experience about like the importance of media for venture capital?
So I think it's probably important to recognize that it's never been a thing really.
Like if you look at a lot of historically good investors, they want very public.
I think about the greats, like Moritz, Ping Li, Doug Lione, Benton, Mike Fawlty.
They're just not very public.
And so historically, there's been no correlation between public and not.
I think a couple of things have changed in that time.
One of them is the traditional media just turned on tech and it hates tech, right?
And so in the past, when I was a founder, to get a...
A lukewarm to positive article is pretty straightforward, and the VCs would help with that.
They would know a few reporters.
It was very easy.
But now it's actually very dangerous because you go talk to them, and who knows what they're going to say.
And so in a way, if you want to help a portfolio, you do want to build a bit of a platform, you do have to go straight.
So I think that's one thing that's changed.
The second thing is, so if you're traditionally in enterprise, take from the enterprise standpoint.
Like marketing has been something that you build brick by brick, right?
And it's like you put content out there and people read it and like it's durable over time.
And so you get this kind of compendium and you build a brand over time.
And it feels we're in an era now where it's just become so episodic that if you don't understand like the current zeitgeist, you just can't even get a voice.
And by episodic, I mean, like today, GPT-5 launched, right?
It was massive.
Like, if you didn't know that that was going to happen, you would have been drowned out.
And if you did know, you could draft on it.
And so, and then it just feels like for some launches, they go, they're a big deal, and then they just disappear forever.
So I just, so much of the nature of how we consume and think about content has changed.
And so I do think that venture capitalists, one, they need to like, if they have a message they want to get out, they kind of have to go direct because, I mean, if it's your own platform, it doesn't hate you.
That's one.
But then also to help your portfolio company, I think you need to build an in-house capability so they can know how to most effectively message.
And you can't really borrow a page from traditional marketing.
And this is from someone that's come very much from the age of traditional marketing.
It's just different.
Yeah, I mean, one of the things that I've been very surprised by is there's always room for another podcast or something like that.
People consume a lot of this stuff.
And I think people in tech find it sort of like a...
it's almost like a halfway between working and like watching Netflix where it's like I'm passively learning, but it's like low stress and people would like rather consume a good podcast than like a new Netflix show.
Yeah, for sure.
And I'll also say like there's always a concern that there's too much content, but that concern has been around forever.
There's always been too many books to read.
There's always been too many books to read.
you know, TV to watch, there's always been too many web pages to read, et cetera.
So it's always been an ordered list that starts with the most important and goes to infinity.
So the question has always been, how do you be in like the top 10 or the top 20?
And that changes all of the time.
I do think you're right.
I think people like to consume things that they can consume casually that is relevant to their interests.
And so it's actually a great time now that you can actually be in that top 10 for the set of people that...
that you care about.
Totally.
So I want to talk about your time at Andreessen and like what's evolved, which has obviously been like a lot.
Can you sort of give the picture of what it was like when you joined?
When do you want to start?
When I joined as a, when I was a founder or when I actually joined as a GP?
Maybe when you joined as a GP, but then let's connect it back to when you.
Okay.
So when I joined it, it was 2016.
So I've been here almost 10 years.
Yeah.
That's a lot.
I'm that wild.
So.
So I think it was the ninth general partner.
I think the firm has 75 people.
Not only were we all generalists, like, you know, you can do whatever you want.
That was kind of part of the pitch.
You know, you can kind of do whatever you want.
But like most of us had done some pretty serious time operating.
Like my journey of my startup was about 10 years, let's call it.
And so many of us, like, we're so tired of the space we came from, we did something totally different.
You know, like, you know, and so it was very, very different than that.
So generalist.
a few people in the firm, and then actually the investing team alone, you really had GPs, and we were all the same.
And then you had relatively junior partners that couldn't write checks that actually would bounce between the GPs.
So there's no alignment at all.
So it's a very, very different structure.
So I guess one of the things that's interesting then over the evolution is that it started in this generalist version, and now you're running a distinct platform.
And the way the firm is shaped is there's a ton of autonomy.
You know, Mark was talking about this on the podcast where basically part of the idea was like, we can recruit these amazing GPs because they get huge autonomy, but we're going to have specialists, you know, sort of leaders for things.
And so I guess, what does that change meant for you?
What's it been like to go from generalist to specialist, I guess?
Yeah.
So I think it's important to maybe talk about why a change is necessary.
So the historical context is interesting.
I think there's two things that are important.
One of them is...
The model of venture came out when like tech was like a non-market.
It was like this total speculative stuff.
And when you meant tech, you meant everything from like bio to software.
Everybody was a generalist.
Often it was just kind of, it wasn't like really a profession.
It was like, you know, if you wanted to play money, you do it.
And so, you know, they made decisions that made sense at the time, but that no longer makes sense.
So for example, it's a historical quirk why you know, we, venture capital uses like the same model that you'd use for like a dentist office or something, like a partnership where everybody's equal, right?
Like that makes sense for a small service organization, but you can never scale that.
And so there's all these decisions that were made when the market was much smaller that as AOM grows and as the market grows, like there's many companies, many more companies you could deploy in now, you'd have to restructure the firm.
And so kind of our view is like, we definitely want to scale.
We definitely thought we had the best platform for founders.
And also the markets were so large, you didn't have to be a generalist.
Like in 1980, if you did enterprise infrastructure software, how many companies could you invest in?
Not a lot.
Two or something like this.
Someone can have an entire career investing in databases alone.
And so as the market grows, clearly you have to specialize.
And so when I joined, we were all generalists, often that hated our own disciplines because we'd kind of been through it.
