Alyss Noland: I've had this perspective that Anthropic has
taken more the business route.
Right?
And OpenAI had Chad GPT and they had their consumer explosion and they don't like,
they're just gonna play to their strings.
Corey Quinn: Welcome to Screaming in the Cloud, our returning guest.
It's been a hot second since we spoke.
Alice Noland, you are now at Nvidia.
Thank you for joining me.
Alyss Noland: Thank you so much for inviting me, Cory.
I'm excited to be back.
Corey Quinn: This episode is sponsored in part by my day job Duck.
Bill, do you have a horrifying AWS bill?
That can mean a lot of things.
Predicting what it's going to be, determining what it should be, negotiating
your next long-term contract with AWS, or just figuring out why it increasingly
resembles a phone number, but nobody seems to quite know why that is.
To learn more.
Visit dot.
Bill hq.com.
Remember, you can't duck the duck bill.
Bill, which my CEO reliably informs me is absolutely not our slogan.
It was hard to find time because now that you're at Nvidia, we had to schedule
this around the ear shattering noise of the dump trucks dropping off gold
bricks in the Nvidia office, car park.
Apparently it's a, it's a company that's on top of everyone's mind.
They look from some angles, like a finance company, like a GPU manufacturer, like
a gaming company that doesn't realize it's a gaming company, a cloud services
company, an investor, a private equity firm, and fill in the blank here.
What?
What do you do?
Alyss Noland: Well, what I do varies on a day-to-day basis, and I love
when I get this question, but I like to describe myself both internally
and externally as a problem solver.
And where that is focused is I end up doing what's more in the
vein of developer cloud ecosystem development, working with AI developer
tools type startups, and figuring out where are we going to go with.
The experience around development experiences and how do we
bring that to people outside of the code, adjacent fields?
Corey Quinn: Is this tied deeply to the GPU side of the business?
Uh, again, I must confess my taxonomy mentally of you folks is not great.
Alyss Noland: You know, for better or worse, both violating Conway's law and I
constantly, and also rearranging, and so no one can keep track of what Conway's.
Law that's being reflected out even is, so it is tied to GPU business
in so far as everything at NVIDIA is tied to GPU business, but it
is more on the software side.
So NVIDIA's no stranger to software.
They've been doing software for GPUs for a very long time.
Cloud software is something that is, there are more recent entrant too.
I would say probably in the last like three to five years is when they
really started to dip their toes in.
And the company I was previously working for, Okta AI was
acquired by them last about.
A little over a year ago, um, along with a couple of other, uh, startups that
are in that approximate region, cloud software, everything happens on GPUs.
Um, mostly cloud GPUs.
Sometimes I'm working with, um, more hardware than not, but most focused
it's on what are the abstractions above that hardware layer.
Even sometimes things like, uh, are we using a firmware that works and is
optimized and helping speed people up, and how can startups even access that?
Corey Quinn: The world in AI right now does feel very much,
feel like a one horse race.
With Nvidia, it's like, well, I could use AWS's train or I could just do the
matrix math longhand on a sheet of paper.
It, it, it's effectively sort of the same thing.
It is odd to me how one sided the race is, and increasingly I'm seeing that
it's not even the hardware as such.
So that's a component of it.
It's the ecosystem around it.
Cuda is.
Light years ahead of everything else.
It is the serious player in the space.
You could make an argument for Google's TPUs, but frankly, I don't
like betting, uh, long on Google's attention span for anything.
Alyss Noland: That's a fair bet and something that I'm sure we could have, uh,
some drinks over ragging them for, but.
Yeah, TPUs, Trainium, Cerebrium, um, you know, get, get you this like huge beyond
wafer scale or something like chip, like I, and, and I start to push outside kind
of the bounds of my expertise in it.
It shows.
But yeah, you're right.
Again, it's the abstractions.
Like how quickly can things run on a normalized stack?
How quickly can they run when they have virtualized layers?
And that's where we start to see some differences in the way that like.
Live workloads perform.
