idea of the superpowered individual uh
where if if I'm a coder like you know I
mean step one is like I need to make
sure that I really understand AI coding
and like what that means and what how
coding is going to change in the future
you know that that I need to you know
specifically how to go from being a
coder who writes code entirely by hand
to being a coder who you know
orchestrates you know a dozen instances
of of you know coding bots you know you
know there's there's a change in the
actual job of coding itself which is
which is happening right now but the
other part of it is okay how do I become
that superpowered individual how how do
become a coder that also then harnesses
AI so that I can also be a great product
manager and I I can also be a great
designer, right? And then the same thing
for the product manager which is how do
I make sure that I can now use coding
tools? How do I make sure I can also you
know do AI AI based design? And the same
thing for the designer which is how do I
use AI to be also become a coder and
also become a product manager. And then
what you get is maybe the maybe the
those individual roles change like maybe
those are not anymore sort of stovepipe
roles the way that you know they have
been for the last 30 years or whatever.
Uh but what happens is the the talented
people in any of those roles become
superpowered and they become good at
doing all three of those things. Um and
then and then those people become
incredibly valuable because then those
are people who can actually like you
know build and design right new products
right from scratch which is like the you
know which is which is the most valuable
thing. And so I I think I think that's I
think I think that's the opportunity.
>> So I love this answer. So what I'm
hearing is essentially uh if you're
amazing at any of these three roles you
will do well. Number one, if you're
amazing at these roles, that's great.
But also, you part of being amazing in
these roles is also being being able to
fully harness the new technology, right?
So, if you're if you're a master coder
today and you you don't ever get to the
point where you you figure out how to
use AI to leverage your coding skills,
you know, and and do more, right? Like
at some point, you are going to hit an
issue, right? Here's another way
economists talk about this, which is
there's the concept of the job, but the
job is not actually the atomic unit of
what happens in the workplace. The
atomic unit of what happens in the
workplace is the task. And so and and
then what what the way the economists
think about it is a job is a bundle of
tasks. And everybody wants to talk about
job loss, but really what you want to
look at is is task task loss, right?
Tasks changing. I mean the the the the
classic the classic example of task
changing. Classic example of task
changing was once upon a time executives
never used typewriters or personal
computers themselves, right? You know,
if you were a vice president of a
company in 1970 or whatever, you did not
have like a typewriter or a computer on
your desk typing things. You had a
secretary who you dictated memos to,
right? And then there and then there was
this change where like emails started to
show up. And what would happen was the
job of the secretary then went from, you
know, it went from, you know, the the
job of the secretary changed from
sending out letters with stamps on them
to like sending or receiving emails with
the other admins. And then and then that
the secretary would print out the email
and bring it into the executive's
office. And the executive office would
read the email and paper, scroll scroll
the reply. um and and and and give and
give that message back to the secretary
who would go back and type it into the
computer on on on on his or her desk and
send it as an email. Fast forward to
today, none of that happens. Now
executives just do all their own email.
They still have secretaries or admins,
but they're now doing different tasks.
You know, they're travel planning and
orchestrating events and like doing all
these other things, you know, that that
you know that the great admins do. And
then that and then the task the task set
ironically of the executive has expanded
to do actually more of the clerical work
themselves actually like sit there and
like type their own memos which again 50
years ago they never never would have
done that. And so the executive job
still exists the secretary job still
exists u but the tasks have changed and
and I think that's like a great example
of what's going to happen in coding. The
tasks are going to change it's product
management the tasks are going to
change. designer tasks are going to
change and so the the the job can p the
job persists longer than the individual
tasks and then as the tasks change
enough then that's when the jobs change
and so at the at the level of individual
you kind of want to think of like okay I
have this job the job is a bundle of
tasks I need to be really good at making
sure that I can like swap the tasks out
right I can I can really adapt use the
new technology you know get really good
at AI coding for example um I can you
know and then and then you want to kind
of add skills I can also get really good
at I can also get really good at product
management because I've got this new
tool. So you want to kind of pick up
more and more scope as you do that. And
then you know 10 years from now is your
job title coder or coder designer
product manager or is it just I build
products or is it just I tell the AI how
to build products? It's like whatever
that whatever that job is called who
even knows what it's going to be but
it's going to be incredibly important
because the people doing that job are
going to be orchestrating the AI. And so
that that that's the track that the best
people are going to be on. Um, and and I
think that that's the thing to lean hard
lean heart into.