Can I ask you a question about something?
Do you have to become specialists as the market grows or as the firm grows?
In other words, is that...
Is the specialization choice downstream from growing the firm or do you think it's downstream from the market growing?
I think it's ultimately the function of the market and I'll describe why.
So if you believe that this stuff is competitive, right, which I do, then you need to end up with a product that is competitive.
And because it's adaptively competitive, like let's say you've got two firms that are competing, you're always going to be looking at like what...
the weakness of the other one is.
And so, like, for example, if a certain firm can't do seed, then, of course, you'll want to do seed.
Or if they can't do large checks, you'll want to do large checks.
What happens is everybody ends up getting as many products as they can so that they don't have any weaknesses, which will naturally happen.
Now, you can only do that if the market is large enough.
And so now you have a high AUM.
You've got a lot of products.
I've got a growth fund, I've got a seed fund, I've got a venture fund.
And then you have to ask the question of how do you scale that?
And venture was not built to scale.
And I think this is why we've seen the industry go this way, which is the market has increased a lot.
Funds want to be competitive.
In order to be competitive, they have to find out what products that they offer that are actually competitive.
This drives to higher AUM.
And as a result, you have the specialization.
When you're...
No, just that said.
So, but there's also kind of this internal thing, which is assuming that you want to scale AOM independent of the market, you have to solve this problem because you just can't scale like a consensus org of generalists.
Like, it's just not something you can do.
Like the people issues on the inside.
You just can't get through good decisions.
Is that what you mean?
Well, I just think conflicts, well, there's many, many issues, right?
Like, but one of them is you wouldn't ever have...
a structured approach to tackling a market.
So you can never know that you've got good coverage because maybe everybody wakes up in the morning and they said they all like the same thing.
And so I just don't think you could actually, even from a numbers game, scale it because you don't, you're not carving it up enough where you actually know that you've got like a uniform focus.
You don't know if you have, are hiring people that can cover the certain areas.
I actually just think, even just from a strict number standpoint, it doesn't work.
how valuable is the specialist thing when you're in these competitive situations?
Like, I imagine that a lot of the times when you're competing to win a deal, it's, you know, up against a firm that, or a partner that is like more or less generalist, I would think.
And I'm curious how that plays out sort of in the day-to-day.
So I'm not, yeah, it's hard to answer how much it helps in the competitive situation.
I think...
I think my experience is it's a lot more powerful that founders know that I've been a founder.
And I know this is such a cliche thing to say, but I do feel that resonates much more than like, I got a PhD in computer science or I know infrastructure.
Because the reality is most founders know a lot more than I do about whatever their area is, even if I've got a high level thing.
So I think I've been competitive.
It's not hugely.
But what I think is very helpful for is I am primarily a Series A investor.
And at Series A, you have to have some thesis on how the tech hits product and how the product hits the market.
And unless you've been very close to both of these things, that's a hard thing to do.
Now, if I was a growth investor, it wouldn't matter.
I just look at numbers.
But for where I am, I think you kind of have to understand.
Yeah.
An interesting offshoot question from that is, You know, when we were talking earlier about how important is media, you're like, it seems really important, but there's a lot of great examples of investors who are all over media and social media.
There's a bunch of examples, phenomenal investors who you never hear about if you go on the internet.
Yeah, I literally don't know if they're correlated at all.
Mostly the best investors I have known in the last 20 years had no media presence and they had no interest in it.
Totally.
And then I'm wondering, I think, you know, around being a former founder.
Yeah.
as I'm just like thinking through names, I can think of like a lot of examples of both.
I definitely think founders appreciate it.
And I'm, you know, speaking as somebody who's a former founder, I think that's a nice thing.
But like, it also, I wonder if that's also an uncorrelated thing, or do you think that has more of a correlation somehow?
Okay, so I'm just going to guess.
I would guess that founders really appreciate reach.
And so I don't think a founder is like, Martin, I saw you on that podcast.
You seem smart.
Because everybody sounds pretty smart on podcasts and articulate and whatever.
I do think a founder would be like, hey, listen, when you really believe in something, boy, you talk a lot about it.
I will have the opportunity to talk about it.
You will help me kind of break through the bootstrap problem of zeitgeist understanding and brand.
And so I do think having a platform matters more and more.
And again, a lot of this is just because the media.
has turned on tech so heavily.
Like there just aren't a lot of options.
Again, I mean, I think sometimes we in VC kind of overweight our importance in these things.
Most companies with great brands did not do it through a VC firm.
Totally.
Right.
And like, it's not like, you know, we somehow can single-handedly make great brands, but we are an accelerant.
We are a platform, you know, and there is actually a lot of signaling as a result of alignment with a good firm.
So I think all of that matters.
Yeah.
I do think that it's, there's this question of like, VCs getting to do the great deals because they were the top VC or are they in some sense helping make them?
And I, you know, my own instinct is that for the most part, it's the former and like, you know, companies are just almost exclusively made by the founders.
I totally agree 100%.
I think that the primary reason to create a distribution channel as a VC is so the portfolio can get out there and reach to people.
This is very hard what we do.
It's not because like whatever, Martin needs to be famous or Martin needs a brand.
Like that doesn't really matter.
That never comes up in like a closing situation.
I mean, I've done so many deals, right?
That's never been a thing.
But I do feel that a number of our companies, you know, once they're ready to launch.
you know, we can provide a benefit.
And so I think that is ultimately the benefit to the portfolio.
But I've never seen a company win a lose by marketing.
So I just don't think that that's the high order.
Totally.
Okay, I want to jump over and talk about AI a little bit.
