I think a decade looking back, it'll
it'll be obvious that
intelligence became abundant and that
agency became abundant. Like the current
trends we're on are just going to keep
continuing. And um this will be very
strange. I mean, I think for the history
of humanity, um you know, groups of
smart people getting together towards a
shared goal was was the bottleneck of
progress. You know, US The United States
of America in some sense was an example.
It's like the United States of America
is formed from a smart group of very
smart people getting together and having
a vision for the future that they wanted
to enact. And that's the story of nearly
every company um in America and the
story of every YC company. Um
and
that's going to change. Like all of a
sudden the scarce resource isn't going
to be intelligence or agency. I really
think it's going to be vision and
ambition. It's like, do you have a clear
view of
what you want the world to look like in
the future? What is the like one way in
which you want to put your finger on the
scale for how the future of the world
will develop and how the how the world
will look like in 5 to 10 years that it
does not look like today? And do you
have the ambition and drive to like go
through all the crap to make that
happen? And AI will make that easier.
Like agents and AI makes that maybe 10
times or 100 times easier than it was a
decade ago. But the flip side of that is
then you all of a sudden you can dream
bigger. Like I think And the world is
like
um you know, there's so many things that
need to evolve for us to be able to
fully embrace this technology. Um you
know, the world is like really just, you
know, barely even ready for this
technology today. And I think, you know,
as a builder, we have a responsibility
to prepare the world, right? Like we
have to help enterprises and
governments, you know, to adapt to this
new technology. We have to help figure
out how we secure the world from a
biosecurity perspective or a
cybersecurity perspective. We have to
figure out how we um how we're going to
to manage all these risks that we see
with this new technology. But on the
flip side, it's also the time of like,
you know, unprecedented opportunity for
humans. Like we can develop new
sciences. We can solve problems in
health and biology that have been
forever unsolved. We can build new
businesses that you couldn't have even
imagined before. There's like new
creative opportunities that couldn't
have existed before. So it's like
it's just this incredible cradle of of
opportunity and risks that
I think makes it like no better time to
be someone who's a builder and
has a strong view of how the world
should change.
>> Do you think the path has changed? I
mean, one of the things I saw, I think
Stanford, the amount of computer science
majors actually dropped by some
double-digit percentage. People sort of
worried like, which is sort of insane to
me. Like you still sort of need those
skills to even create agents that are
that good. Maybe that won't be true. I'm
not really sure.
How you know, have you changed you know,
what do you what would you say to people
in this audience right now? Like this is
sort of a real question that people are
sort of facing. Like should they become
more word cell and less shape rotator?
Like what you know, what's the move? And
you
has that changed um
the kind of people you're looking to
hire and you know, how you manage your
teams right now at Meta?
>> I think systematic and rigorous thinking
are still incredibly important because
you know, the abstraction layer, I mean,
I didn't used to believe that this is
how this is going to play out, but it
really has. Like the abstraction layer
just keeps changing. So, you know, when
I started a company, back in my day, we
wrote code. Um
>> [laughter]
>> And now, you know, I'm sure nobody here
writes code anymore. That's ridiculous.
But um but now it's about how do you
orchestrate the agents together? And
then it's like, how do you develop these
organizations of agents? Like how do you
get like a million agents to work
together well? And then it'll be, how do
you get like a trillion agents to work
together well? Like I think that there's
going to be this continued um
uh need to figure out how you structure,
uh, workflows at the abstraction layer
that we're going to be operating at. And
that form of like rigorous systematic
thinking, I mean, traditionally the way
this would work, like in my era of
starting companies, is you would start
by writing code, and then you would have
organizations of humans, and you'd
figure out how you how to organize those
humans. Um, and that requires system
thinking. And now, maybe it's like much
more much closer to first you you work
with the agent, then you figure out how
to organize like these agents, but, um,
but I think systems thinking is never
going to go out of style. So, I think
it's definitely a mistake to go all in
on Word cell. Like, I think you need to
you need to shape rotate. Um, but then I
think the sort of like, um,
much more of I think what's necessary
going in the future is having, um,
a deeper sort of compass and
philosophical view on how the world
should develop. Because I think there
are there are many many lessons, um,
from human history around, um,
how how we think civilization go through
this period, and, um,
so, you know, humanity will change more
in the next decade than it has in the
past 100 years, probably. And, um,
and so, I think like the imperative for
us to have positive visions for that,
and have coherent articulations of how
that should develop are are more
important than ever.