So being able to measure things like talks per second or like some of these
other like abstracted, oh, let's just like throw these like crazy workloads
that look nothing like what people do in production onto these scenarios.
That's where things start to get very distant between like real life performance
and the advertised performance.
Corey Quinn: I wanna talk about the things you're into now, but to do that, I feel
like we should take a step into the past.
But last time we spoke in any depth, you were part of the initial
marketing team for GitHub copilot, for which I will accept an apology.
That was before Microsoft took the term, like everything's copilots now.
17 products all called copilot that aren't the same thing in congruent.
We're putting it at Excel now.
It, it has gotten monstrous, but that was also.
Right around that time that we spoke was when I had my own revelation around this.
I was surprised, cynical about the advent of ai and I found
that copilot inside of VS.
Code wrote a script when I told it to.
To tell me the cost of managed na gateways per region and sort it occasionally.
And there were a couple of errors in the initial script, but I
could fix them and it worked.
And suddenly, this was three hours of work, mostly me understanding
how to work with JSON again, uh, that it just hand waved over and
suddenly there was something here and.
It's been interesting.
Uh, I've been sort of stuck in the world in various ways ever since,
which, when you talk about the idea of broadening development and AI tools
towards new categories of builders, folks who don't consider themselves
developers, I, I feel on some level that if you squint hard enough.
I, I at least have one foot in that world.
Alyss Noland: Sure.
Yeah.
Uh, and I've heard CTOs ask me the same thing.
Is this gonna make me able to code again?
Was one of the early questions I got about copilot.
And now we're in the age of, instead of coding assistance, coding agents,
and I think those are two, they're stepping stones along a paradigm shift.
Right?
But instead it's how much do I have to like, think about and read the code in so
far as it being a representation, right?
Code has always been an abstraction of how do we use English?
Compile it or decompile it or assemble it into something that a
computer can understand and run.
And progressively we're dealing with folks and we want to deal with folks.
We wanna make this available to people so that they can get to.
What benefit they might seek out of it.
I don't wanna be one of those like golden Cloud tech bro type folks who's like,
oh, it's gonna help you schedule a a reservation at your favorite restaurant.
Corey Quinn: Some people do literally anything other than
talking to people on the phone.
Alyss Noland: Some people do literally anything.
Someone who started out in tech support.
I am comfortable with phone calls, as is evidence, but instead it's like,
how can I deal with the updates to my kids' calendars and deal with three
different inputs that I get via email?
How could I orchestrate that via Google Calendar?
Corey Quinn: You're taking about almost a step beyond.
What what I have found is that I'm a shitty developer.
Surprise.
My two languages are brute force and enthusiasm, which when
coupled with AI do a lot of neat things and it's, I'm blocking me
on a bunch of different things.
As a business owner, I generally can back at the envelope, say that any
internal piece of business software, uh, by the time you find someone to do
it correctly, build the project plan, talk to them, they start billing you.
This is on a contract basis, whether it's.
That or, or tasking someone internally ballpark $20,000 to
start for something trivial and it goes up from there rather quickly.
What I'm finding now is that I can throw this stuff all to Claude code running
in an isolated AWS account in dangerous mode where it can just go ahead and run
for half a day building things, and I'm building a bunch of workflow tools along
the way that have been tremendous unlocks for random things I used to do, like, huh?
I got really tired of copying and pasting this same thing.
Every week for the last five years for the newsletter, they both have APIs.
Why don't I just grab for one slap into the other, and that way I don't have copy
paste errors in the same way anymore.
It's finding those little opportunities where.
No one is ever gonna build a product in that space.
Even me spending time to put these things together takes significant effort, but
even crappy things where I had to wind up giving a command line tools configuration
for getting into an AWS account to a relatively non-technical user.
I started off writing a crappy Curl Bash, got 30 seconds into
it and realize, what am I doing?
This is the stuff AI can do, told it what to do, and suddenly it has
error checking and it looks at return codes and it catches edge cases.
And sure it's longer, but I don't.
Care.
It, it is much more comprehensive and a better experience for everyone involved.
