Inside Claude Code: How an AI Native Team Actually Works | Cat Wu
By Peter Yang
Summary
## Key takeaways - **Prototype over documentation**: Instead of writing lengthy documents for new features, prioritize prototyping with Claude Code to quickly gauge usefulness and gather user feedback. [00:05], [29:13] - **Treat Claude Code as an eager new grad**: Interact with Claude Code like a junior engineer: provide clear feedback on mistakes, and guide it iteratively rather than expecting perfection on the first try. [29:35], [30:00] - **Invest in your .CloudMD file**: The .CloudMD file acts as memory for Claude Code, serving as an onboarding guide for new hires by detailing architecture, gotchas, and testing preferences. [30:12], [30:38] - **Engineers own features end-to-end**: The Claude Code team empowers engineers with end-to-end ownership, encouraging them to prototype ideas, dogfood them internally for feedback, and then fast-track successful features. [05:05], [06:10] - **Feedback loop every 10 minutes**: With over a thousand internal users opting into a dedicated feedback channel, the team receives high-quality input roughly every 10 minutes, enabling rapid iteration. [00:30], [12:45] - **Designers and PMs can ship code**: Claude Code lowers the barrier for non-engineers, enabling designers and PMs to directly contribute code, significantly impacting user experience without relying solely on documentation. [14:00], [18:47]
Topics Covered
- Great features start with engineer prototypes, not Google Docs.
- High-volume feedback makes prioritization obvious without complex tracking.
- The codebase is the source of truth, not documentation.
- Treat your AI coding agent like an eager new-grad.
- The rarest skill for an AI PM is model intuition.
Full Transcript
We don't use many Google Docs for quad
code. A lot of our best features was
like an engineer prototyping an idea
shipping it to dog fooding, and we just
hear what the feedback is. Like, do
people immediately understand it? Are
people confused? Is it buggy? Or do
people just like love it?
How do you guys think about you?
If you see a change in the Sweet Bench
score, it's not always obvious what
caused the change, and you actually have
to read through these pretty gnarly
transcripts. And a lot of them we get a
new piece of feedback every I want to
say like 10 minutes or so. We love
negative feedback. Like we don't want
platitudes. We want to hear what doesn't
work.
Do you have like a vision doc or
something for clock or like what do you
think the product will look like a year
or two from from now?
A year or two is a really long time. I
can talk about the next few months.
Okay. Welcome everyone. My guest today
is Cat the product lead for clock code.
Uh, Cloud Code is my favorite AI agent.
So, I'm really excited to talk to Cat
about how the team ships so fast, how
she uses cloud code personally to do
product work, and what her vision is for
the product. So, welcome, Cat.
Thank you so much, Peter. Excited to
share more about cloud code with your
audience.
All right. So, um, why don't we start
with the vision story for cloud code and
how you kind of got involved.
Yeah. So um quad code started as a
project that uh Boris was tinkering with
to better understand our APIs and to see
how much of software engineering he
could augment and at the time I was I
was spending 20% time adding RL
environments and I found that cloud code
could make me a lot more efficient at it
and that it was really good at
integrating with all the tools um that
we have internally and So, I was sending
him a bunch of product feedback, um
things that I wanted to change in the
tool, and when we made the decision to
ship it externally, I was so so stoked
to work on it full-time. And since then
it's been pretty widely adopted um
externally as well. And so, we're really
excited to uh, continue to invest in it
make it more featureful, make it work
across heterogeneous developer
environments, and to make it more
accessible.
Awesome. So, so it wasn't like some part
of a grand strategy. It just kind of he
built a little tool that he tinker with
and then he got involved. So, what
happened?
Yeah. Yeah. Exactly. Like he built the
tool and other people on his team
started using it and then the rest of
the org started using it and then it
crossed over into research and then it
actually started to cross over into tech
adjacent roles like data science and
product management and product design.
So, it had a very high viral factor
internally before we launched it. Okay.