And in particular, I'm interested in talking about like, infrastructure, because it's something I know relatively little about.
And so I want to like, learn from you about like, first of all, like, What is it?
If you could put some broad fence around what the term is.
Yeah, so I do computer science infrastructure.
So I'm like a computer science maximalist.
I think it's like the meta-discipline that you can solve other disciplines with.
We solve graded unified field theory and physics goes away and then we just go on to biology type thing.
So I do computer science.
So infrastructure is the stuff used to build the apps.
So you sell to technical buyers, people that use computer science to solve business problems.
So like if the company sells to marketers, that's not infrastructure.
But it is developers, database administrators, networking, that's core infrastructure.
I mean, and so like depending on how you count, this is a multi-trillion dollar.
But the important thing is the actual buying and use behavior is a very technical thing.
So that's our definition of infrastructure.
Okay, so when you're looking...
Compute network storage databases, now models, dev tools, that type of stuff.
And it seems to me, from just my viewpoint, is that when these new paradigms come, cloud, mobile, AI, it seems like that's a very good moment for infrastructure because the board's shuffling a lot and new infrastructure's being laid.
And so when you're looking at it, Is there any broad way that you think about, you know, will this continue to exist over time?
Will the models or, you know, whatever AWS in the past, will they do it?
Will there be, you know, a need for somebody third party?
Like, how do you even start to think about what will play out over time, just like at a structural level and infrastructure?
So can I say something that may not be true, but I feel very strongly.
That's what we're here for.
This is like a total.
That's what this whole thing's about.
This is like an inflammatory opinion that's self-serving that may not be true.
But it's an observation.
Here's my observation.
In software, the true differentiation is technical, right?
Now there's, of course, brand stuff and business stuff.
But if you have two products, it comes down to a technical problem.
that almost always comes from the actual infrastructure that the software is built on.
So if I built two, let's say, dog-walking apps, the fact that it's got three or four features, that's a very light differentiation, but one being super fast, one being super slow, that's like an infrastructure.
So the companies that provide infrastructure, I think ultimately they are the source of value, they are the source of differentiation.
And so while there are fewer infrastructure companies, my bet, and this is my inflammatory opinion, is that they just have better multiples and the more durable because they service everything above it, but they're the thing that provides it.
And actually, Sarah Wang, who is an investor on the growth fund here, and I did a, you know, kind of relatively loosey-goosey public market analysis where, like, what are the multiples of companies that are infrastructure versus apps?
And they just have higher multiples for this reason.
Does that make sense?
It does make sense.
So my view is the infrastructure is where the value is.
Every time you have a platform shift, you'll get a new set of infrastructure companies.
And then a bunch of apps get built on top of those.
But the value is going to accrue largely to the infrastructure because that's where the differentiation ends up happening.
So you don't need to have a platform shift necessarily in order for you to have important infrastructures with good multiples.
I just think it's a durable part of any sort of...
But then the question is, what happens when it matures, like the clouds do and becomes an oligopoly and they no longer can private investors invest on it.
But every time we've seen that happen, you see a layer of infrastructure evolve on top of it.
So maybe say it this way.
So the way I view the world is you've got a bunch of app developers who are non-tactical and they want to develop apps to solve all sorts of like consumer problems and business problems and whatever.
So.
Their goal is to build an app for a non-technical user.
So why would they kind of invest heavily in technology?
So they will pick up whatever is easiest to use technically.
And so, you know, the companies that fill that need are the ones that provide a lot of the value of the true differentiation.
Does this make sense?
And so I always think that will always be something that you can make it faster.
You can make it easier.
You can make it more reliable.
It'll always be kind of the bedrock that apps get built on.
And, you know, until people stop wanting to produce apps, you'll always need to produce.
And this is totally independent of macro shifts or platform shifts.
How do you think about if or when the big players are going to decide to enter those markets and how that...
might impact things, you know, like in cloud, like whether or not AWS was going to offer something directly now, whether like, you know, OpenAI or Anthropics offer something directly, or are you like, if I'm investing at the series A or B, that's not that important.
You just have to think about great entrepreneur, big market, and that's okay.
Yeah, I mean, I worked at VMware for four years.
We were the big incumbent.
And so like, we're always worried about the shadow that is cast by these incumbents.
But the reality is like, it's not nearly as strong as everybody's worried about.
And it's very hard for these big companies to execute.
And so, you know, reInvent is like the AWS conference.
And I swear, being an infrastructure investor for so long, every time they have reInvent, I have to play therapist to all the founders.
They call them like, oh, they're entering our market, they're entering our space, like they're doing all this competitive stuff, et cetera.
And I still today can't really think of a company that AWS has put out of business, even though it entered the market.
And the reality is they kind of compete with everybody.
And so, I mean, If the market will bear an independent company, then that requires your own sales force, your own focus on customers, your own support, your own technical differentiation, right?
And like no big company can like build a small company in a big company because they have too many centralized service.
And if the market won't bear an independent company, there's no company to build anyways.
And so my view is as long as the market is continuing to expand, which software is continuing to expand, if you enter an area that's viable, as it expands, you will fill that expanse.
And if that doesn't work, then the market is either not big enough or it isn't expanding fast enough.
And I just feel like if you take the historical view, this is the case.
I strongly agree with that.
When you think about markets in AI right now and how things are evolving, one of the things I thought was really interesting from talking to Mark was basically as you all sort of ambitiously grow the firm, one of the biggest issues is companies running into each other in this conflicts dynamic.
And obviously you're...
You're becoming prominent within an area to a degree where you're going to just, I would imagine, just companies, as they grow, they grow into each other.