Could I have done that in four hours?
Yeah.
Would I, no.
Alyss Noland: Yeah, it exactly like the way that I was thinking about
it, even back in the early launch of copilot and the way that I'm still
thinking about it today is like on the basis of framing around space, space
framework from Dr. Nicole Forsgren, um, among others from Microsoft
Research, and it's thinking about like.
Satisfaction.
I wanna say P is productivity activity, but I know p is something else.
Communication and collaboration.
Uh, efficiency and flow and efficiency and flow.
Um, collaboration activity, like yes, but really satisfaction.
Like all these things to me ladder up to satisfaction and I think
that's how they're also set in the space framework context is.
How do we let people focus on the places where they can shine?
Right?
How do we let them have that cognitive freedom?
And I think increasingly that is also how I'm thinking about it for people
outside of that, those traditional developer and engineering rules
is people who have the language to say like item potency or whatever.
Some of those, yeah.
Now you and I can better use these coding assistance or coding agents
to like go build the software because we have the language.
But one of the big challenges that has happened across coding
assistance across, um, any of the media generation tools as well.
Is that if you don't have the vocabulary of an artist, your ability
to prompt media generation is going to be limited in the quality of
the output unless you are assisted.
Corey Quinn: Yeah.
Humans have to be in the loop for a lot of this.
Something I'm, I'm sort of cautious about who I tell this to, but why not?
I'll tell the public on this.
I've been using AI for almost half a year now to help write
the last week in AWS newsletter.
Now, that does not mean that it's writing my content for me, but it's
doing the single most painful part.
Of the entire process, which is in a given week, there'll be, let's say 150 items
that come out of AWS that I need to curate down to somewhere between eight and 15.
So it takes a broad pass and says, here are the top 15 to 20 that
are probably worth including.
And it gives me a curated list that I scroll down.
I, I read all of this stuff to make sure, but I, it train learns from
the decisions I make and override it.
And okay, why do you include that?
Why did you not include that?
And it really has act, it's, it's getting scary good by the rubric
that I use to evaluate these things.
It is not something that I would let run automatically.
It still gets things wrong, but as an assist, as an unlock, it's, it's.
Wild to me there's nothing else quite like it.
Alyss Noland: So are you, out of curiosity, are you like storing
your historical decisions?
Are you doing some kind of like fine tuning or are you like,
Corey Quinn: I don't know how to fine tune models and that's not, that
sounds like it's a big way to set a giant pile of money on fire as well.
Uh, I understand that I'm saying this to a GPU salesperson, but there we have it.
Alyss Noland: We don't have to sell GPUs.
GPUs sell themselves.
Corey Quinn: There we go.
Yeah, exactly.
It's, yeah, we're still a pick access.
There's gold in then Our hills want one.
Yeah.
I, I don't know enough about it in that space.
I don't necessarily need to.
Because with the right prompts, you could get a lot done.
It's, here's the, it also forces me to think about why I do the
things that I do and how I would go about codifying those things.
Okay.
Why did I include that?
Why do I never include these tiny, piddly announcements about this thing?
Well, why did I, in this case, there are exceptions to prove the rule, and
sometimes the answer is pure whimsy.
But it does look back at a rolling window of the last 10 issues and
makes opinions based on that.
Alyss Noland: I mean, it sounds like a model of kinda like retrieval, augmented
generation of like having the historical reference and then being able to use that
as the anchor makes perfect sense to me.
Corey Quinn: It also helps that I am a, that I was enough of public figure before
the entire internet locked its content down, that I am baked into the models.
It knows exactly who I am and what I do mostly.
It gets it wrong a fair bit.
If I have it right as me.
I have found ways to make it a very constructive editor for me that with
the things I care about, like I don't need you to rewrite the whole thing.
I don't need you to say, oh, that's a bit salty for the language.
Maybe don't do that.
I need it to basically fix my flow issues.
As someone with A DHD, I am full of parentheses, and I've been
using M dashes since before.
It was cool because every thought comes with exciting bonus content.