So, you know, when I first started
playing with Clockode, I installed in
the terminal and then I was like, what
is is this it? This is the product. And
uh but as I started using it more and
more, I discovered more and more
features and it kind of felt like uh
kind of mastering a video game. It kind
of felt like it doesn't kind of explain
everything to you right off the bat, but
like the more I got into it, the more I
felt like more powerful, like you know
kind of kind of power user. So I I I
guess was this like kind of intentional
and, do, you, and, the, team, have, any, of the
product principles in building this
tool?
The beauty of the terminal is that it
can through the terminal cloud code can
access almost everything a developer can
and this is what makes the onboarding so
smooth to the tool. If you're used to
calling like the GitHub CLI or the data
dog CLI or
literally any CLI tool, you immediately
know that cloud code can do it. And so
this just makes it really fast to get
started. The terminal is also a very
minimalist form factor. So unlike a web
app, you can only use ASI. So you can
only fit as many characters are
available on the screen. You don't have
the option to add any buttons. And as a
result, we've been very
um pragmatic and very almost like brutal
about what features we decide to
showcase and what features we don't
because there's such minimal screen real
estate.
Mhm. As a result of this, the app form
factor is very light and so it means
that you don't get overwhelmed when you
first start, but it also mean but
because we've built it to be very
extensible.
There's a kind of like arbitrary depth
as you get started. Our design
philosophy is to make sure the CLI is
very very simple to on board to. We have
this philosophy that for new features
there should be no onboarding UX. It
should just it should be intuitive
via the feature name via like a oneliner
description what it does
and you should be able to just get
started. And then we also think that the
CLI need to be very extensible because
developer environments are very
different and we want to expose tools so
that every engineer every developer
productivity team can customize it for
their own setup.
Got it. And so that's why we have things
like hooks and custom slash commands and
sub aents and stuff like that.
Okay. So kind of like um do the simple
thing, first., No, no no, like, you, know
crazy onboarding flows and also making
it composable and extensible.
Yeah definitely make it very simple to
get started but able to handle
complexity over time.
Got it. you guys have been have been
shipping a lot like there's new features
coming out all the time and I'm just
wondering how the claw code team
actually works like you know on a given
week like like do the engineers like
basically ship features end to end
themselves and if that's the case then
what's your role as the PM you know how
do how do you guys work
our team is very strong um a lot of very
strong product engineers who love to
have endto-end ownership over features
the the way that things normally work is
there's some like high higher level
design principles that we want to
follow. Like we always want the tool to
be customizable, but within that there's
a lot that you can build. And a lot of
our best features was like an engineer
prototyping an idea, shipping it to dog
fooding, which is so that hundreds at
this point maybe like a thousand
internal employees can try it out. And
we just hear what the feedback is like.
Do people immediately understand it? Are
people confused? Is it buggy? or do
people just like love it? And for the
features that people love, that that's a
really strong signal that we should fast
track it to um sharing it with the
public. And so a lot of the features
that you've seen that we have shipped, a
lot of times we've gone through two or
three iterations of it internally before
we made it public. And there's a lot of
features that we've played around with
internally and just like decided not to
ship. I think as a PM it's tricky to be
a PM for a developer product because at
the end of the day the developer is the
end user and so I see the role of the PM
as one setting like the broader
direction of okay how much how much
customizability do we expose what is
like
what is the minimum bar or what is the
like aspirational bar that we want our
product features to fall between and
shephering it through the process. It
also in the age of AI tools, a lot of
the PM role is around pricing and
packaging as well. So just making sure
that uh developers can focus on making
the best coding experience possible and
then the PM's role is to make sure that
it's accessible for the world.
Okay. So is there like even like a
product review process or you just kind
of they they prototype something and
then it gets traction internally and
then it's like okay let us do it. Is
that how it works?
Yeah. Yeah. For our larger projects
there's a product review process and so
if you if you look back at cloud 4 we've
released ID integrations with VS code
and intelligj. And so for those it was a
very clear decision that we wanted quad
code to meet people where they worked
and have more context about their tools
and so made a decision worked on it for
a few months and then shipped it. But
for smaller features
such as a to-do list or plan mode, these
are ideas that we've talked about
internally. And they didn't require PRD
because the hard thing is actually to
figure out the right form factor. It's
not like an integration challenge. It's
a design the tool the right way with the
right prompt challenge.