And what's your experience with that?
It's such a complicated problem because you can try and do everything right and still end up with conflicts.
So it's actually pretty good to categorize the conflicts.
And so perhaps the most common conflict is one company that, two companies that you've invested in, one pivots into the other one.
Yeah.
Right?
And this one, It's basically impossible to do anything because companies have to figure out the right business.
You're on the board or not, and you don't control it, and they do that.
So that one, I feel like no investor can, there's nothing an investor could do.
There's another more pernicious type of conflict of existing portfolio companies.
I'll get to the net new companies soon, which we're seeing a lot now, which is.
Imagine you have an old, imagine you have a tech revolution like AI, and you have a set of old companies doing things the old way, and you have a set of new companies doing the new thing, and the old company wants to pivot to using AI to do what they did before.
But the reality is, is the old way is not the AI way.
They're not AI native, right?
And so now there's this question where she's like, well, when we invested in this company, it was doing X, whatever it is.
And now it wants to do X with AI.
But the reality is the AI way of doing it is entirely different, and they've got no chance.
So then you have, you know, the dilemma of going to the founder and saying, listen, we're investing in...
one of the new space, but it's AI and you're not AI, which of course that's not going to work.
Or you just don't do the deal.
I run into this one a lot.
We've got a very large portfolio and to date we've just been like, hey, listen, like we're going to back the portfolio companies that we have.
Actually, this happened last week.
You know, the founder company says you can't invest in this.
This is the space we're going into.
They haven't even done it yet, and we try to do the right thing there.
So that one is, I think, the toughest one for all investors today just because you never want to bet against your own portfolio, but the reality of them being actually competitive is very low.
I think the most, and then there's one more, which is kind of like this.
fun stage thing, which is like, we've got a growth fund, they do their own thing.
We've got like an early stage, they do their own thing.
And, and like, sometimes the communication isn't always perfect.
And you can kind of end up in like, you know, conflicts that way.
The one that we simply do not do is, you know, and I always have this talk track, you probably heard me say it.
And I borrowed it from Chris Dixon, but it's very, very effective where you basically say, for any company that I'm an investor in, If I'm talking to another company that looks similar, I'll ask the founder.
I'm like, listen, is this your mortal enemy?
You only get one.
You can't, you only get one, but if this is your mortal enemy, we'll do everything together to kill it and we won't invest in that.
But like you have to name your mortal enemy and you can't keep changing it.
And I think at least that gives them the power to decide who it is, but not kind of hamstring investment efforts.
Totally, that makes sense.
I mean, it's also funny because I think a lot of times, you know, two companies that look the same but are serving very different segments of the market, those are actually, they might sound like competitors, but they're actually never going to bump into each other versus...
two companies offering different products to the same customer are much more likely to bump into each other.
Well, in AI, it's even crazier than that, which is the market is so big and it's growing so fast.
Even companies that seem like they're competing end up in totally different places just because so much white space is being created.
But they're all competing, like totally different companies and spaces are competing for the same talent.
So the first time I can remember where the actual talent competition is like way more fierce.
than the market competition.
Well, actually, what's funny about that is I've heard of people getting upset with their investors because, and they're like, I know this company has nothing to do with it, but we were interested in that candidate and one of your partners sold that candidate on one of their...
It's a very real thing.
And what's interesting is like, you often don't even know, right?
Like, you know, like, they'll say, oh, I'm, you know, I'm talking to a healthcare company, you know, or whatever.
And you're like, okay, well...
What's tough, but I guess is also like a blessing overall is I think there's a lot more good ideas than there are.
talented people to work on those ideas.
And I think one of the hardest things right now is clustering talent densely enough behind a good idea.
Yeah.
It's also, this happens when there's these large infrastructure build-outs.
This happened with the cloud too, which is there are these moments in time where to build the system, you have to have experience with the system at scale.
This happened with the internet.
This happened with the big cloud data centers.
And this is the case with AI.
Which is like, it's one thing to like go to school and know AI and be a good researcher.
It's another thing to have actually trained a very large model.
You know, like maybe what, there's 30 teams that have ever done it.
And that's part of where you see these like mega acqui-hire acquisition things.
Because it's like certain experiences are just worth a huge amount.
Yeah, yeah, 100%.
And like the market always normalizes these things.
By the way.
I mean, this is all ancient history now, but the exact same thing happened in the internet.
I remember once there was basically one guy that ever wrote a BGP stack, which is like, it's a way that routers talk on the internet.
And he was like the one guy that could make it work.
And so he just basically got these crazy, at the time, crazy offers.
And he jumped between all the router companies and do that.
And there are very few teams that could do this.
And so we've always seen this episodically in the industry.
We're just kind of seeing the new version and the, listen, the businesses are working and they're doing great.
So we're kind of seeing it on steroids.
Yeah, I mean, if you're a FANG-sized company, what's it worth to have like the one or two or three people who really know how to do something huge?
Yeah, I also feel like...
Tech always figures out a way around kind of regulations and markets.
Like, you know, in like the late 90s, it was like, you know, you could IPO a company for very little, you know, with not a lot of market traction.
Remember like the whole SPAC craze?
And then now we've got these clear to acquire things.
I think the reality is in hot markets, people know that there's a lot of value to be had.
Nobody knows exactly where it is.
And so, you know, there's all sorts of things, you know, the markets try to do to get access either to the talent or the companies or whatever it is.
And we're kind of seeing our version of that now, whether it's these, like, I will hire an individual one, I'll do it.
We're going to acquihire.
But again, I feel like this is all normal in the sense of, you know, we've seen it in different shades in the past.