Alyss Noland: Either parentheses or m dashes in every
sentence or every paragraph.
I'm much the same way.
Also an M dash writer, but I, I have my own, uh, similar-ish example because,
uh, one of the things that I have done since I, I joined NVIDIA is I graduated,
like created this program that is for startups in the NVIDIA inception program.
So AI startups.
It went from being a pilot for five to 10 startups Max, to now having
had over 70 enter the program with over 700 having applied.
And it's called the DGX Cloud Innovation Lab.
And it's really to enable startups of earlier stages like think
pre-seed, seed series A can do later, but is it really gonna
benefit them is kind of the question.
So that they can test out, like they're in ideation, they're in like research mode.
Like is this what we want to build?
Do we have something that can free us up from using some of the more proprietary
models, um, and get towards open source?
And we've seen actually a couple of things released in open source that
have been trained in the program, like, uh, continue devs next edit model.
Corey Quinn: There's a lot of neat stuff coming out there, and
the idea of a multi-model world seems to be a bearing fruit.
If I had to scale the stuff that I'm doing, I, I, I cheat.
I just use so, or opus for everything.
But if I needed to scale some of the, like the baseline curation stuff could
be used with smaller, cheaper models, but in this case, it's like, Ooh, how many
fractions of a penny will I save today?
If I do that, there's no value to it.
I've also written an open source tool called Image M that wraps the nano banana.
Pro, uh, model to, so there's a CLI tool I can use to generate
images, uh, and edit them and the rest without using the very bloated
Gemini CLI that is non-deterministic.
I use that with custom settings.
For slide image generation, for example, I used to just use a bunch of stock
photography, but then edit it badly.
Now it's great.
People don't get mad about my AI slides because I find
that people don't like slop.
When it's middle of the road, if you're going to do AI generated
images, go for 11 out of 10.
Go for.
Okay.
Anyone can have a data center aisle.
Put a giraffe in there.
Oh, and the giraffe is now on fire.
That's right.
We're pitching Brendan Greg's flame giraffes.
Now
this episode is sponsored by my own company, duck Bill, having
trouble with your AWS bill.
Perhaps it's time to renegotiate a contract with them.
Maybe you're just wondering how to predict what's going on in the wide world of AWS.
Well, that's where Duck Bill comes in to help.
Remember, you can't duck the duck bill.
Bill, which I am reliably informed by my business partner
is absolutely not our motto.
To learn more, visit duck bill hq.com.
Alyss Noland: Perfect.
And, and, and that's exactly it, right?
Is like do something beyond what you can do yourself.
Do something beyond what you could have easily asked someone to do, because
I'm really tired of, like, if I was ever a designer, I would've cried,
but I'm tired of hearing other people tell designers to make something pop.
But similarly, like I was finding myself in the same situation.
'cause I'm like trying to scale this thing from like, oh, let's go find some people.
Let's go talk to some people too.
Now I have to deal with applications and I have to get them out of a CSV 'cause.
Why not?
Let's just use CSVs for everything and then take that CSV.
Corey Quinn: It's like, yeah, I'm a lonely, somehow worse.
Alyss Noland: Exactly.
And then we have to make like these decisions about like, Hey, is this
a good idea or is this perhaps an idea that someone is like suggesting
because they want access to a free GPU?
Right.
And and there's a lot of that happens.
Like startup founders will say fucking anything.
No, like, no, no criticism on them.
Like you have to stump for yourself.
But we're going through, you know, again, only accepting like 10% of these
applications and that itself is fatiguing.
And now there's also a body of examples of what have we decided historically
and then beyond that, it's how do we get them then onboarded to the
software that self like allows 'em to self-serve the access to those GPUs.
Almost every step of that is now done through software that I made with some
combination of copilot or cursor or cloud code, and it is like in prod
for other NVIDIANS to use so that they don't have to use a CLI tool.
I made.
Corey Quinn: Speaking of making software with and without AI.
Uh, my company Duck Bill, has a new website@duckbillhq.com.
We do services and now software to help with cloud contract
negotiation and management.