Got it.
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Now, back to the episode. I think Boris
tweeted something about, well, not
three, he posted on threads about how he
designed a to-do list, and it was just
like him prototyping clock and trying
different form factors, right? And then
you guys all tried it. Is that how it
went? Yeah.
Yeah. There's a long history for to-do
list. So
Sid actually was the first person on our
team to start experimenting with to-do
list. And the problem he was trying to
solve is we noticed that a lot of people
use quad code to refactor or to rename
variables or these like other larger
tasks. And these tasks often involve
making 20 or 30 changes. and cloud code
would sometimes do the first five and
then forget to do the rest. And so we
were we were trying to figure out how do
we force the model to actually complete
these tasks. And so Sid came up with
this great idea to actually just force
the model to write down its task kind of
like what a human does as they go about
their day. And we were totally blown
away because actually just by forcing
the model to write down its tasks and
reminding it, hey, you can't stop until
the tasks are done, this actually forced
the model to go through and do all 20 or
30 items without any early stopping.
And so this was like bottoms up uh by
SID. And then the to-do list has now
been augmented quite a lot. We've in the
past it was just quad code would write
the to-do list in the transcript and so
you would see it fly past your screen
but it wasn't persistent and then a lot
of people we noticed that a lot of
people were actually just using a to-do
list to track the model's progress and
this is actually this actually meant
that you actually want it to be stickier
like you don't want it to fly off the
screen because otherwise
users who happen to look at the terminal
don't what the agent's working on, they
have to like scroll up a lot. And so the
the new form factor that Boris is
experimenting with was actually showing
like having the to-do be more persistent
so that you can call slashtodo at any
point.
Yeah. Yeah. I I I I use that. Yeah. I
think there's like some some shortcut
key to see it see how it's doing at any
point right?
Yeah. Totally. And we've like
experimented a lot of form factors along
the way that we uh didn't end up
keeping. So things like we have these
like cute little thinking words and at
some point we put the to-do list in
there and then people weren't super
happy with that and so it it's been a
iterative process for sure.
How do you uh when you iterate you you
have you have obviously the you know
anthropic employees that you get
feedback from but do you have a customer
community too or you just look at
Twitter or how do you how do you get
feedback? Yeah
we're very lucky that Anthropic
employees are extremely vocal about
cloud code feedback. So, we have an
internal chat with about a thousand
maybe more anthropic employees who've
opted to join. So, it's not people
aren't in it by default. They've just
decided to join. And we get a new piece
of feedback every I want to say like 10
minutes or so. And it's always really
high, quality., So, we, are, very, very very
lucky that we get such a high volume of
feedback before products even get out
the door. Um once products are shipped
we look at feedback from both our early
enterprise adopters and also
occasionally from Twitter. Um I I think
our enterprise adopters are probably the
highest signal for me right now. There's
about 10 companies that we work very
closely with who are who we tell, hey
just be just be as loud as possible.
Like if you run into any issue, please
put it in the chat. We might not be able
to fix it immediately, but we want to
hear about it. We appreciate it. And
please, please, please share negative
feedback. We're very insistent that we
love negative feedback. Like, we don't
want platitudes. We want to hear what
doesn't work. And thankfully uh these
users are both very engaged with cloud
code and very happy to share what's not
working for them and we've held
ourselves to a pretty fast SLA for
fixing a lot of um a lot of these
issues. So, so for issues that we decide
to prioritize and decide to fix, we'll
turn it around in a week or two.
You know, like in a more traditional
company like the PM has to maintain a
bunch of artifacts, right? Like specs
and road maps and maybe like the vision
dock or something and and uh uh and also
like keep track all the feedback. So, do
you have any of those stuff or like do
do you uh use cloud to summarize all the
feedback or how do you Yeah.
Yes. Um
it's an interesting question. We
actually get so much feedback that
what we should prioritize becomes pretty
clear because you'll hear it 10 times. I
know this isn't a super satisfying
answer. I wish I could just say, "Hey
we like rank, we track every single
thing and we like rank it all."
