The Return to Building

Name: Personal AI Is the New Personal Computer
Uploaded: 2026-05-08T14:30:06+00:00
Duration: 41 min 29 s
Channel: Y Combinator
Description: Summary and key takeaways on Personal AI Is the New Personal Computer: Summary & Key Takeaways, covering The Return to Building Gary Tan left his investor role

Y Combinator

May 08, 2026

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41 min video

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2 min read

YouTube video ID: 57lDpTwiW6g

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Gary Tan left his investor role to become a builder again, launching a special‑episode project called Gary’s List. The initiative targets the difficulty of accessing algebra resources in San Francisco public schools. Using Claude Code, the team built the system in roughly five days for about $200, replacing months of manual research with a few dollars of API calls.

Evolution of Development Tools

Tan’s tooling journey began with Posterous in 2008, a blogging platform later sold to Twitter for around $20 million. He moved on to Post Haven and now relies on an AI‑driven workflow that shifts from manual line‑by‑line coding to “vibe coding” and fully agentic systems. In this model, plain English instructions written in markdown act as the compiled logic that guides AI agents.

The Token Maxing Philosophy

“Token maxing” treats token spend like rent: it is costly not to allocate enough model capacity. By borrowing extensive machine time, developers become “time billionaires,” allowing AI to boil the ocean—ingesting every available source, cross‑referencing conflicting data, and delivering complete, well‑tested outputs. The approach demands high test coverage, typically 80‑90 %, to avoid sloppy results.

GStack and Workflow

GStack is a repository of AI skills that automate the software development lifecycle. The core skills include:

CEO – defines the overall vision and strategic direction.
Designer – crafts UI/UX concepts.
Developer – writes implementation code.
CodeX – a “200 IQ nearly non‑verbal CTO” that finds bugs and optimizes code.

The human remains the “ADHD CEO,” supplying the “why,” taste, and final QA. Markdown prompts serve as the “harness” that connects user input to the LLM, while CodeX ensures production‑ready quality through rigorous testing.

The Future of Personal AI

Tan likens today’s AI landscape to the Homebrew Computer Club era, describing the current “kit‑car Ferrari” phase where powerful tools are available but require personal maintenance. The choice lies between personal AI sovereignty—owning one’s prompts, data, and models—and surrendering control to corporate‑owned black boxes. Those with technical taste stand to benefit the most from this shift.

Builder Identity

AI restores the “builder” mindset, enabling individuals to ship massive amounts of code despite limited time. Tan reports a 400× increase in code output compared to his 2013 productivity, shipping hundreds of thousands of lines in a few months. The resurgence of the builder identity hinges on leveraging agentic engineering while retaining human strategic oversight.

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nearly non‑verbal CTO” that finds bugs and optimizes code. The human remains the “ADHD CEO,” supplying the “why,” taste, and final QA. Markdown prompts serve as the “harness” that connects user input to the LLM, while CodeX ensures production‑ready quality through rigorous testing. ## The Future of Personal AI Tan likens today’s AI landscape to the Homebrew Computer Club era, describing the current “kit‑car Ferrari” phase where powerful tools are available but require personal maintenance. The choice lies between personal AI sovereignty—owning one’s prompts, data, and models—and surrendering control to corporate‑owned black boxes. Those with technical taste stand to benefit the most from this shift. ## Builder Identity AI restores the “builder” mindset, enabling individuals to ship massive amounts of code despite limited time. Tan reports

400× increase in code output compared to his 2013 productivity, shipping hundreds of thousands of lines in a few months. The resurgence of the builder identity hinges on leveraging agentic engineering while retaining human strategic oversight.

Helpful resources related to this video

If you want to practice or explore the concepts discussed in the video, these commonly used tools may help.

Ergonomic Mechanical Keyboard For Programmers Recommended

Provides tactile feedback and comfort for long coding sessions, essential for builders managing high-volume AI-assisted development workflows.

Amazon →

Ultrawide Curved Computer Monitor For Multitasking

Offers expansive screen real estate to view code, documentation, and agent outputs simultaneously, supporting the 'boil the ocean' research methodology.

Amazon →

High Performance Desktop Computer For Developers

Provides the necessary local compute power to run development environments and manage the 'kit car' AI tools described in the podcast.

Amazon →

Book On Software Testing And Quality Assurance

Deepens understanding of testing methodologies, which is critical for maintaining the 80-90% test coverage recommended for AI-generated code.

Amazon →

Links may be affiliate links. We only include resources that are genuinely relevant to the topic.