Yeah, totally.
It's like an evolutionary response.
What are the markets right now in AI that you feel most confident are totally working?
What are the ones where you feel like they're on the horizon and should be working very soon?
And then what are the ones, if any, that you maybe have low confidence will work, period?
Yeah.
So the diffusion markets are all working.
So any area where you bring the marginal cost of creating something, a piece of content to zero is clearly working.
You're creating an image, creating music, creating speech.
And we don't think about these markets as much because we're all so focused on the frontier labs.
It's cheaper to build these models because they're smaller.
And then people need content.
And actually, the economics are so simple.
Whatever.
Imagine you're an artist and you're like, OK, I'm going to draw a picture of Martine.
How long would that take you?
A while.
Whatever.
three hours and it costs you 400 bucks, right?
But if I have a model do it, it's a hundredth of a penny type thing, right?
So you've got a four orders of magnitude difference in economics.
So that's why we've seen those types of companies, you know, I think like, you know, 11 labs or whatever do very well.
So like that's clearly working.
And this is content creation where the marginal cost of creation goes to zero.
I actually think the whole kind of loneliness companionship stuff is definitely working.
It's just this very fragmented market.
So I think...
I think the unit economics are fine.
I'm not sure from an investor standpoint how you think about it, but it's a use case that will be solvent, that will do fine.
Code seems to be working incredibly well.
Yes.
And you see this in cursor and the whole thing.
The areas that I don't know, I mean, they're working, but I don't know how the economics actually pencil out are the enterprise use cases at this point that are kind of a bit more agentic-y, automate-y.
These are the ones you're putting in the middle bucket?
This is like what you're saying is like kind of working, but not 100% sure yet?
No, no, no.
So the ones that are, well, so the middle bucket was like, was companion, was actually like, you know, like.
like the friend, the emotional, like the character that AI is like, there's a long tail of companies that are basically emotional support and or friends and or entertainment.
It's probably also a big component of the usage of like the main models and stuff.
Yeah, 100%.
Like that's clearly working in the sense that people are willing to pay for it, the engagement's great, et cetera.
From an investor standpoint, it tends to be kind of long-tailed and fragmented and kind of spread and stuff.
And then that enterprise agentic workflow type stuff.
That was the fourth one I mentioned.
That's like, you know, chatbots.
I mean, clearly it's working and there's...
There's companies that are doing it, but it tends to be, you know, if you look at the companies, like, you know, there's a lot of, like, bespoke work going on.
Like, it's just a different type of economic model than the content creation one where it's like, it's just a model.
So, those ones we're still trying to understand.
Yeah, I mean, one way to think about that is, like, how confident are you that, like, highly skilled work will get replaced in, let's say, like, legal finance, accounting, tax, like, those kinds of areas.
So, I think the way I view it is, It's actually very simple.
So if the use case is the model is creating content, and that content is whatever, it could be language, it could be image, that clearly works, right?
So, okay, if the model is automating something a human being would do, and we conflate these two things all the time, that's totally different, right?
So if I'm like, model, do this thing instead of me, that's not content creation.
It somehow has to mimic exactly what I do.
That area still needs a lot of work, it seems to me.
And so they clearly can do some work of a human.
But, you know, you know.
not as exact, and they need a lot of guidance.
And I think that's an area where there still holds a lot of promise, but the economic case isn't as obvious.
Make me a picture versus go browse the web for me.
And so it's kind of that second one, the automating what humans do, where we're still like, we've got lots of investments, we're very excited about it, we think there's a great future there, but the economic case isn't nearly as good as make me a picture.
Totally.
To double-click on code for a second, obviously you know a lot about it through Cursor, you were a technical CTO.
where do you think we are right now?
You know, like I, I just posted one with Guillermo who, you know, and who obviously knows a lot too.
And it was great.
It was like, this is both the future.
And it's also at the moment, you know, it's not obvious that it is in today's, you know, incarnation.
It's not necessarily producing quite as much value for engineers as even they themselves experience, but clearly it's going to get there.
So, yeah, I'm curious.
So just so you know, AI in general has this problem, which is so dazzling.
People conflate, oh, this is dazzling with this is useful, right?
Yeah.
That's for everything, right?
It's not just code, right?
It's like, you're so impressed.
These things are magic.
And then somehow that dopamine, you know, hit.
What's really funny is, so I posted this on X and...
you know, like this study that was saying that people experience their own programming as plus 20% and like the observed results are minus 20 or whatever.
And What was funny was there were a bunch of reply threads where somebody was like, no, no, no, no, this is crazy.
I've been using it and I'm so productive.
And then the reply to that is like, that's what the study is saying.
Which I'm sure for some people there, but there is this thing.
Literally, there is an endorphin hit.
These things are absolutely magic, but I don't think it makes it very hard to think clearly about the actual utility.
Now, so I think you can say a few things.
There's a lot of things that it does very well that programmers don't like to do.
that is pretty routine.
Documentation.
It's great at writing documentation.
There's a lot of boilerplate stuff it knows.
The thing that I use it for the most is writing code isn't just writing code.
Writing code is understanding the frameworks.
It's knowing how to deploy it.
It's knowing how to run the toolchain.
And there's no first principle way of knowing that type of stuff.
There's not some core computer science fundamentals on deploying to...
Like, that doesn't exist.
And so it has all of that knowledge, which is clearly very useful.
The writing code itself, I think, is still clearly very early days.
I mean, if you constrain how you use it, it can be very effective.
And then if you don't, it may not be as effective.
And so I think that, like, studies like this that are purely observational are hard to read into because...
Totally.