Yeah. But I think in practice what
happens is we get someone posts a GitHub
issue and they say that something's
broken and then there's like a hundred
thumbs ups on that GitHub issue and then
our sales team DMs us and says hey like
for these three customers this thing is
broken. So normally when a big when
something's a really high priority it's
very very obvious. Um there are a few
ways in which I do use cloud code though
to help me with this. So one is we've
connected cloud code with slack. So it's
really easy to synthesize feedback. So
for example if one customer asks us for
the ability to customize
models by sub agent. I'll just ask cloud
code hey which other customers have
asked for this? That way I know when
it's built we're telling the right
people that we've done it. And then I
also can ask cloud code, hey, like also
look at our GitHub issues and see if
there's any GitHub issues about this.
That way when it's built, we close out
all the GitHub issues. We also use cloud
code to automate as much of this
handling as we can. So for example
cloud code will help us update the docs.
So it'll do a first pass at docs and
then we'll clean up the remaining 10% to
make sure it's very accurate so human
still reviews it. And then we also use
cloud code to dduplicate issues on
GitHub. For a lot of issues, we see five
or more cases of it being filed over and
over again. And so this helps us just
maintain the the backlog and make sure
that our community is kept up state.
You probably have all your documents in
like MD files, right? You don't have any
like Google Docs. If I just have one
there. Yeah
we don't use many Google Docs for quad
code. No. Got it.
Okay.
It's also nice because our codeface is
actually pretty small and so even if
like I think normally people use Google
Docs to document functionality or why we
built something and I think for a lot of
quad code features the why we built it
is sometimes it's just like in the PR
and so if you ask it hey what was the
original inspiration for to-do list? uh
search GitHub, it will be able to just
find the original PR and like tell you
it. And because the code base is small
if you actually want to know exactly how
something's implemented, it's actually a
lot faster and more accurate to ask
cloud code uh while it's in initialized
in that repo rather than read a doc that
um might be out of date.
Yeah, that's a really good point because
the source of truth is the codebase
right? And like you know, this model is
really good at summarizing stuff in the
codebase. So
totally. Yeah. And the code base is
small.
Do you check in code yourself? Like make
some copy tweaks or do you check in
features? Yeah.
Yeah, I do. Um, so I used to do this a
lot more when I first joined as the PM
and there's always like smaller features
that are just faster for me to do than
for someone else on the team to jump in
on. So, like two months ago, we had this
collaboration with Rick Rubin about vibe
coding and he one of the ideas from our
brand team is that we should have a vibe
command that referenced some of Rick
Rubin's writing about the topic. And so
it was just much easier for me to add it
than for someone on the team to add it.
And so, just like take that on. And
we've also seen this with other folks on
our team like Megan who's our amazing
designer. She used to never commit code
which is very normal for a product
designer. And when she started using
quad code more she started making PRs to
console which is the our management um
it's our product for managing API keys
and other API usage and she's also made
PRs to quad code itself and so it
definitely lowers quad code definitely
lowers the barrier for everyone to make
PRs especially for simple changes.
Yeah that that's amazing. I mean like
that that that is a dream, right? To be
able to for designers and PMs to be able
to check in code directly make impact on
the end user experience without just
writing a bunch of Google Docs like
that's a dream.
Yeah, totally. And it also makes it
easier to audit flows too because we
have a lot of branching logic. So, for
example, if you're on a max plan
there's a lot of conditions where we'll
like show you a rate limit warning or
like show you an upgrade message or and
this differs based on every plan that
you might be on whether you're on one pi
or 3P API or cloud for enterprise or
proumer. And so
cloud code also makes it really easy to
audit these flows because you can just
ask it, okay, trace the code for each of
these and tell me exactly what happens.
And then you can
got it.
You can feel pretty good that it's
accurate if um it comes back accurate.
Got it. Okay. Um so probably entire team
talks the clock hole the the most
during the day. Yeah. Um let let me ask
you, let let, me, ask, you, there's, been, a
lot of hot takes about evals recently on
Twitter. Some people say it's like you
have to have like super robust evals
before you launch anything. Some people
are, like, ah, what whatever., like, how, do
you, guys, think, about, eval, and and, and
run stuff before you ship?