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Full Transcript YouTube

I think that's like the defining
question like will you have control over
your own tools or will your tools have
control over you? Using OpenClaw these
days is like driving a Ferrari and it's
like exhilarating. It's insane. Like you
get to do things like it figures things
out you would never think a machine
could figure out and it does it so
quickly. But then it's also like a
Ferrari and that you better be a
mechanic. like it's a Ferrari that will
break down on the side of the road, you
know, when you most need it and you need
to get out with your wrench and pop the
hood and like f fix it, you know, you're
gonna have to fix it yourself. And so
this is a very exciting time in uh
computer science and technology.
Welcome back to a special episode of the
light cone. In this episode, we're going
to talk about how Gary Tan got back to
building. If you follow us on Twitter,
you'll know that after a multi-year
hiatus to become an investor, Gary Tan
is back to being a builder. And in the
last couple months, he shipped hundreds
of thousands of lines of code and built
popular open- source projects that have
gone from nothing to more than 100,000
stars on GitHub. And he did all of this
while having a very demanding job
running YC full-time. A lot of people on
the internet don't even think that this
is possible and are somewhat like in
disbelief, but it actually happened. We
know because we were here to see the
whole thing. And so today we're going to
talk about how he did it.
>> Well, I'm relatively uh shocked myself.
So I'm amazed as well. It was 13 years
of not coding and then suddenly boom,
I'm doing about 400x the amount of work
that I was that year. The last time I
was even sort of like twothirds of the
time writing code. Maybe to start things
off, how about we go back to the project
that started it all off, which was
Gary's list. Oh, yeah. And just like
talk about a few months ago how you
powered up Cloud Code and like started
to get back to coding.
>> It was right after one of the Lyon
episodes, right?
>> Oh yeah, definitely. I realized that I
wanted to bring together all the people
who believed what I believed um
particularly for California. And so I
started a uh 501c4 and now it's a C3 and
a pack which is sort of what a lot of
political groups do. Um it's a very
common way to bring people together. You
know, everyone focuses on the money but
we're trying to bring together smart
people. Um you know what I learned in
the years of working in San Francisco
politics is that bringing together
people is so powerful and uh that's what
a mass social movement is. And I said,
"Okay, well, why don't I just make a
website where we start doing that?" And
it would just start with um why don't I
start writing about the issues that I'm
worried about? It's like I want children
in school. You know, people watching
this from all around the world might
find it very very strange. Like I find
it strange that uh it was not possible
and still very very hard for a seventh
grader or eighth grader in middle school
in San Francisco public schools to be
able to take algebra. And that was, you
know, a math education thing. like you
know if I didn't get to do that when I
was in public schools in the East Bay of
the Bay Area there's no way I would have
studied engineering at Stanford I never
would have written code I never would
have been able to do any of these things
so it was close to my heart and I
realized like hey it's time to write
code and I ended up building Posterous
my first YC startup from 2008
>> what what was Posterous for people who
don't remember it
>> yeah Posterous was dead simple blogs by
email it grew to be a top 200 website on
the internet and then Twitter ended up
buying it for about $20 million. So that
was sort of like my first bag really. I
actually built it again uh as Post Haven
when Twitter um you know bought it for
the amazing people that we had hired and
uh they shut down the startup. It would
have cost a couple million dollars to
buy it back from Twitter and at the time
I had no money in the world. So the next
best thing was why don't I write it
again? And then uh in January of this
year I ended up writing it a third time.
um only, you know, the first time it
took about, you know, $4 million and,
you know, six or seven people and about
a year and a half. And then the second
time it, you know, took about, I don't
know, a h 100red grand and two people,
me and my co-founder Brett Gibson, who
now runs initialized,
um, and maybe like three months or so.
And then in this case it took about $200
which was my Claude Code Max account and
probably five days fullfeatured blog
platform does everything you want and
then on top of that like full rag full
um agentic retrieval like be able to you
know sort of go out and read all of the
internet like every tweet I've ever done
recursive crawl deep research of any
topic. The algebra thing is just one of
a whole lot of different issues that we
really really care about. And to be able
to go ingest the internet, you know, see
all the arguments for and against and
then to craft incredibly detailed um
reports on the back end about um what
are all the quotables like I think
people who are big followers of the
Lyone might remember one of our first
episodes about agentic uh systems with
Jake Heler actually. So Jake created
case text and he described exactly what
I ended up building for basically
journalistic uh long- form articles
about any you know sort of issue or uh
you know piece of news that was
happening. And so you know anyone can go
to gararys.org work today and you know
we do about two or three relatively you
know researched all fully sourced um
articles about what's going on in
California and San Francisco and LA and
like how do we build a better
government.
>> This is the thing I feel like people
missed about Gary's little don't fully
get is that it's like the classic thing
we've been talking about here which is
like software was you build software to
let people use it. So it's like you