>> I think people aren't fully grasping
just specifically software engineering
and how much that is changing. Like it's
pretty clear we're going to be in a
world soon where engineers are not
actually writing code which I think a
year ago we would not have thought and
now it's just clearly this is where it's
heading. It's like there's going to be
this artisal experience of sitting there
writing code which is so crazy how much
that job is going to change.
>> Yeah. So again here I go back and again
pardon maybe the history lesson but like
I go back like coding. So the first you
may know that do you know that the
original definition of the of the term
calculator? Do you know what that
referred to?
>> No.
>> It referred to people.
Right. So back there were like
electronic calculators or computers or
any of these things. um the way that you
would actually do computing, the way
that you would do calculating like the
way that insurance company would
calculate actuarial tables or the
military would like calculate you know I
don't know whatever troop logistics you
formulas or whatever it was the way that
you would do it is you would actually
have a room full of people um and by the
way these like big rooms you could have
hundreds or thousands or tens of
thousands of people doing this and you
would actually you would actually figure
out you have somebody at the head of the
room who was like responsible for like
whatever the mathematical equation was
and then they would parcel out the
individual mathematical calculations to
people sitting at desks who were doing
them all by hand, right? And and those
that that that job title was those
people were calculators, right? Um and
so we've gone from a world in which you
literally have people doing mathematical
equations by hands by hand. Then we got
the first computers. The first computers
of course didn't have programming
languages, right? They they only had
machine code, right? So the first
computers were programmed with ones and
zeros. And so the task of the programmer
became do the ones and zeros. And then
that became punch cards. And you can
still, you know, there's still people,
you know, kicking, you know, today who,
you know, whose job as a programmer was
to like deal with the punch cards. And
then you got actually this big
breakthrough which was called assembly
language, which was basically the way to
do machine code, but like with some
level of like English kind of added to
it. And then the best programmers did
assembly language. And then, you know,
when I was coming up, it was higher
level languages like C that compiled
into machine code. And that's what
programmers did. And then I still
remember when when scripting, you know,
when scripting languages, you know, we
developed JavaScript at Netscape and
then, you know, Python took off and
Pearl and these other scripting
languages. When scripting languages, you
know, took off in the in the in the in
the in the 2000s, there's this big fight
in the technical community, which is is
scripting real programming or not,
right? Because it's it's like it's kind
of cheating, right? Because real
programmers write code that compiles to
machine code and like real programmers
like do like memory management
themselves and they do all you know this
this this whole craft of writing writing
uh you know writing writing C code and
you know these these JavaScript or
Python programmers are just doing this
kind of lightweight thing and does it
even really count as as coding and of
course the answer is yes it very much
counted and now most coding is done with
the scripting languages right um which
have you see my point the scripting
languages have abstracted away like five
layers of detail underneath that that
people used to do by hand and they don't
anymore and then and then there's and to
your point like AI coding is the next
layer on that AI coding actually
abstracts away the process of actually
writing the scripting code right and so
in one sense this is a really big deal
for all the obvious reasons but on the
other hand it's like okay this is the
next layer of the task redefinition
under the job of programmer right now
what's the job of the programmer it's to
your point it's not necessarily to write
the code by hand but what it is now is
all right now you know if you talk to
the world's best programmers today what
they'll tell you is oh my job is I'm
sitting there and I'm orchestrating 10
code bots, right? Coding bots that are
running in parallel, right? And
literally they sit there and they shift
from browser, you know, browser to
browser or terminal to terminal and
they're and they're they're watch
they're their their day their day job
now is kind of arguing with the AI bots
to try to get them to like write the
right code, right? And then and then
debug it and and fix the problems and
change change the spec and and do all
these things. And so now now the job of
the programmer is to argue with the
coding bots. But like if you don't know
how to write the code yourself, you
don't know how to evaluate what the
coding bots are giving you, right?
Right. And so, you know, you asked about
the 10, you know, our 10-year-old is,
you know, super into computers and super
into programming. And what I'm what I'm
tell, you know, he's he's using Claude
and ChatgPD co-pilot and all these
things. What I'm telling him is like,
look, and by the way, he loves vibe
coding. He's on Replet all the time
doing vibe coding, you know, doing game
doing games, you know, he's sitting
there, you know, it's hysterical, right?