Yeah, eval are really hard. Um, so
there's two kinds of evals that we care
about and they're both imperfect and
we're both we're trying to get better at
both. So the first is endtoend evals. So
you can think of this as running sweet
bench on new quadcode harnesses to make
sure that we're not degrading
performance. And so this this is
something that we regularly do both when
we're making large changes to the
harness and when we're testing out new
models.
This isn't that granular. So if you for
example see a change in the SWEBench
score, it's not always obvious what
caused the change and you actually have
to read through these pretty gnarly
transcripts and a lot of them to be able
to figure out themes and what went
wrong.
We want to make this better, but we
don't have a silver bullet right now.
Um, the other kind of eval that we think
is really important to make is
triggering evals. So, what that means is
there's a lot of situations where cloud
code can decide whether or not to use a
tool. And ideally, cloud code can make
these decisions without the human. Um
that that way things just feel more
magical to the human. So for example
uh claw code supports web search and we
want to make sure that web search isn't
overly eager. Like if you ask it a
question, you don't want it to like
search the web 100% of the time.
Yeah.
But you want it to search it if you're
saying, hey, what was the latest like
what was the latest React release and
what new functionality is available
there? And so actually tuning this
triggering is pretty hard to do. And so
th this is a situation where both it's
really straightforward to make an eval
because you know you can clearly
articulate when web search should and
shouldn't happen and then it's also
really easy to grade whether or not web
search did happen.
Got it.
The harder emails are capability ones
like what what kind of capabilities like
give, me, an example., Yeah.
Yeah. So if you want to evaluate, hey
is this harness better at
data science work than the last one
that is actually much harder to test
because you would actually want
something closer to a SWE like setup
where the model has access to a really
big underlying data set, has the ability
to write queries against the data set
iterate on those queries, and you have a
you need to have a gold standard answer
and you need to make sure that there's
no ambiguity in what the right answer
is.
Yeah, got it. Okay. The the web search
one um you just kind of look at the like
maybe look at the past uh when the web
search was triggered and see if it makes
sense or not and maybe have a score or
or something. Is that kind of how it
goes? Yeah.
Yeah. So there's for web search there's
a spectrum of when web search should
never trigger and when it should always
trigger. And so to start, I'd recommend
codifying the black and white areas in
an eval. There is always a gray area and
I would probably just take care of those
afterwards.
Yeah. And and and and I mean the truth
is like you have such an engaged
community that like your your users are
keeping you honest all the time, right?
Like so you can look at some scores but
like your users are just keeping you
honest about what is working and what is
not working.
Yeah, that's true. Yeah. Like even for
to-do list, we spent quite a bit of time
making sure that it was triggering well
because sometimes cloud code would want
to write a to-do list for one item and
then check it off.
And this is a clear case where a to-do
list shouldn't have been used because
you don't really need this form factor
to track getting done one task. Just do
the task.
Got it.
This is a situation where an EVA would
have been really helpful. Like you can
make sure that you can take the
trajectory where the agent um create a
to-do list for one task, put it into
your eval suite, and then make sure that
either the agent doesn't make a to-do
list item or if it does make a to-do
list item that it's like three or five
items.
K, can you tell me some interesting
stories? I mean, you've been on this
journey of CLCO team, right? Is there
any like interesting stories that the
team laughs about? you know, like, you
know, I think I heard a story about you
guys shipping a feature during a me
meeting.
Tell tell me some fun fun stories on the
cloud cloud team.
Yeah.
Yeah. When I think about the team, I
think of just like just people who
absolutely love developers. Um, some of
our some of our favorite memories are
when we first launched. We wanted to
thank our earliest users. And so if
anyone accidentally mentioned the word
swag or stickers while they were using
cloud code, we would send them Sid built
this. We would send them to like a
sticker portal where they could enter
their address and we would actually mail
them a sticker uh a set of stickers and
someone actually reverse engineered the
code or like looked at our source maps
or something and found this
and as a result we got like 500 or so
inquiries where people were like
submitting their addresses and it was
just like a cute little thing that a
cute little Easter egg that we wanted to
embed into the
like for no other reason than to just
like thank our earliest, most engaged
users.