build a blogging platform and people
like write blogs and maybe like they
start their own substacks eventually or
they write articles. But Gary's List is
both blogging platform but it actually
does the work of a highquality
investigative journalist. It's not just
something that a journalist uses to
publish their articles.
>> Yeah. I mean basically the for the
equivalent of like5 or $10 of Opus
calls. I mean, I would estimate that it
does the work of like, you know, a real
human being that would have to like go
painstakingly through dozens of
articles, read entire books about
certain subjects, uh, annotate them. I
mean, going back to the case text
example, like the thing that Jake taught
me was that you need to think about what
a human would do with the context given.
Like, what would it retrieve? Like, does
it go to the library? What kind of book
would it look for? what does it search
on for search you know on the web I mean
the great thing now is like you don't
have to just do that like you can get
perplexities API and you can do deep
research there you have X's API you can
do deep research there you know Grock's
API if you need to like do research on X
using the Grock API is actually very
very good and you can just grab all of
the context this is sort of going back
to the philosophy of uh boil the ocean
which is one of my essays it's like
particularly when building agentic
software now You don't have to settle
for um what we did when we were humans
writing the code like and that goes for
research as well. What if you absolutely
boiled the ocean like what is you know
the total completionist like if you were
a human this would take you about a
month to do this research you can just
you know zap the rocks harder. uh you
know you pay more money and you might be
token maxing but you should token max
like basically if there is incremental
work that makes something more complete
more awesome more you know in the case
of um this type of writing like we want
it to be more representative of reality
like you know we don't just settle for
one source when we can get 20 sources
and we can cross reference them we can
figure out like well these 13 sources
say this and the seven sources disagree
with that and then you know you want to
feed all of that context into like your
core prompt and then you can basically
make a better decision than what you
would like just you know a human being
clicking on a link reading a headline
and that's all you understand and I
think if you token max like that's
actually the coolest thing you can do
now and it's not just in you know
generating articles it's not you know
it's clearly in uh writing code right I
think now it's it's going to permeate
every part of society like every thing
that we would call knowledge work could
be token maxed and um I don't think that
it means that we're going to get rid of
people. I think it means that people
need to still supply uh the agency like
I need this like I'm the one who's
sitting here caring about algebra like I
want kids like me who couldn't afford
private school you know San Francisco is
the one city in the world that has the
highest rate of private school
attendance um probably in the entire
country actually and that's not okay
like you shouldn't have to be rich to
have a good education and you know I
don't know why that's controversial and
so for me it's like this you know mass
sort of shift in technology was
happening and then uh I had a need and a
want and a desire and it was a burning
desire like I it hurts me and pains me
to think about 10 12 13year-old kids who
don't know algebra and like could have
but uh some bureaucrat or you know some
virtue signaling person in power says
like actually I don't want that kid who
wants to learn algebra to learn it. So I
think in this process of basically
solving your own pain and need from the
young Gary and building Gary's list, you
sort of discover a lot of patterns on
token maxing and this new way of
building that led you to the next
project which was uh GStack.
>> Like I actually did not plan to make
GStack. All I did was like I uh realized
that I was doing the same things over
and over again and then I got sick of
typing the same thing. So I went into my
Apple notes. I typed in all the things
that I found myself writing over and
over again into Cloud Code and it was
pretty simple stuff. It's like here's
the plan review. One of the things I
started doing is I really love asking
Claude to make asy art diagrams. One of
the things I discovered is um sometimes
Claude would just get confused and like
write bugs or not be complete. But once
I started saying actually before you
start your work make an asky diagram of
all the data flows, all the inputs and
outputs, what are the user flows, what
are the error messages and you can see
this it's like data flow, state
machines, dependency graphs, processing
pipelines, decision trees. Once it did
that, it loaded all of the context in
and then it just did the work more
completely. Like it boiled the ocean
better and it broke down into a bunch of
different sections. Like here's
architecture review, code quality, test.
I mean, one of the things I learned
building Gary's list was that when I was
writing the code myself, I would always
do the minimum amount of testing cuz it
was just like not very fun. I knew I
needed to have it, but I'm here to
write, you know, fun new code. I, you
know, did not like write to write tests.
And then honestly, like I hit all the
things that everyone else hits when they
start vibe coding, which is like this is
slop. It's not working that well. Like
it works fine for the 80% case, but if
any users actually touch it, it starts
falling over. And then that's when I
realized, oh, I can get to 100% test
coverage. I've since learned that 100%
is probably too much. Like hitting 80 to
90% is usually the best practice at this
point. Um, but yeah, this this is
basically the first version of plan-ge-
review. I know, uh, everyone knows the
office hour skill, uh, which is, you
know, what people can use and I still