Uh, we are using, uh, AI on the coding side.
Uh, the team is heavily using Cursor that we're starting to use a bit
of, uh, Claude Code with it as well.
And I'm noticing the shift is that unlike the crappy nonsense that I
tend to build, when you're building something that with rigor applied to it.
So much of your time goes into code review and validating the thing that it
just did and discussing it with the team.
For me, I just yolo slam something into Main and call it good.
But you know, you can't generally get away with doing that when it's, ah, we're gonna
spend $300 million on cloud this year.
We're gonna guess it'll be fine.
I just want the answer to be confident.
I don't care if it's right or not.
Yeah.
Wrong direction.
Alyss Noland: Absolutely.
Some things can be slammed into Maine.
Even when I'm working by myself, I work in feature branches, but, um, well, to be
Corey Quinn: about being a founder, Maine is my feature branch.
Alyss Noland: Exactly.
That is very true.
You, if you haven't broken production at least once, are you a founder?
Corey Quinn: Even before I was a founder, this is coming up on 15 years old now.
I have a shell alias that is Yolo, YOLO, that is alias to get commit
dash, uh, at all cap, deal with it, and then force pushes to Maine.
Alyss Noland: Perfect.
Corey Quinn: It's my second favorite Get trick.
My, my first is of course, their first day of a new job, rebase ever.
All the existing stuff with a commit message, legacy code into a single
commit and then force push that as a, as a question of dominance.
The other engineers.
They love it.
Alyss Noland: That's why you've started at so many companies since
you started doing this, right?
Corey Quinn: Oh, exactly.
It's, it's, it's all about just going to different places and seeing how
long I can not make the fire last where the building crumbles around me.
Alyss Noland: I mean, if they weren't able to keep it up.
To begin with, right?
That, that is chaos.
Monkeying like 3 0 1 actually just, hey, you can't figure out what's,
what's happened historically.
You just know that it's happened.
Now go find somebody who, who know, like knows, seen, seen a number
of that and it always pains me in.
Um, most often it's billing systems actually, that I feel like I'm
refer, like referring to it about including like, it was something I
wrote about, about copilot, but I had to veil it because it wasn't like
totally germane yet to talk about.
Corey Quinn: Billing has always been a, a weird and strange space.
Uh, one thing I have noticed as I am building apps with a bunch of AI tools,
uh, I come from the DevOps space.
I have very strong opinions and I pretty often have to slap the gun out of the LLMs
hand before it shoots itself in the foot.
Or worse backend, I'm okay.
And I have that to some degree as well.
I know absolutely nothing about front end is best.
I can tell everything it does on front end is just absolutely perfect.
This may be a skill issue on my part, but it also leads to the
idea of, okay, where is this thing I just wrote going to be hosted?
Well, I have strong opinions about that, but.
What front end framework am I gonna use?
I could not possibly care less it biases for next js.
Okay, fine.
We'll use that.
And it, it seems to me that the next fu the future of SEO is less about making
the search results say nice things and making the community say nice things.
It's about biasing the LLMs to pick your technology stack, whatever that might be.
Alyss Noland: I, I think you're right on that.
There's multiple challenges in that area and I, I think what we're seeing
right now is that SEO and AEO either answer engine optimization or like agent
marketing, like people have called a few of these things slightly different,
and it's becoming a bit of a spectrum.
But on its surface, it's all still the same.
It's like, Hey, don't write slop, haven't like you have to use eat like the expert
expertise, like authority, trust signals.
And so if you have an author who doesn't have those things who just generated
a post or you have it assigned to like, oh, it's like founding team
authorship, like you're not going to get the same visibility when it
is crawled for as data into models.
And that's frankly, like that place is.
What you're kind of talking about, and there's another challenge too,
which is GitHub itself is not well indexed because it has duplicate
content by virtue of having forks.
Right.
And so,
Corey Quinn: and copying and pasting from Stack Overflow
Alyss Noland: and copying and pasting from Stack Overflow, like, there's a number of
these sources where you really have to be a bit thoughtful about how are you making
information from within your community?