Yeah.
We thought that it would only take an
hour for 12 of us to send 500 stickers
but instead it actually probably took us
eight hours.
Wow. Okay.
And then we just we we were originally
going to make dumplings and we ended up
just ordering takeout and mailing
stickers the whole time.
Wow. Okay. It's probably have to remove
the feature afterwards because you don't
want to be sending stickers all day.
Yeah, we we thankfully did cap it at I
think around 500 or so.
Well, send send me a sticker after this.
I, I I, want, a, sticker., Yeah.
Oh, we have a lot. We've been iterating
on them. Now we have think harder
stickers and Ultra Think and
there's there's a bunch of memes, right?
Like for example, Cloud Cole will will
be like they'll make it make a to-do
list and they'll be like, "Oh, it'll
take it'll take an engineer. It'll take
me like two weeks to do this and I just
d in like 10 minutes.
Yeah,
I've seen that happen before. Yeah.
Yeah. We need to teach it a better sense
of time. I think it's quoting human
hours and then it just doesn't cuz I
think it's only seen human hours on the
internet.
So, um I mean sounds like there's some
pretty good vibes on the team and um I
know you're hiring a PM for the cloud
team. Uh you know, what kind of person
is looking for and what does the
interview process look like? We're
looking for someone who loves
developers, just like loves like ideally
has been a developer before or has
worked on developer tools for a while.
Ideally,
we'd love to have someone who wants to
make sure the SDK, the cloud code SDK is
the best way to build agents. We want to
create more agents in the world and we
think the cloud code SDK is the fastest
way to prototype an agent and bring it
to production. And we're also looking
for someone who wants to grow the
ecosystem. So we've noticed a lot of
developers are customizing their setups.
They're building custom slash commands
and custom hooks and status lines. And
we want to have like a hub where people
can share all of this, where people can
review each other's customizations
where someone can oneclick install it to
their own quad code instance. So I I
would say we're looking for someone
who's both able to steward the SDK as
the best way to build agents and two to
grow the community to make it to make
these customizations easily sharable.
So probably someone who's already pretty
like into cloud code then. Yeah, we're
definitely super power user.
Yeah. Yeah. And do you guys uh maybe for
cloud code or just anthropic in general?
Um is there like a like during interview
process there like hey can can you build
something here or like you know can you
add a fee feature using cloud code or is
there some live demonstrations involved?
Ooh maybe we should do that. We do ask
folks to spend a bit of time in the
products and give a critique of what
they would like to see improved. Okay.
I think normally we can get a pretty
good sense for how engaged someone
really is in the tool uh based on that.
But that would be fun.
Yeah. Or we're or we're looking for
people who are like making tutorials on
YouTube, you know. Just kidding.
Yeah totally.
Yeah. Okay. So, uh let let's kind of
let's do a lightning round. I want to
hear kind of like uh some some tips on
how to get the most out of cloud code
right? And maybe how you use it per
personally.
Yeah. I the three tips I would share are
one demos not docs. Quad code makes it
so easy to make prototypes that if
you're thinking about hey should we
build this feature I I would actually
ask hey is there a way like for quad
code to prototype that feature for you
so that you can get a feel for how
useful it is before writing a multi-page
doc on it. The second thing is I would
treat cloud code as
an eager
new grad software engineer. So I would
think of it as something quad code as a
tool that's very responsive to feedback.
I sometimes see people give quad code a
really ambitious prompt and then when
quad code makes wrong assumptions they
kind of give up. But instead, I would
say if you notice cloud code's doing
something wrong, just tell it that it's
doing it wrong the same way that you
would give feedback to to a human. And
it's really receptive and it'll normally
um change its direction and incorporate
that feedback. And then the third thing
is there's a ton of value in investing
in your CloudMD file. CloudMD is the
equivalent of memory for cloud code.
Every time you start a cloud code
instance, the cloud MD is included in
it. So you can kind of think about it as
edge onboarding. It's everything that
you would tell someone who's new to your
codebase and who you want to be
productive off the bat. So it's great
place to mention the architecture of
your app, any gotchas, how you like to
test and verify work, anything that you
would tell a new hire.