use when I'm trying to make a brand new
product or a brand new feature. It, uh,
simulates what what we do when we're
working with a company. It's like, how
do you know that people want this? You
know, who's it for? What does it do? And
what's the impact, right? But this is
like the proto skill. Like, this is I
didn't even know skills existed. And I
posted this and it went viral. Like, you
know, 200,000 people saw that. And then
I made another version of it that was a
much more ex uh expansive version. I
called it the mega plan. And then I
ended up um renaming it to the CEO plan.
We've probably talked about metaring
before. I used metaprompting here. I
took the other review plan that we had
and then uh I said, "Okay, well, let's
do a version of this, but like imagine
Brian Chesy sitting with you, right?"
Like Brian Chesy has this great line
about uh what is a 10-star experience.
So and you know the point of it is
everyone thinks about hotels in terms of
like three this is a two three star
experience this is a fourstar experience
and he like goes you know through the
list like five stars. It's like
everyone, you know, yeah, cool. Like,
but he's like, "What's a six-star and
what's a sevenstar and what's an eight
star?" And like he goes all through that
entire list. And um that's one of my
favorite like product and design
exercises to go through like as a mental
exercise. And then the cool thing is
like you can do that every single time
now. And so that's what this is. You
know, this prompt basically tries to
figure out what is the platonic ideal of
uh what this is. These are sort of like
the three the two things that are pretty
awesome. one is uh what is the 10x
check? What is more ambitious and
delivers 10x more value uh for only 2x
the effort,
>> right? And so for whatever reason coming
out of latent spaces helps the model
like really visualize like so I'm plan
CEO skill I actually really enjoy
because I'm an ADHD C CEO and I love um
potential like pure potential and so
this is like the one like I can't
believe this is just literally two
little sentences but like this unlocks
an incredible amount and so that's how
GStack started actually not as you know
I didn't want it to be anything other
than like well I need to make some
skills and I had heard that people were
making like skill repos. But then the
third thing I did was I started um using
these two skills so much that um my
conductor instance was getting very
backed up. So this is how I use
conductor. Uh this is actually my real
setup like
>> so this is your like daily workflow.
This is how you've been shipping
hundreds of thousands of lines of code a
month. It's all it's all in here.
>> Yeah, that's right. So, I dropped like
13 PRs in the last 48 hours and then,
you know, I you just ceue them up. Like
anytime I come up with a new idea, I
come in and uh here it is. You know, I
love using the CEO skill. I loved using
the skill to like really make it super
well tested. I did that all in plan
mode. Uh and then I'd click approve here
and then, you know, Claude would go and
do all the stuff. And then I did that so
much that I ended up having like 15
different features that were all queued
up waiting for me to manually test it.
Like it passed it, you know, it passed
end to end testing, it passed uh
integration, it passed unit tests, but
like at the end of the day, I still need
to, you know, for Gary's list, it's like
pop open the Rails server and like, you
know, load that user and like make it
into that configuration for that
particular user and like manually just
make sure it works. And I got sick of
doing that and I was trying to use um
clawed encode MCP and it was very very
slow two to three seconds for every
turn.
>> I was like this is not usable for QA but
I had heard that Microsoft had released
playright which is sort of um an
alternative testing framework. In
retrospect it's like actually there was
like agent uh there like agent harness
and like all these other like tools that
I could have used. But the upside and
downside of Claude Code is it's so easy
to just start something that I just
popped open like I literally went in
here and this is probably what I did.
It's like I'm so sick of using Claude
Claude in in Chrome MCP. It's too slow.
Let's go ahead and wrap Microsoft's
playright.
Can we do that? And then I just pressed
enter. And then, you know, one of the
things that emerged with GStack is that
like this is how I create new features.
Now, of course, you know, what it's
going to do now is like, "Hey, dude, you
already did that." Which is hilarious.
You know, I have bug fixes right next to
giant features. And then, um, the way
GStack works, there's a CEO, there's a
designer, there's actually a developer
experience person in there. There's a
number of design tools, uh, and then
Plange is the last one. And then I
actually usually run SLCEX. And um I
recently added a slashclaw in codeex.
>> So one of the cool things that I
actually learned from uh YC alums I came
to an event and brain totally frazzled
but you know went to one of our batch
events and we were just you shooting the
 about what was going on with claude
code versus codeex and at the time I was
a total claude code only guy and uh I
realized oh a lot of people actually
prefer codecs. Why is that? And I
discovered that claude code is ideal for
the ADHD CEO, but once in a while
there's a, you know, claude code will
just BS a bunch of stuff. Like claude
models are very very good, but like they
are not the smartest, it turns out. And
so a lot of people, you know, explained
to me that if you have a problem that's
much crazier. You need the 200 IQ nearly
nonverbal CTO. So you can just call in a
friend and then that's what like /codex
is. It's a, you know, GStack skill that
takes whatever plan your plan is or if
you're out of plan mode and you already
implement it, it'll take your repo and
it'll run codeex in a command line
prompt with the prompt that says find
all the problems and all the bugs and it
reports it back to cloud code and then
you and cloud code can work through
those feed that feedback. Uh, and then I