You know, it's just like, this is like, you can use it for anything.
And because they're so magical, I do think people tend to use them for stuff that they may not be so good at.
just because the experience feels good.
And so my guess, like any new technology will develop best practices.
I feel very strongly we're going to get a 10x in productivity.
But like, it'll take us a while to get, listen, I remember an other epoch of development productivity.
Like when the IDE came out, when higher level links, when OOP came out, like we'd get so enamored with the tool set, like object-oriented programming, I'm going to do everything in it.
And it turns out these were great advanced.
in computer science, and they helped the best practices, and they helped architecture and engineering.
But at the time they came out, they were just so cool.
Like, that just kind of took a lot of our focus.
So I think we're seeing that.
So it's like, this drop of productivity is not like necessarily code requires you to drop productivity.
I think it's...
Of course.
It's just so cool.
I'm going to try it with everything.
Yeah.
It does seem like it's on a path to like, you know, in the same way that like people have been saying this about self-driving cars and it seems like it's going to become true.
It does seem like we'll get to a place where like you can.
It's so clear.
I mean, this is incredibly obvious.
I mean, you can literally just scope it to a subset of things that are obvious.
Like it's really good at writing text.
It's really good at writing documentation.
It's really good at like dealing with a bunch of like, you know, long tail framework stuff that you don't know.
It's good at teaching you things.
I mean, there's clearly, there's things that are obviously good at.
I just think.
We get so enamored with it, maybe we start using it for stuff that it's not so good at or not so equipped to deal with, et cetera.
But yeah, this is very clearly, it's going to change software.
And sorry, I don't mean to ramble on.
I just have to say, I have been in software for a long time, since the late 90s.
We disrupted everything, right?
We disrupted the back office.
We disrupted hotels.
We disrupted everything.
It's the first time I say that we're probably getting legitimately disrupted as a discipline.
What it means to be a software engineer is changing pretty fundamentally.
I think it's because of AI.
So it's kind of fun to actually be the disrupted for a change.
That's awesome.
Another topic I wanted to get your thoughts on was why is open source so important to you?
And like I saw, you were really excited about open AI as an open source model.
And I know this is thematically and spiritually important.
Why do you think that it is such a critical part of the way that this plays out?
So I think open source is historically one of the best mechanisms that shows a healthy ecosystem, right?
And what normally happens is somebody does something closed source, it turns out to create a market, and then somebody releases open source, and it stops a monopoly from forming and enables everybody else.
And then it kind of...
keeps the people that are close to us to continue to be innovators and allows everybody else to come in.
So it's just been very, very healthy.
And the thing that really worried me last year, and in the past, academia, VCs, startups were all very pro-open source because they understood that it was a very important part of a healthy competitive ecosystem.
And the thing that really, really worried me last year was...
the people that should be championing open source, like VCs, like startup founders, like academia, were decrying how dangerous it was in relationship to AI.
The implications of this to me are huge, right?
I mean, of course, you know, the national security implications are pretty straightforward, which is like if somebody else does the open source, it proliferates, and that's not good for US interest.
But for the industry, it's terrible, right?
I mean, this is kind of how you actually create monopolies if, you know, you're not allowed to create...
something that enables everybody else.
And again, it was very dramatic when like the Node Close was like, open source is bad, and Founders Fund is like, open source is bad, and you had academics saying open source is bad.
And so I was much more interested in like...
trying to reset the discourse than any specific open source release.
Yeah, and I guess a lot of that probably came down to how potentially dangerous was the technology.
And so if you thought it was extremely dangerous, for example, then there is an argument for massive containment.
What was the steel man in your mind at the moment when closed source was such a strongly argued?
If you had to argue why you think people were saying that, what would have been?
I really think it's the legacy of BoStrong, right?
So, you know, Boestrom wrote the book Superintelligence in 2014.
Terminator's waking up, we got to continue.
But this is before all of these things, right?
Like, Boestrom's book was a thought experiment.
It was like this platonic ideal of AI, and then somehow that created this very interesting kind of intellectual journey on the perils of AI.
But then, you know, like, GPT-2 lands, and these two things got totally...
You also got, there's a lot of incentive for people to be doomer-y, I think.
Like it gets a lot of clicks.
It was like.
Yeah, but not historic.
But it's the weird thing historically.
Like let's take the internet as an example.
So like I was there during the early days of the web.
We had a lot of examples of like how it actually changed the dialogue when it came to risks, right?
We were running critical infrastructure on it.
We had totally new types of attacks like the morse worm, which had actually taken down computer systems.
So we're at.
This space, we're like, okay, well, it makes you more vulnerable if you use it.
And we have new attacks that you can attack with it, right?
And yet, academics are like, this is great.
The technologists were, this is great.
So you had this very even-handed debate.
What was so weird about the AI was it wasn't even-handed.
Like, I'm all for both sides of the debate.
Like, I'm not a, you know, I'm not just, you know, pro-innovation at all costs, but like, that's not what was happening.
And so...
Like, maybe you're right.
Maybe it's like the Duber's got more click, but I think it's something more than that.
I just think that there was an existing intellectual legacy that came from Bostrom that had some very influential people, right?
Like, Elon was killed by that.
You know, Eric Schmidt, Moskowitz.
And they had very legit concerns, but they were kind of already primed and like...
You know, there was already kind of that ready.
So when it happened, I just think they were already ahead of the game.
It took a while for the rest to catch up.
And now when I listen to the discussion, it just feels more even-handed, which thank God I don't have to be on Twitter talking shit about this like I did for so long.
I feel like the right voices are in the room.
For sure.