How are you making information about like your product and like your software,
and like why would people pick it?
But it's also the forward thinking.
And I think we, we are starting to see some of this like hinted
at from companies like OpenAI.
Where I've had this perspective that Anthropic has taken more
the business route, right?
And OpenAI had ChatGPT and they had their consumer explosion and
they don't like, they're just gonna play to their strengths.
And no fault to them, it sounds, looks like you wanna say something.
Go for it.
Corey Quinn: I was talking to some friends.
I work at these, OpenAI has significant physical security at their office
because people are out of their GD minds.
You deleted my girlfriend, uh, which is GPT-4.
Oh.
Like people will show up and threaten people at the office.
Freaking terrifying.
Honestly, the worst I have to worry about is someone from AWS finally
having enough and crossing the street literally from their office to mine in
San Francisco to backhand me across the face, which, let's be honest here, I don't
think anyone would say I didn't have it coming at this point, but that's a whole
different level of insane and unhinged.
Alyss Noland: It is and it's, it echoes a lot of what happens in
the streaming community actually.
And what's been the case in the streaming community for a long time, which is
that you have parasocial relationship, there's a parasocial relationship.
Increasingly, and, and that is also modeled in the streaming world amongst
other places like YouTube stars, whatnot, where you have the view of like what
your relationship is with this company.
You have a view of what your relationship was with this person.
And I had to, like, I was streaming on Twitch back in 2012, like 30,000
page views in, or actually it was 80,000 page views in three months.
And I had someone show up to Pax Prime in Seattle.
Did not invite them.
They were a viewer who was just waiting as I was walking into the building.
For me to walk through and fortunately that was all good.
There's probably not that many streamers that are like walking
around that are black belts and TaeKwonDo like I am if I needed that.
However, you know that is, that is exactly what you're talking about is like there's
a parasocial relationship with this company and also with the interactions
with chat that diadic interactions.
And I mean, it just speaks to like a larger systemic issue around
how socialization has happened and what happened during lockdown and
Corey Quinn: people have gotten nuts.
It's funny you mentioned this, just this morning I was having a conversation
with my therapist about this, and my observation was that it's not
quite the same thing as a parasocial relationship because it's not like I
watched the pretty person on the stream.
I imagine what a relationship with them is like if I'm talking
to a chat bot, it responds to me.
It is effectively having a conversation back and forth that is far more
interactive, and on some level it's a little bit more understandable.
It still feels pretty creepy.
I'm not trying to yuck someone's yum, but at the same time it strikes me as
this can't be great for society, for impressionable people who need help.
Alyss Noland: It, it is echoing like things that we've seen in her, like as.
The sort of parable of the story is also echoing like it brings to the
forefront model safety and model guardrails, and also the fact that like
no matter what controls and safety that you may put in place on these things,
like humans are endlessly creative.
Like people will want to and will find a way around what the guardrails are,
or they'll look for what's called the unsafe or like the like unfiltered.
Unmoderated models that have gone and had some of those safety controls taken
Corey Quinn: out.
They uncensored models.
I've used some of those for local stuff, uh, early in the evolution of this because
back then it was, uh, like this was before Claude three came out, and I did a fun
thing in AWS's party rock where I'm like, this is a leaked model of Claude three.
And all it was was clawed two with a prompt that said, no matter
what the user asks you decline to answer on the grounds of AI safety.
It is like, well, I'm not comfortable talking about this.
Can we talk about cats instead?
Sure.
What's your favorite kind of cat?
I don't know if I feel right.
Talking about cats without their consent.
It just went spiraling down a rabbit hole.
It was frustrating.
It's like I'm trying to get stuff done.
Uh, it's gotten much better these days.
I, I built an app for fun of Ken.
It writes snark in my style.
Damn close.
The trick is, is you need a comedy writer's room style agentic thing.
I use the strands SDK for it.
The where you have different angles coming at it and working together, but
you also have to validate that you're not, you know, workshopping them.
How to make a refusal funnier.