have since added if you use codeex as
your main coding agent, you can actually
go and type slashclaude and have Claude
come and be the CEO briefly if you want
as well. The cool thing about GStack is
when I run it through this program like
I always I do I start with office hours
CEO review like I do design if there's
UI if um I know a developer needs to use
it which is like practically all of
GStack and GBrain stuff I run the
developer review and then I do review
and then codecs once that plan is done
I've worked through all of the issues
the GStack relies very heavily on ask
user question so because you know and
that's that to me is like really
important that's where the human, you
know, vibe coder, operator, agentic
engineer needs to supply their
understanding of what's going on, what
are we building. There's not really a
substitute to that. It would surprise me
very much if someone really truly did
manage to make a thing that could just
make software without the human in the
loop like that. You know, it's
controversial take, I think, but um I
never want to be entirely out of the
loop. I just want the machine to do the
stuff that I don't want to do. And so,
you know, basically QA is a good
examples. And, you know, I mean, that's
hilarious. Coming back to the demo, it's
like I type something into the modern
version of GStack and it's like, dude,
what are you doing? Like, we already
built that. We have browse. Browse is a
longived HP demon with 70 commands as a
CLI. And then QA is just browse. But,
um, in the prompt for QA, it says look
in your context. What did we do on this
branch? if there's UI or any mutation of
data, go and use the browser to test
that thing, which is cool. It's like
having a blackbox browser. It blew my
mind when it first worked. It's like
mini AGI is already here. You know, I
you know, I realize this is not true
AGI. True true AGI would be like I'm not
even here. Um, and actually that's fine
in this respect. Like as a builder, you
know, selfishly, uh, I hope that we
never have to stop.
I hope that the machines never figure it
out cuz that would be really cool. Like
then, you know, humans are really
important and like engineers who know
how to do this, who have taste and
design and product feedback and um you
know, the real customer in mind, like
we're going to be like we basically have
wings for as long as we do. YC Startup
School is back. We're hand selecting the
most promising builders in the world and
flying them out to San Francisco for
July 25th and 26th to discuss the
cutting edge of tech. Apply now for a
spot. Okay, back to the video. I think
you crystallize a lot of these thinking
in this post on X about thin hardness
and fat skills.
>> Oh yes,
>> which actually encompasses all of this
philosophy on how to token max.
>> Yeah. I mean, some of it came out of uh
being trolled on the internet
relentlessly about markdown and like I
you know, I'm just like peddling a
markdown instead of markdown and it's
like, you know, I guess my lived
experience at this point is that
markdown is actually code. It's just
like this compiled in a different way,
but like you can get the computer to do
really astonishing things. Like I mean
even this it's like
>> could we have imagined that I would be
talking to something that has replaced
Visual Studio for like I I don't use
Visual Studio at all. Like there's no
reason to like when I can talk to my
agent and my agent can do this, right?
The article actually the name actually
came from uh our partner Pete Kumin. We
have had to build an internal agent and
you know we call that the harness over
and over again and then at some point
using cloud code all day we realized
like you know why should we rewrite a
version of that over and over again like
you know we should just use the things
that are really awesome as you know
harnesses like a harness is the core
loop that takes the user input gives it
to the LLM runs what the LLM does like
it can do tool calls and things like
that I mean why would we build that like
what we should spending all our time
doing is thinking about what markdown
should there be? And the way to think
about markdown is if you were an event
planner and throwing a wedding and you
were trying to write down a checklist of
how to throw a wedding again, like what
would you what would you write in plain
English to teach the next person who had
to do it what to do? All of that should
be in the markdown. Whereas um all the
things that should you know be
deterministic like um I mean or is is a
real action like a a wedding planner
might have to call like 20 venues right
but you wouldn't use markdown for that
like you would make a you know a call to
Twilio for instance right there's like a
you sort of all of the difficulty in
enantic engineering today is when people
try to do things that should be in
markdown in code and it fails because
code is brittle it doesn't understand
special cases. It actually you know code
literally doesn't understand what you
want or who you are. It is like you know
executing deterministic zeros and ones
in a touring complete loop right like it
doesn't know but then now we have LLMs
that have latent space and they know who
you are and uh it knows what your
motivations are and it can handle
generic cases and then you know a lot of
the the magic right now as an engineer
is like figuring out okay how much of it
is over here in LLM land and how how
much of it is over there in um code
land. And then you know if you combine
that with the other thing I learned
which is like get to 80 to 90% tests
like if it's not tested and you're just
throwing users in there like it's slop
you know 10x worse than like human
written code cuz like you just have no
idea what's going to happen. Um and so
that's like one of the things that
people have to do. It's like all right,
not only do you need to figure out
what's going on in latent space and
deterministic space, you also have to
make sure that like it's, you know, unit
individually tested and then the
integration is tested. And then going
back to uh boil the ocean, like the