And obviously, this isn't like, you know, I don't think either of us was saying that like there aren't real risks.
No, there's totally real risks.
It was just a totally lopsided debate.
It's so crazy when VCs are talking against open source.
I mean, to me, I mean, like no academics are talking in defense.
But now we have a bunch of academics in defense.
I mean, like I think the right people got mobilized, but it really took some rallying to get the right folks back into the conversation.
Yeah, yeah, absolutely.
I want to ask you just a couple more questions about sort of the structure of the firm and sort of your own work outside of the specifics of what you're investing in.
One that I thought was a really interesting point from Mark when I talked to him on the podcast was basically around, you know, like, how do you sort of drive the right overall aggression of the firm?
And he said something to the effect of like, when you're in a market moment like this.
the right answer is to just encourage people to do more.
And so many partnerships are trying to get other people to a no, and that's the common function.
And he was basically describing something where it was like, how do we get people to a yes?
And how do we take advantage of this?
I'm just curious how you feel and your experience in the last couple of years in AI land.
So one of the reasons Mark is such a great leader...
is he, his intuition on the temperament of people is almost perfect, and he will drive, like, the right behavior relative to that.
And so, like, if he thinks people are being too conservative, of course, he'll drive them to be more aggressive.
There's definitely a more aggressive stance.
I mean, the reality about AI is there's been a lot of money that's already been lost in absolutely record time, right?
So just because, like, the upsides aren't great doesn't mean, like, there's been a lot of money.
And so as a firm, we tend to be fairly disciplined and do a lot of market analysis.
And he thinks we're coming.
And so he's very good about pushing the team.
And I think he's absolutely right to do that because there is already a foundation of discipline that is not going to be eroded or compromised by doing that.
On the other hand, there are individuals who are like, total shoot from the hip, like everything.
And then he actually tempers his messaging a lot with those.
And so I would say, again, I mean, you know, I don't know what was in his head when he was saying that, but I just think if I was going to add a little bit of nuances, my observation of Mark is he's very good at pushing when people need to push, but he understands the situations when like that's probably not the most appropriate thing.
And so I think this is a core issue of leadership, which is you need to provide kind of the right kind of macro.
you know, macro, you know, shift in order to get the right one without being too overbearing.
Yeah, I think, you know, some of that conversation was in relation to, like, you know, fund sizes and what's possible.
And I think some of it was articulating just, like, these companies can be enormous.
This opportunity is, like, you know, quite oversized relative to what's going on.
Yeah, yeah, but I mean, but again, I just think it's important to know, which is...
Yeah, that it's a per person thing.
If you take, you know, him at his word, it would be an infinite...
deployed infinitely.
Right?
So like this is a...
It's calibrated to people.
This is an intellectual landmark, which is set...
And is 100% the right one to do.
But what's important, he's so good at that.
Yeah, it is in relationship to the mindset of the people that he's talking to.
And he knows that.
And what flagposts do you have to put out to get people to the right place?
100%.
And 100%.
And then I have seen him very subtly, depending on who is the audience.
Yeah, yeah, yeah.
You know, he'll move that flagpost to different places.
Where do you normally experience yourself there?
Do you feel you're often needing to get pulled into more aggression or into more?
I think I'm a 7 out of 10 for aggressiveness.
I would say my team is a 5 or a 6 out of 10.
There's people on my team that are 10 out of 10s.
There's people on my team that are 3 out of 10s.
So I think, like, if you did a normal distribution, I'd say we're a 6.5 to 7.
And so for us...
You know, he, I mean, he, he pushes pretty hard, but I know he knows that he's getting like, you know, like a step forward as opposed to like.
Yeah.
And I think that's like one of the, I mean, being a leader of people is always in relation to, you know, pulling, you know, minds and so that's always how it goes, which is, you know, it's a rare thing to, it's rare to be able to do multiple versions of that at the same time with lots of different.
No, exactly.
Exactly.
And it's just, it's just, it's hard to appreciate from the outside because you have to actually see the conversations.
It's something that he's just phenomenal at.
And the very kind of nuanced different takes where he kind of knows where people are, you know, kind of nudge them in the right direction.
To the extent that we are in somewhat of like a gold rushy in the good sense moment, you know, overall.
Yeah.
Do you think, does it change your perspective at all about what you need to see to want to make an investment?
So like maybe a specific version of this question is in a somewhat stabilized time, I think most, you know, most people would agree that you should only back extremely special.
founders.
Is there ever a version in these kind of moments when a good founder in a great market with exceptional traction or some configuration like that, where you say, actually, you know what, that works here and that can produce something really big.
So do you know how we think about investments?
Because I think it answers this question.
So it's very simple.
So the way that we think about investments, and the reason is the only way you can scale because you can actually distribute this kind of algorithm to a team is the only sin is picking the wrong company in a certain space.
Because that conflict thing?
Because you're conflicted out of the winner.
Like, investing in a space that doesn't work is fine.
I mean, like, there's no way you can actually predict whether a space is going to work or not.
I mean, that's like weather prediction, right?
But in a given space, if you know all of the companies you do the work, you can most likely, you know...
at least tilt it, like you can do the work to determine if you think one is better than the rest.
Like it's something you can actually put.
So the way that we view the world is first you have to identify legit spaces.
We think that founders are smarter than VCs.
So I don't care if VCs think it's interesting.
If there's five founders in a space and they're good founders, man, they're betting their families, their fortunes, you know, their time.
So it's probably a real space.
And then we do the work to understand the space and all the teams and then we make a pick within that.
I mean, that's really how we think about it.
That's true within AI as anything else, right?