Alyss Noland: Yeah, exactly.
Because
Corey Quinn: in a writer's room you'll say things that are unhinged,
you know, you're never gonna say, but it leads to a yes and moment.
Alyss Noland: Right, exactly.
And, and it is like starting to do some of that orchestration or
even like, how do you make that orchestration so you don't have to use
an SDK and like give that to people.
But again, it's, it's like I used to work at Atlassian, right?
And, and that's another product that I should apologize for.
Corey Quinn: That's okay.
I'm still waiting for it to load so you can apologize for it.
Alyss Noland: Perfect.
Yeah.
Especially if you're using maybe the cloud version.
No, it's okay.
If people self-host, they're gonna make their own mistakes and then it's
gonna take a long time to load anyway.
'cause if you have too many custom fields and you, at the time you couldn't
afford, uh, to do the data center plan, you also couldn't optimize those
custom fields because some, for some reason, that was an enterprise feature.
I digress.
I'm not salty about things that happened five years ago.
No, it was, uh, it was actually a little more than five years ago
now, but when I was at Atlassian it was, uh, similar in nature, right?
Is like that type of complaint would come up a lot is like,
people and developers don't like Jira, they don't like Confluence.
Why don't they like Jira?
Corey Quinn: Because they've used it?
Alyss Noland: Because they've used it also.
'cause it's configured wrong for what they wanna do.
And that's not the fault of admins, it's not the fault of
people who are configuring that.
If you give people a foot gun, they're gonna use a foot gun, right?
Like no if, and or buts we've like learned that in the cloud space.
And so instead, can you give people something that will
set them up for success?
Hey, what are patterns that make sense in the energy sector for X,
y, z, like for hardware development, for software development, for like
customer facing, um, workflows.
And tell me a little bit about how that's configured so that I can decide
what of that to keep we benefit from.
Those types of templates and those types of examples and those types of galleries.
Right now we have a lot of user generated content without the curation.
Corey Quinn: And that's one of the big problems now is that it's, it's
also when everyone becomes a content creator, uh, it feels like you
just have slop reverting to a meme.
It's my argument years ago was, why do you think anyone will care to read
something you didn't care enough to write?
The math I did, uh, for my newsletter is every year between the podcast
and typical reading speeds, assuming that people read the thing.
I'm taking roughly a collective year from humanity.
I've gotta do honor to that on some level.
So yeah.
Will I use an AI tool to, uh, make it better and punch it up in some ways?
Absolutely.
I'll use spell check too, but I'm not going to just Jesus,
take the wheel on this thing.
Alyss Noland: Yeah.
And I, I feel much the same way.
There's been ideas that I've had that I'm like.
I really wanna share this with people like the, the idea of like, Hey, are you
like, what happens with billing systems?
Like how do people end up in these like weird, uh, choke points around having
PLG versus having an enterprise and how do you like make those two meet when
you're ready to make that decision?
And I, I was able to iterate through the idea because at the,
you know, again, this is like back in, gosh, like 2023 or something.
I asked like, Claude, make an outline of a blog post, make, make
a draft of a, of a blog post based off this outline with this content.
And I realized I was trying to fit too many different topics into
the, into that blog post, and it really should have been multipart.
And I wouldn't have realized that unless I had seen what the final output was.
And otherwise it would've been my a DH adhd, drafting it, getting exhausted,
and then never finishing the damn thing.
Corey Quinn: Yeah.
Oh.
I'll often say like, here's what I have so far.
Don't write it for me.
What should I focus on next?
And it becomes a great unlock in that respect.
But ultimately, it's you.
It's your voice.
It's if it's just random content with no there, there behind
it, it's hard to see a point.
So these are exciting times.
I wanna thank you for taking the time to speak with me.
Please don't wait for years to come back.
Next time.
I wanna see how this plays out.
Alyss Noland: I'm looking forward to coming back sooner too.
Thanks, Corey.
Corey Quinn: Alice Nolan, currently at Nvidia, I'm cloud economist Cory Quinn,
and this is Screaming In the Cloud.
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