machine doesn't care, it'll just do it.
It's amazing. like just zap the rocks
more and you can get to 90% test
coverage and then you can have a system
that you know is not quite perfect like
you know openclaw right now um there are
lots of like failure cases but it's 95%
there you know it's uh I feel like using
openclaw these days is like driving a
Ferrari and it's like exhilarating it's
insane like you get to do things like it
figures things out you would never think
a machine could figure out and it does
it so quickly uh but then it's also like
a Ferrari and that you better be a
mechanic. Like it's a Ferrari that will
break down on the side of the road, you
know, when you most need it and you need
to get out with your wrench and pop the
hood and like fix it. You know, you're
going to have to fix it yourself. And so
this is a very exciting time in uh
computer science and technology cuz it's
like this is Homebrew Computer Club. Uh,
you know, the moment when the Apple 1
came out, like the Apple 1 created by
Steve Jobs and Steve Waznjak was a
breadboard inside like literally a
wooden case hammered together with like
nails and duct tape, you know, and uh if
you wanted a personal computer, that's
what you had to do. And that's where
we're at right now. like you have
relatively, you know, smart technical
and, you know, people who had to study
computer science have to spend like two
or three hours and like maybe like $500
or $1,000 in both tokens and cloud to
actually get something like that
running. But like once you get it, it's
like we're sort of in the kit car
Ferrari phase. It's like then you can
drive and you can go anywhere and you
know you want you want to shout to the
hills like, "Hey, I got a Ferrari." Even
the part about fixing yourself, I feel
people um it's just like one of those
things until you've like pushed through,
you just don't quite get if I really
zoom out, it's almost like things have
moved so quickly. Like if you think way
back, just having Stack Overflow as a
website that you could consult when you
got stuck on a programming problem felt
like amazing. And then it's like like
chat GBT launches like oh now I've got
this like interactive thing that's way
better than Stack Overflow. But you're
still sort of doing the same thing. and
you're like asking questions and you're
copy and pasting code and you're running
the code and seeing what happens and
copy and pasting it back and then you
sort of with clawed code you sort of
push through and you realize you don't
need to do the copy and pasting anymore.
It just like actually like executes and
runs the code and even with open core I
found out when I set it up yeah it's
annoying because it can like effectively
brick itself and it does a bunch of
annoying things. But if you actually
have like clawed code like it'll fix it.
>> Yeah. I just have clawed code running it
will just like fix it and it's clearly
not the way things will be long term.
But there's this like mentality shift of
it doesn't actually matter if it's
brittle and requires fixing because you
can actually just have another agent
like sat there like fixing it all the
time.
>> Yeah, I feel like this evolution I was
like completely clawed code pill uh and
still am but like probably only like 50%
or 60% of my time like building product
um or agentic engineering is in cloud
code now at some point basically
>> almost half of it is through opencloud
now.
>> Yeah. Which is very interesting. I mean
then again I'm also spending a lot most
of my time working on Gbrain itself. So
GBrain came about because I met you
obviously we had Peter on the show. Um
and then I finally got around to it. It
was like one weekend I said I got to
check this out like what's going on with
OpenClaw. Let's get it going. And um
this was about the time Karpathy wrote
his expost about knowledge LLM wikis.
And so I was like, okay, well, I have a
repo full of markdown. All my, you know,
I should put all of my context into that
markdown. And then at some point I
realized, oh shoot, it's just using GP.
>> And GP is not that good. Like it's, you
know, wasting context. It's loading a
lot more into context than it needs to.
And then I sort of fell into a rabbit
hole. I just went into conductor, click
quick start, and then I had GStack built
into conductor already. And you know,
basically this was how I started. I you
know it was actually much more
interesting than that. So uh I didn't
start off from nothing. One of the
things I've learned as you write like a
larger and larger corpus of code is like
you have it loaded in your brain. You're
like oh well in order to build an
agentic newsroom for um Gary's list I
actually had to learn about uh vector
embedding and hybrid RRF and chunking.
like when you're in there trying to make
it work, you're just like very applied.
It's like I have an output that I want.
I want the article to look like this. It
needs to be of this quality. It needs to
have these citations. Like you start
building up uh your you know your tests
and integration tests and like you end
up with like a product that's like
battle tested from like the output that
you want. And so I sort of put two and
two together. And I you know and this is
something that you know anyone can do
actually. It's like this. This is why I
think we're entering the golden age of
open source. Uh I could just open you
know this project in conductor and then
the first thing I write is like you know
go look at you know tilda/garry's
list like look at how we do chunking
embedding uh you know hybrid RF rag like
all of this and then just like extract
it and then I want to use Postgress with
PG vector and like I want a a you know
full rag system for my open claw and
then sort of like one thing led to
another. It's like then I have, you
know, 10 windows and Gbrain and I'm just
like at it. What's cool about OpenClaw,
I mean, maybe this is a good example.
This is actually my open claw. I did go
ahead and ask it's um how, you know, how
did I actually get into it? January
23rd.
>> Also, all your emails.
>> I had a tweet that was like, Claude Code