There's kind of like two approaches to
cloud MD, right? You can just type
slashinit and it'll like scan the
codebase for you and add a bunch of
stuff.
But uh I I kind of like how Megan uses
it. She she has like a she's like I'm a
product designer. You got to like
overexlain everything to me. Like it's
kind of like a more per personal like
style kind of cloud MD. Yeah.
Yeah. Yeah. Totally. So the whole system
is very configurable and so you can have
uh a quad MD for the entire repo and
then you can also have your fully
individual cloud MD and in Megan's case
for for a cloud MD that describes who
you are and your role at the company and
that applies to all projects. You can
also have a global personal cloud MD so
that cloud code has this context no
matter what repo it's working in.
Got it. Got it. Okay. And in terms of
the in terms of like the the second tip
that you shared about treating as an
overyear engineer, I I found that like
the more time you do planning actually
the better the results are. So like so
like actually making it write like a
pretty detailed spec about what you want
to build and like looking over it and
then also like asking it to like make a
to-do list and then looking over that.
Totally,
you know, that that's that's been super
helpful for me. Yeah
totally. Our users love plan mode. So
actually,
yeah,
maybe a funny story is we originally
knew that people wanted plan mode
because people kept saying, "Hey, just
like tell me what you're going to do
but don't write code yet." And we kept
being resistant to adding plan mode
because we wanted to teach users to
express what they wanted in natural
language. And when you do express in
natural language, COD will make a plan
for you even outside of plan mode. Over
the course of one or two months, enough
users said that they just wanted to be
really explicit, that they wanted a
shortcut to it that we caved and said
"Okay, okay, we'll we'll add an explicit
plan mode." But we were really hoping
that we could teach users to directly
ask the model to plan. And maybe maybe
in the future when the model is better
at
following these kinds of user
directions, we might we might remove it.
Uh yeah, I mean it's just like the
models these days are just too eager to
code. Like it's like even even in plan
mode when I'm like, "Hey, can you make a
plan for me?" And then it'll make a
plan. They'll be like "Oh, by the way
I can start coding right now. Do you
want to start coding?" Like, "No, stop
coding. I got to review your plan
first."
Yeah. So it's just too eager, I think.
Yeah.
Yeah totally.
Do you have like a vision doc or
something for cloud code or like what do
you think the product will look like a
year or two from from now?
A year or two is a really long time. I
can talk about the next few months. So
we we want to make sure that the CLI
continues to be the most powerful coding
agent and we also want it to be
incredibly customizable so that it can
work in any developer environment. it
can integrate with all your existing
tools and you can and that we create an
ecosystem around the customizations. The
second pillar is we care a lot about
growing the SDK. So in general we would
love for there to be more agents in the
world. not just coding agents but legal
assistants,
EA assist like personal assistant AIS
uh, health health assistant AIs
financial assistance, stuff like this.
And we hope that the cloud code SDK
actually makes it easier for all the
companies building general agents to get
started. And we're seeing the initial
signs of this. There's many companies
that we're working closely with who are
building non-coding agents on the SDK.
We want to make sure these companies are
incredibly successful and and will tell
their stories as their products come to
market.
Yeah.
And the third bucket which is the most
amorphous is bringing cloud code
out of the terminal and making it more
accessible to more audiences. So right
now we primarily target professional
developers. We will continue to focus on
professional developers because that's
the core market of quad code. But
increasingly we find that it adds a lot
of value to tech adjacent folks. So data
science, product management, product
design and we would ideally like a form
factor where uh these folks can get
value too and increasingly to expand
another to expand out by another ring to
folks in marketing, folks on sales who
we think will also benefit.
Yeah. Yeah, cuz like people in anthropic
are all like designers, marketers are
all using this stuff, right? I mean
there's a few we want we want to onboard
more. Right now, it's still really hard
to explain a terminal interface to folks
who haven't used it before, but I think
the core primitives are very general.
So, I'm very excited for the future.