>> Um,
let's get a little more concrete. I
mean, one of the things I'm curious
about is like, are there sort of
applications of AI that you're seeing
among your friends or internal to Meta
that you can talk about that are, you
know, they're sort of obvious near term,
maybe people haven't figured out yet. I
mean, give us some alpha.
>> [laughter]
>> Um, I mean,
I think there's still just like
astronomical opportunity in, uh,
agentic looping, and and figuring out
how you develop systems that enable you
to spend like 1,000 x more or 1 million
x more on tokens to drive an outcome in
a in a continuous feedback loop. Like if
you think about most companies,
companies are just these like
large-scale feedback loops where humans
are operating each of the edges. Like,
you know, companies they
they get customers and they figure out
to make those customers happier. And if
customers are happier, then they spend
more. And if they spend more, then they
can hire more people who can then go
figure out how to get more customers and
make those customers happier. And that's
like this you know, that in some sense
is the feedback loop of
every startup or every business. And you
know, these within that there are micro
feedback loops that exist. And I think
developing agentic systems that can
operate and optimize these feedback
loops is there's like just huge amounts
of alpha there. Like I think we've seen
internally at Meta
cases where if you can develop the right
agentic loop and you have the right eval
or the right metric for the agents to
optimize, you can have a swarm of agents
accomplish more than like a team of 100
engineers in you know,
very very handily actually, very very
easily. And so, I think figuring out
what the world
looks like with lots of
sort of this like
these agentic coordination problems. I
think that is like one of the most
interesting problems today. So,
mechanically speaking, I mean, markdown
files, cron jobs. Is I mean, is it
that's and then basically pointing the
agent at enough data so that it can
figure something out that you know,
maybe isn't in distribution. Yeah, I
think figuring out yeah, yeah,
mechanically figuring out what the
metric is. And yeah, it just comes down
to skills, markdown files, cron jobs.
>> Slash goal.
>> Yeah, slash goal. Like I think I think
it's always funny how
mundane everything is once you really
dig into it. But um
>> So, it's not magic. You know, I mean,
some some people put a lot of magic
There's like some LinkedIn threads out
there about some magic stuff.
>> advice, ignore LinkedIn.
>> Hey.
>> LinkedIn is where you get customers.
>> [laughter]
>> So, uh I like to end on this, which is
um
you know,
you get a telegram to send to the
18-year-old version of yourself. You
know, what do you say to that person
right now, given all, you know, I mean
thank you for coming back and sharing
your wisdom with this audience. I mean,
you know, what would you send in a a
message in a bottle to the 18-year-old
version of yourself right now?
>> Yeah, I think the
I think it really boils down to
develop your own internal compass for
how you think the future will develop
and have strong conviction in it
because, you know, you will get so you
will get inundated with noise and people
telling you and like you'll get be
very confusing and it'll be very hard.
And especially when you're young and you
don't have experience like it can feel
very difficult to
um
have true conviction in what you believe
and and what you want to do. But, I
think that's the most important thing.
Kind of as we talked about, you know, um
it took a deep, deep conviction in what
we were building to be able to weather
the the sort of storms of many years of
um of uh chaos in the market, in the
industry, and the people around us. And
so, um and and the other piece of advice
I would have is try to identify what is
the what is the exponential in the world
that has both the steepest curve and
will go the longest. And, you know, many
decades ago this curve was uh was
Moore's law. And that probably was, you
know, that was yeah, at the time like
clearly the right thing to invest on. I
think right now it's AI progress, but
there will be more of these very steep
curves in the future. And it's fine if
these curves start um you know, the
starting point is very boring or like it
doesn't even seem that interesting. Like
it you know when we started
when I started working on scale, um
you know we had cat detectors in YouTube
videos and that felt, you know,
it's hard to say explain the story that
that's like the most important
technology of our time, but it was on
just this like unbelievable exponential.