this week has awakened my 25-year-old
self, the one that checked Red Bulls and
stayed up till dawn coding. We're so
back.
>> The builder identity resurfaces.
>> Yeah. And you know, I'm basically back
to, you know, sleeping 4 hours and, you
know, coding 20 hours a day. You know,
this is also when I started getting
myself into trouble like talking about
lines of code. I still believe this, by
the way.
>> Yeah, this might be like a good quick
aside to talk about like this this idea
of like lines of code being important
measure has been like controversial on
the internet. There's obviously the
counterargument like, oh, lines of code
doesn't like measure developer
productivity, but
>> it doesn't, right? But it also does. So,
It also kind of does, right?
>> Yeah. Like it does. It's clearly And you
know what's interesting is you can
actually um there's wellpublished git
repos out there that you can run to uh
strip away and like standardize what is
actual logical lines of code. And so I
actually did go ahead and do that. Um
you know, and I got into trouble for
saying like, oh, I'm coding at like a
100x uh the rate that I was in 2013. And
then after I did the logical lines of
code strip down um it actually went up.
>> It actually went up. So it turns out
that I was actually doing 400x the
amount of code. But you know obviously I
wasn't writing it. I was directing you
know 15 agents at a time to do so. And
then by the numbers like it was not that
it did like knock down my lines of code
from cloud code a little bit but uh the
surprising thing to me was that it
knocked down the amount of lines of code
that I was writing in 2013 by like 70%.
>> And so I think that that's sort of the
mismatch here. Like people get very
upset because it's easy to like pad the
lines of code if you're a human writing
code. Whereas like unless you direct
claude code to literally like pad the
lines of code, it doesn't necessarily do
that. Like it'll maybe build the wrong
thing. Like you might not steer it very
well. It might not do the right thing.
But like it's not trying to optimize for
lines of code the way a human working a
job would, right? which is you know
that's just life and then I guess the
really surprising thing is if you look
at the literature about software
engineering going back to like 2000 1990
I mean it's pretty clear that the
average number of lines of code that a
professional software engineer that's
like tested and production ready it's
not like a hundred lines of code it's
like 50 it's like 30 like
>> a day
>> yeah a day right like for me it was like
14 but I was like part-time I don't know
it's
So that's where the 400x actually came
from. You know, the other thing I know
is like I should have said that instead
of just trolling people more on the
lines of code. So I, you know, if I
trolled you on the internet, I'm very
sorry for that. Like there, you know,
there is a deeper understanding of this.
And I did end up releasing a blog post
about it that um explains this quite a
bit more. I mean, and I think it's not a
little bit significant. It's very
significant for people who are technical
because it actually raises the bar on
like what you're capable of doing. Like
all the people who are attacking me
about lines of code, they particularly
are the people who are most likely to
get wings if you like let it rip and
token max. This is sort of like the
classic problem. It's like if you have
taste and you understand technology, you
are particularly the people who should
would benefit the most from getting
this. all someone has to do is, you
know, believe, right? So, stop fighting,
just open cloud code and try it. You
know,
>> I think another thing that's potentially
going on is just like the experiences
vary dramatically depending on like the
the models and the harnesses. Um, like
certainly something I've noticed is any
sort of like semi complicated
programming task I try and do through my
openclaw agent just like kind of fails.
like it's exactly the same model and so
like Opus 4.7 as clawed code but it just
like like anything above like a simple
script I just find like it's not like
that great at so I'll go back into like
clawed code and then
>> it was sort of a moment for me where I
realized oh like this is how it used to
feel like this is how like even 6 months
ago it used to feel like oh like you try
and like these things yeah these things
aren't quite there yet and then claude
code with like opus 4.5 was like oh like
it's actually like here
>> it's about to recur. Like right now,
people sort of are feeling like OpenClaw
or Hermes is like not quite there or
it's like a lot of work. And then I
guarantee you like this time next year
like everyone's going to be saying what
you heard here first, which is like
every single person on the planet will
have their own personal AI. We could
either live in a world where we have our
own AI, where we have our own data, our
own integrations, like we see what's
happening, we write our own prompts, and
we have control over what we see. Uh, or
it's corporate controlled. It's
something, you know, you go to a host,
it's kind of like your Facebook feed,
and like you don't know what that, you
know, who wrote that algorithm and who
does it benefit and like what business
model is behind it. Like nobody knows.
the most powerful idea that like was a
gift was the personal computer
revolution and we're about to go through
exactly that same shift with personal AI
and it's going to be a choice like you
know people are going to have to figure
out am I willing to write my own prompts
and you know I think I wish Pete Khan
were here like that's one of the things
we learned from him too it's like unless
you have your own prompts and you can
write it for yourself like you are you
know below the API guideline for some PM
or developer that is not you who like
will not understand you will not
understand your needs will not
understand what you uniquely care about
and I think that's like the defining
question like will you have control over
your own tools or will your tool your