And, doesn't, requ, like like,, you, know,, I
I just did a recording of uh Alex
right, who basically runs his life like
he runs a bunch of tasks using cloud
code. And you don't need to have like
some crazy prompting. You just have to
talk to claw to figure stuff out.
Yeah.
Just like can't do
you just tell it. And if if you're
confused like I recently onboarded one
of one of the folks on our marketing
team onto cloud code and she was like
you know I've never written code before.
I don't even know I I don't know what I
should ask. And I was like okay just ask
it to build an app. And then quadcode
goes with like some purpose and quad
goes off to build an app. She's like
"Okay, I have no idea how to run run
this app." And so I told her like, "Hey
you can just ask Quad Code." And she
did. And I told her how to run it. And
she was like, "Whoa, you mean any
question I have, I can just ask." And
I'm like "Yeah." And it's really cool
because it kind of just works.
Yeah. Yeah. Yeah. And and I I I love how
you guys uh shipped um explanatory style
to kind of like help people become more
technical too as as they're using this
stuff. Um my my one feature request
actually is like to be able to use cloud
code from my phone cuz like like this
this stuff is very agentic, right? Like
it will work for like 10 minutes and I
can just go like play with my kids. So
have some sort of like you know thing
later on the phone would be really
really cool.
Totally. I I agree.
This is also why we built our original
inspiration for hooks is kind of related
to this. A lot of people wanted to get
Slack notifications when Quad Code was
waiting on their response.
Yeah.
So yeah. So Hooks made it customizable.
So, for example,, if, you, wanted, to, get, a
text message every time Quad Code was
waiting on you, you could configure a
hook for that. But I also hear you on
the broader request to run it remotely.
Yeah, I haven't I haven't played with
hooks yet. I still have the list of
features to dive into. But but yeah um
you know I I love how you said like you
know two or three years is too long. You
know you know what's ironic just to
close like I feel like the most
innovative teams like like yours are
just kind of iterating and then some of
the more traditional teams are like oh
we got to have like a three-ear vision
and we got to go there. It's feels like
very
you know that that that's just kind of
the feeling that I get like just just
put yourself out there and like you know
iterate with your users like that's how
you build innovative stuff.
I agree. We're very pragmatic. So
yeah,
we we try to build the products that we
wish we had today.
And because the models are changing so
quickly, we think that it's really hard
to predict more than 6 months in the
future. We think it's really important
to build products for the next
generation of models.
Yeah.
But generation capabilities don't become
obvious until a few months ahead of
time. So I I don't know how people plan
further than that. Yeah. Yeah. Yeah.
Okay. So, like any closing words or
advice for the PMs out there, you know
trying to become AIPMs or like, you
know, any any kind of advice do you
have? Yeah.
The hardest thing to learn about being
an AIPM
is having a really good grasp of what
the models are capable of. There's
it's hard to build evals. At the end of
the day, a lot of it comes down to
intuition. Like if you want to build a
feature, you should probably actually
have a really good sense of intuition
for whether or not the model is capable
of supporting that feature. And if not
how far away is the model? Is the model
80% there and you can prompt the last
20%. Or is the model only 10% of the way
there? In which case, you should
actually probably just check back in in
three months or six months.
Just three months. Yeah. Yeah.
This is the hardest skill and the rarest
skill. And I think you have to have that
curiosity to push the model, right? To
try to make something happen that you
know can't do this or or not. Just try
to make make it work.
Yeah. Yeah. Exactly. Like you have to
know if the model fails, is it because
the context was wrong? Is it because
you're not you're using maybe the wrong
model for the task or is the model at
the core un not capable of it?
Got it. Okay. That that's really good
advice., Yeah., Um, All right., So,, where
can people find you online or do you
want people to Yeah. Where can people
give you feedback? about cloud hub.
Yeah. So, two places either underscore
catw on Twitter or if you have uh
technical feedback, please feel free to
open a GitHub issue and we'll we'll look
into it.
Okay., All right,, Cat,, this, is, awesome., I
I really learned a lot talking to you
and I'll be using Cloud more and more
I'm sure. Thank you for your support and
a as you have more feature requests
please let us
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