I think that, like, the fundamentals of
cryptocurrency, like, it makes sense, and I like it.
But then on top of that little core of truth is
this giant pile of scams and garbage and hype.
Welcome to Screaming in the Cloud, I'm Corey Quinn.
Thrilled to be able to talk with Stephen Barr today.
We've talked many times previously, but this is the first time
we're doing it in public on one of my properties instead of his.
Stephen is the Chief Evangelist over at CloudFix.
Stephen, how are you?
Really well, Corey.
It's great to be here on, like I said, on your
property, talking in an official capacity.
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I've honestly been looking for this for a while,
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I have to say that you and I suffer a similar affliction
in that it is kind of hard to describe what you do.
How do you define yourself as far as the starting, the stopping?
So I like to see it as a facilitating a two way relationship between the,
well, our customers who are interested in cost optimization and then the
engineering and the internals of the company to make sure I can be a trusted
source for developers to go to for the more technical folks within the business
to go to and say, "Hey, does this actually do what we're claiming it to do?"
To be able to talk shop with the developers in our, with our
clients, and then also to make sure to advocate for them.
So I see the evangelism as a two-way street.
It's not just, it's me doing a lot of talking and that goes through
content creation through marketing, that sort of thing, but also
a lot of listening and bringing that back to the rest of the team.
I've always found that cost optimization tends to be a content area that
people care about at very fixed points in time, usually when there's a
burning fire and the rest of the time they could not possibly care less.
So my strategy around it has always been to talk about the, the
greater AWS ecosystem and architectural fun things thereabouts.
I guess make it a point to periodically throw some of
the cost content in to remind people that I exist, and
I found that that's been working for eight years so far.
I almost see it as like, well, like you said, it comes up when there's a fire.
And almost like fitness, right?
You go to your doctor and he's like, "Hey, your cholesterol is way
off," and all of a sudden you're like, "Alright, I'm going to the gym.
I'm getting serious.
I'm going to change my diet," and then, you know, we're human.
We tend to regress.
Three weeks later, we're on the couch eating chips.
Exactly.
And so it has to be this constant pressure, and I want to see myself as being,
in a way, a bit of a constant friendly encouragement, constant pressure.
Say, "Hey, here's something else you can do,"
and then, yeah, "Here's something you can try."
"Have you looked at your EBS volumes?"
Just like you'd have a personal trainer who
is saying, "Let's push it on this exercise.
Let's try and do an extra set this week."
That kind of thing to be that constant pressure.
It's interesting just seeing how difficult it is
to define what we do in the context of what we do.
I like to sometimes say that we're marriage counseling between
engineering and finance, which feels like it is not that far from.
You know, where a lot of these things tend to play.
You don't have a trademark on that phrase, do you?
No, no, I don't.
I'm sure that will come up in conversation.
We have to sit down on the couch here and, and
what are your needs and are you being heard here?
That's definitely the case.
Exactly.
We can talk about insecurities.
It's a safe space.
Trusting.
It'll be great.
So lately, it seems like there have been some shakeups over at AWS.
There are a lot of things going on over at AWS as of late.
I know that they've been chasing a lot of the ML dragons lately.
They've had some significant and notable
departures that I'm not seeing backfilled.
That doesn't mean it's not happening, but it's not happening in the public eye.
My Rolodex, people I know at AWS seems to get slimmer every year.
A Rolodex is a list of contact cards for those of my, uh,
those of the audience who are, you know, younger than we are.
It's funny that those analogies are starting to break a little bit.
The save button is still a floppy disk.
Yeah, I mean, so just at point in time, we've learned about Matt
Wood's departure, and there's no official word on where he's going.
As of this recording.
This is one of those things where just invariably as soon as we say
this and the track is laid down, ten minutes later there'll be an
announcement and it'll be all over the place and we'll sound like fools.
Check the show notes for an asterisk somewhere.
Exactly.
Yeah, but I guess with anyone involved in the generative AI space with that
large of a persona, you probably have a lot of opportunities coming your way.
So that's, that's my speculation, but I don't have
any inside information as to where he's going.
It's always interesting to me watching how senior executives manage transitions
between companies, the way that they talk about it, how they structure it.
Like when you talk about like the Uber executive types, the executive VPs
at giant companies, in many cases they'll do a departure, they'll have
a long handoff period, there will be a farewell tour with a lot of the
clients, they're generally on gardening leave for three-to-six months.
And then it comes out where they're going to go is generally a step up.
The inverse of this is stepping down immediately to spend time with family.
It's like, "Ooh..."
We can read between the lines there.
Yeah.
That sends a message that isn't terrific.
And the fun thing is when companies don't realize that that's the
message it sends and it's a legitimate, I know that's actually
what happened, but no one believes it because of the messaging.
They need to get new PR for them.
Honestly, lately it feels like so much of the AWS corporate comms
apparatus has been aimed at talking about machine learning, and
when you start digging really deep into it, the teams that build
and run the services that we know and depend on are still there.
They're still doing things that are neat and that are going
to be trotted out at reInvent, which is freaking terrific.
The problem is, is that that's not at all what gets talked about.
I mean, yeah, certainly I'm, you know, machine learning AI
optimist, but It has to, it can't take the place, right?
