One thing that's real is that, you know,
every 3 months we make a model that's
smarter than the month than the model we
made before. And indeed, the models are
slowly getting to where they're, you
know, better than most humans at most
things. Maybe at some point better all
humans at than all things. The other
thing I think is real is, you know, the
model is not building itself in the
sense that like I have a specific copy
of the model that's like making a
specific copy of the the, you know, the
the next model. you know, we don't have
our self-replicating, you know, nanobots
or robots or or whatever, but but what
absolutely is happening is that within
Anthropic and elsewhere, we are using
Claude to help build products on top of
Claude and to help train the next Claude
to help serve Claude faster. Um, you
know, six months ago, I I made this
prediction that, you know, in in six
months, 90% of code would be written by
by by AI models. Some people think that
prediction is wrong but within Anthropic
and within a number of companies that we
work with that is absolutely true. Um
now 90 you know
>> so you're saying that 90% of all code at
anthropics being written by the by the
model today
>> on on many teams you know not uniformly
every
>> is that something that you've kind of
provided something kind of
>> something auditable around that or like
shown how that's happened. Yeah, the
teams play an editing and supervisory
role, but you know, Claude can both you
can say write this feature and claude
will do it and then the human kind of
looks over the code or asks for help
from another another model, another copy
of Claude. Um uh the other thing is
sometimes we have these long running
bugs. You know, when we were training
our our the most recently released
Claude, it was like, you know, the
cluster was broken. There was this bug.
Engineers were spending a few days on
it. And, you know, we just we just went
to Claude and we said, I don't know,
just kind of play around with the
cluster and see if you can figure out
what's wrong. And, you know, Claude
found this just super obscure bug that
the engineers had missed. So, this this
was one area where it was like Claude is
like having a very talented teammate. So
if claude is now running writing 90% of
all of the code in enthropic do you need
less engineers if 90% of all the code
when will it be 95% or 99%.
>> Yeah. So you know I I you know I think
people can misinterpret it as you know
you know like Claude writing 90% of the
code means we're firing 90% of the
software engineers. But you know if
you're familiar with the principle of
>> well you have made some very aggressive
comments around firing executives
>> that that so
um
>> I just want to put two and two together
to get four. Okay.
>> Um uh so uh um you know if
>> one thing I've learned in knowing you
for so long is I have to come back and
kind of like get that qualifying
question again. Yes. Because you're go
you know you you're you're going fast.
So trying to I'm trying to keep up with
you and it's amazing but I want to just
make sure I understand exactly what
you're saying.
>> Yes, absolutely. Let me let me let me
take them one by one. So um uh you know
under comparative advantage if Claude is
writing 90% of the code what that means
usually is you need just as many
software engineers you might need more
because they can they can then be more
leveraged. they can focus on the 10%
that's editing the code or writing the
10% that's the hardest or supervising a
group of a of AI models. And so what
happens is, you know, you can just end
up being 10 times more productive
because the remaining 10% is is now a
complement to the to the AI system
that's that's getting much better at at
getting much better at what it's
producing. So So
>> it's a rebalancing of the work is what
you're really saying.
>> It's it's not a replacement. It's on a
replacement.