The thing that's harder is, and I've evolved so much as an investor, I used to think like, oh, we'll get good deals.
Like price matters, outcome matters, TAM matters.
And more and more, especially with AI, that's what you have to throw away.
The market is the market.
And that's what matters the most, you're saying?
It doesn't matter at all.
I'm saying, so we don't know what the TAM is because it's growing so fast.
Like, nobody knows valuation.
So I think this is, it's contrary to like common belief.
I think in these times where you don't know the TAM and things are moving quickly, you definitely want to pick the best team.
You definitely want to pick the best team.
I don't think you should overthink the space, but like...
Asking questions about like TAM or valuation or value makes a lot less sense because that's actually what's uncertain.
You just need to be in the best one.
You have to be in the best ones.
And the market will just produce what it produces on some way.
The market is the market.
And listen, either you believe that the stuff is expanding very quickly in markets or...
are efficient or not.
And listen, having been through the dot-com boom and bust, the reality is the market was actually pretty smart.
And if you put the bets in the right companies, that would have been generational wealth.
The same thing with cloud, the same thing with mobile.
And so the goal is finding the right companies.
And really, if there's one change, I would say is you need to throw away too many thoughts about market sizes in town.
Is the rational sort of behavior then to...
You know, obviously, you want to invest as early as possible, but you want to invest as early as possible when you know that you've got the right one.
So does that ever push you to being like, I'd rather wait around or two here?
Oh, yeah, all the time, right?
Yeah.
All the time.
So, I mean, this is all very rough heuristics, right?
Like, you know, we get it wrong all of the time.
You know, I've made so many mistakes.
And so you're just trying to beat the market, right?
You're just trying to have.
But yeah, very often, our discussions are like, do we actually know who the winner is?
And often we wait for that reason.
Basically, the earliest that you feel confident you can pick it.
Yeah, and so listen, when we do seeds, normally it's like the person that did the thing in the big company.
And now I was doing the thing and this is the world expert.
And the thing is a very technical thing.
And somebody else isn't just going to wake up and decide to do it who's a good founder, right?
Because the pool of people that do it are like fives.
And this one's the best of the fives.
That's kind of like for early investments, the way that we think about it.
And then most everything else is actually the result of a lot of market work.
And then this is our best guess.
This is kind of best approach, best team, best market.
And then in these types of ways, and this is where market, this comes from market.
And market is totally right.
If you think you can outsmart the market, I think...
you know, it's very tough.
And so just being the best deals.
As a final topic, I want to just hear your perspective on the board relationship and board roles in general.
And maybe as like a prompt on this, I feel like you've done something which I find very impressive, which is it seems like you're able to manage successfully many more board seats than a lot of people.
And, you know, I often will hear common wisdom that, you know, it could be 10 or 12 or 15.
But it seems like, you know, you found a way to do more than that and be very effective with those founders.
And so I just want to hear sort of your perspective on like, what's that relationship?
What do you think is sort of like the limiting factor here, if any?
How does it all play out?
Yeah, I mean, I do think that like a lot of the common wisdom on boards came from like that earlier year in DC when, you know, it's like people would literally choose VC for like a life choice or whatever, right?
And I think if you come from like pretty serious operating like you do and like I do, like we've just got a lot of hours into the day to throw at it.
VC is also involved that we've got better platforms that actually really help with these things.
And so, you know, between like actually, you know, the hours in the day, I mean, how much does that like board?
I mean, you're a board member.
I actually find that like, can I just take a step back?
Let's talk about what boards mean.
I always ask when I invest in a founder, what is a board for?
What do you think they say normally?
I'm actually curious what the most common answer is, but I couldn't imagine.
What do you think it would be?
I would think they would probably say it's something like, you know, governance and approvals or something like that.
No, that's what they should say.
That's what you and I would say.
They say to provide guidance, to help with hiring.
I'm like, no, that's not a board, right?
And so a lot of, you know, there's a lot of this belief that like a board member is somehow helping with company building.
And almost like it's actually hard for a board member to be like the best friend of a founder for those types of things because like, you know, you're...
you're a fiduciary and you do governance.
So the actual board work itself is just not a lot from the fiduciary governance standpoint.
So often implicit in this question is non-board stuff.
How can you be helpful to a company and everything else?
Because that can take a lot of time.
And I do think this is where, you know, having a big platform to lean on, being totally available helps a lot.
But it's not the board work, it is the other stuff.
And so I would say to anybody listening who is a VC, you can take as many boards as you want.
The actual board work itself is not.
The question is, can you still be available to founders and add value whether you're on the board or not?
A lot of the companies I spend the most time with are not even on the board.
Yeah, that's what's funny to me is people talk about this with me.
There's some board seats I have that are...
the founder's asking quite a lot less than some seeds, or there's no board seed.
And they're sort of decoupled.
Yeah, exactly.
So I feel like we need to be very clear.
A board is to keep everybody out of jail and to do the right thing for the shareholders.
And the actual work requirements of that are relatively little.
That's actually not the hard thing, but we use it as a proxy for the hard thing.
The hard thing is how do you add a lot of value?
And for that, I do think, listen, you have to, in my case...
Listen, I have the pleasure of working with the best team I've ever worked with in my life.
They're fucking amazing.
We've got a phenomenal platform.
It's fucking amazing.
And I get to leverage all of that.
And it's not a board thing.
It's like the help the company type thing.
And I just think this is like the new era of VC.
You help these companies with more than just one person who shows up off the golf field every Thursday.
Yeah.
Well, that's a great place to leave it.
Martin, thanks a lot for making time for this.
I really enjoyed it.
It's a pleasure.
That was great.
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