Because he's sitting there, it's a
10-year-old basically who's, you know,
spends two hours at dinner arguing with
an AI for fun, right? Um, right? But but
what I'm telling him is, no, look, you
need to still fully understand and learn
how to write and understand code because
the coding bots are giving you code. If
it doesn't work or if it's not doing
what you expect or it's not fast enough
or whatever, like you need to be able to
understand the results of what the AI is
giving you, right? In in the same way
that somebody who's writing scripting
language code does need to understand
ultimately how the microprocessor works.
Um, and so again, it's it's kind of this
upleveling of capability where you
actually want the depth to be able to go
down and be able to understand what the
thing is actually doing, even if you're
not spending your day actually doing
that by hand. And again, I look at that
and I'm like, okay, now programmers are
going to be 10 times or 100 times or a
thousand times more productive than they
used to be, right? And and that and and
that is overwhelmingly a good thing.
That the the the tasks are definitely
changing. The nature of the job is
changing. Um, but are human beings going
to be involved in like in the coding
process and overseeing the the AI coding
and all that? And and the answer is of
course absolutely 100%. Like no
question.
>> So you're in the camp of still learning
to code. Still a valuable skill.
>> Oh yeah, totally. Well, again, if you
want to be one of these super look look,
if you just want to put your like self
in autopilot and like I can't be
bothered and I'm just going to have AI
write the code and it's going to
generate whatever it does and that's
fine and I'm going to be, you know, I'm
going to be if if the goal is to be a
mediocre coder, then just let the AI do
it. It's fine. The AI is going to be
perfectly good at generating infinite
amounts of mediocre code, no problem.
It's all good. If if if the goal is I
want to be one of the best software
people in the world and I want to build
new software products and technologies
that like really matter then yeah you
100% want to still be you want to go all
the way down you want your skill set to
go all the way down to the assembly to
assembly and machine code you want to
understand every layer of the stack you
want to deeply understand what's
happening at the level of the chip right
and and and the network and so forth by
the way you also really deeply want to
understand how the AI itself works right
because you want to right because if
people who understand how the AI works
are able to they're clearly able to get
more value out of it than somebody
doesn't understand how it works, right?
I mean, you're always more productive if
you know how the machine works, right,
when you use the machine. And so, yeah,
the the super empowered individual on
the other end of this that wants to do
great things with the new technology,
yes, you 100% want to understand this
thing all the way down the stack because
you want to be able to understand what
it's giving you, right? And and and when
something doesn't work or when something
isn't right, you want to be able to
really quickly understand why that is.
Um, by the way, again, this goes back to
education. AI is your best friend at
helping you learn all that, right?
because it's like, oh, I need to
understand, I don't know, like this
isn't fast enough. Um, I need to go I
need to figure out as a coder, I need to
figure out how to do a different
approach to memory management or
something. And you can be like, well,
you know, like I, you know, I
don't quite know how to do that. Okay,
AI, let's spend 10 minutes. Teach me how
to do this, right? Teach me what this
all means, right? So, all of a sudden,
you have this like incredibly
synergistic relationship with the AI
where it's also helping you get better
at the same time as it's doing a lot of
work for you.
>> By the way, I was going to say I was a
big Pearl uh programmer. I was an
engineer for 10 years and that was my my
language of choice.
>> You do you remember I don't know when
you were doing it but do do you remember
at the at least early on do you remember
did you ever did you ever hit this where
like coders were like looking down their
nose at you being like
>> for sure for sure it's like this is so
slow it's not going to scale what are
you what are you spending all your time
on this thing? Yeah,
>> exactly. And of course, you know, and
again, it was sort of this thing where,
you know, they were they were sort of
correct, which is at the beginning it
wasn't, you know, fast enough or
whatever. By the end, they were
definitely wrong, right? Which is it got
much better much faster and, you know,
it swept the world. Uh, you know, most
coding today happens in scripting
languages. And and then, by the way, the
people along along the way, the people
who really understood the scripting
languages and the people who understood
all the lower level systems, they were
the ones who were able to actually make
the scripting languages actually work
really well, right? And so that that was
that was a great example of this kind of
adaptation. And then and then again the
result of that was you know a far higher
number of people writing code with
scripting languages than were ever
writing code with lower level languages.