tools have control over you
>> and I think this is the one of the
disconnects that the public has I think
is a lot of uh these capabilities you
have to be on the latest and greatest
models
And it's actually quite expensive to use
them and burn all the tokens for now.
>> It's coming down,
>> but I think maybe people are just trying
like set or the free model or having the
basic claw pro subscription only.
>> Yeah.
>> And part of is maybe we have to address
that this new way of really getting all
this almost ASI AGI moment for for
building is you have to be burning lots
of tokens. the whole token maxing
paradigm.
>> It actually reminds me of rent. San
Francisco rents. Like one of the things
that I feel like we always have to do um
with YC founders is that it's like a
general thing. I was like, "Oh, like I
don't want to move to San Francisco
because it's like so expensive to live
there, but it's like
>> it's so expensive to not live there."
>> Yeah, exactly. That's the whole point,
right? Like early on in a YC batch, like
I'm used to like a fan of being like
like this like this apartment is like
thousands of dollars a month in rent.
Like seems ridiculous. Like should I
like pay it or not? And it's like, no,
you should absolutely pay. And if
anything, you should pay more to not
just be in San Francisco, but be in like
the dog patch and just like be in like
neighborhoods where you create this
serendipity. Like token maxing is going
to be one of those things for founders
that we sort of have to teach them where
it's not immediately obvious that you
shouldn't. This is actually like rent.
Like this is one of the things where you
should like spend as much as you can to
like get the like most utility out of it
versus treating it like the office desk
or something. Like sure you can
economize on that or you don't need like
a super expensive like couch, but like
when it comes to like actually using the
models and your token spend, you should
probably be like pushing pretty hard on
that.
>> Yeah. One of the key maxims for YC is,
you know, how do you find good startup
ideas, live in the future, and build
what's missing, right? And so this is a
profound version of that where all you
have to do is commit your brain to look
at, you know, spending $500 in a single
day on tokens and say actually like, you
know, as long as I'm building something
that's actually of great value to me,
you know, and I'm building the right
thing, uh, I'm going to do that.
>> Gary, I have a weird question. Do you
think that in some ways the fact that
you tried to build all of this while
also being the CEO of Y Cominator
actually helped you because like your
time is so scarce you had to like try to
figure out how to write hundreds of
thousands of lines of code with just
like spare minutes in between meetings
unlike a a full-time software engineer
that could you know just take the time
to like open the website and like click
around to like test it. like those
minutes were like insanely scarce for
you and so you were constantly pushing
yourself to figure out how to like
automate everything.
>> Yeah, I I envy time billionaires, you
know, sometimes look at I mean I'm look
at my kids and it's like these kids are
time billionaires right now, man. Like
you know, you could just like do you
know you we run across people at startup
school all the time and it's like you're
a time billionaire right now. Like this
is incredible. Like you could just do
any you like learn about anything. This
is so great. So yeah, you know,
personally like I think my philosophy is
I am in a crazy rush in my brain. I'm
like probably live 10 billion lifetimes
to live in this body right now and I
need every single moment to count. Uh
and then if you can token max it's like
I mean you could buy millions of years
of consciousness of machine
consciousness. Now I can be a time
billionaire. It's not you know my own
time. It's the time of a machine like
doing work for me and like the human
entities that I care about working on
the causes that I care about, right? I
care about YC. I care about builders
being able to build. Even in a lot of
our internal meetings last year,
remember in our offsites, we would talk
about like how do we teach the next
generation how to use these tools? And
so, you know, I'd like to I wish that I
could say like that was all a part of
the grand plan and that's how it
started. It's not like but you know
subconsciously I actually think it was
like I think subconsciously from doing
Lite Cone and like talking about this
stuff like sitting side by side with uh
Boris Churnney right here was a very
powerful moment for me because I
realized like he's he started saying
things that like I could do myself. It's
like he said our team doesn't write a
single line of code. I'm like oh
actually like I can do that and like the
people who are watching right now it's
like you and I are not different right?
We're the same. Like we started in the
same place. I don't think of myself as
like, you know, in the sky yet. Even
though people seem to talk like I am,
you know, like I'm just a person trying
to do a thing and if I sit next to
Boris, I'm like, you know, this guy is
one of the best engineers I've ever met.
But also like if I just open a prompt,
we have the same prompt. We have the
same MacBook Pro. And you know, there's
nothing that stands between like me or
you or any of us from like drawing on
millions of years potentially of like
tokens to like serve humanity.
>> Well, Gary, I think that was a beautiful
quote that should be retweetable. It's
just
>> got to get it on X right away.
>> You could have infinite time by
borrowing the time from the machines.
>> Yeah, what a time to be alive.
>> That's a beautiful thought to end on.
Thanks Gary for showing us the future.
>> Thanks guys.
>> Thanks Gary.
>> All right, thanks for watching and we'll
see you on the next episode of Lyone.

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Paul Graham, Founder of Y Combinator, Live from Stockholm

Y Combinator

May 13, 2026

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