I think the pie should get bigger, right?
It shouldn't redraw the pie.
I really hope reInvent's keynote is not a rehashing of what we
saw at Google Cloud Next earlier this year, wherein the entire
keynote was about AI, and it never pivoted away from that.
The problem I'm seeing when these companies flood the zone like this is that
when there actually is a fascinating and useful breakthrough, that hits from
wherever it happens to come from, we're never going to see it because it'll
just sound like, "No, no, this one is actually transformative and revelatory!"
It's- you've said that for the last five disappointing flops.
So what makes this one different?
And I think that there's a line, right?
And I think that Steve Jobs used to represent
this as this reality distortion field, right?
Where you want to be far enough ahead that it's
optimistic, but not so far ahead that you have lost sight.
They still have to have EC2 instances and databases
and managed services and that sort of thing.
And I've talked to customers, I fix AWS bills.
I see the spend.
There is an awful lot of money in cloud and a surprisingly
small percentage of that is even tangentially related to AI.
Companies have not suddenly given up doing the block and tackle the
things that, you know, generate the revenue and keep people employed.
You're a 50,000 person company.
You're not suddenly going to pivot everyone to AI.
You're just not.
I mean, I guess I could speak for myself personally
and the, you know, the company where I'm at.
I think right now people are doing the similar
things, but they're doing it differently.
Like right now, like whenever I'm trying to do something, I'd spend some time
with, "Okay, how can I do it with AI or using AI or trying to make the scale?"
But it's also the classic programmer trap, right?
Of how do I spend 40 hours to automate this 10 second job?
That's part of it.
I've found that it's useful for certain things and not useful for others.
One area where it excels, obviously, is coding assistance.
That's, that is effectively a superpower.
Every developer I work with these days is using
some form of copilot or something similar.
That is magic.
Doing it, something similar for writing blog posts or whatnot, I find
it helpful, but only because when I, when it spits something out, it
is so bad that I feel the need to dive in and fix almost everything.
So there's like 10 percent of what that originally had that was
there still, by the time I'm done, usefully for me, that's structure.
So great, I've just filled in the content
with things that aren't, you know, inane.
Yeah, I really like the using it to modify and to play
with text and help me rephrase this another way and help
me turn this notes into a more useful general content.
I think starting from zero and saying, "Write me a blog post about cost
optimization," you're going to get out the effort that you put into it.
Oh yeah, but even that is helpful for those of
us who struggle when staring at an empty screen.
Yeah, absolutely.
Well, I guess, so here's a question, especially with the coding assistants,
for young people who are just starting with programming, like, how do
you, I still wonder about that, because you know, I have kids who are
of the age where they can start learning about programming, but like,
is it now worth it to talk about, "Here's how you write a program,"
or should we just focus just on, "Here's how you use an AI assistant."
I mean, because I don't know much about assembly language.
I know the principles, but nothing beyond that.
And is programming, is Python going to be assembly for kids?
I'm taking my guidance from educators, by and large.
Math is a good example of this.
Very often we'll see that, okay, we have calculators everywhere now.
They're in our pocket.
They're ambient in the room around us.
So being able to say, "Okay.
You're not going to have a calculator with you," is ludicrous.
But, I have a second grader who's still learning
math without aid of a calculator because you need to
understand what is reasonable for a calculator to return.
And I feel like there's a similar progression
on this, but it comes down to what is your goal?
Are you trying to be a computer scientist?
Are you trying to get a job as a front end developer?
As your first gig out of school or bootcamp?
Are you just looking for something to keep the lights on 40 hours a week?
What is your goal here?
I've always found that a deeper understanding of fundamentals
is a terrific thing to fall back on when automated things break.
Which they tend to do.
We've all seen ridiculous suggestions from AI, some of them funnier than others.
It's not nearly as funny when it makes it into production.
But there's a strong sense of you, you need
to have a grown up looking at these things.
But senior engineers can see this, sure,
but where do senior engineers come from?
We didn't just emerge from nowhere.
I love how you mentioned math.
Have you read the essay Lockhart's Lament?
Not yet.
Okay.
So it's about this math teacher.
He is terrified that he's talking about, imagine if music was
taught the way math is, and you have to learn all of these scales
and all of these theory before you could ever touch an instrument.
Isn't that how classical piano training works?
Well, the idea is you can just sit down at the piano
and just start playing, try and make some noise.
And you can learn a lot just by playing.
And I feel like with AI, I can play with
programming more freely, but you're right.
You still have to go back and learn the basics.
You still have to go and learn, you know, algorithmic thinking and
data structures to some extent, but being able to play more easily.
And I think a lot of, yeah, a lot of poor math education
is basically like, learn all of this stuff, but you don't
actually just sit there and play with a number, right?
Draw a right triangle and try and, understand the relationships between
the length of the sides or try and figure out why numbers, when you square
them, are always positive or something like that, where you can just
sit there and play and you don't have to, it doesn't have to be formal.
That's how I learned a lot of math.
So much of it was just listening to teachers droning on about
stuff that I already got the first time they explained it, and
I'm just sitting there playing with numbers in a notebook because
this was before the time you could just waste time on your phone.
We could be bored back then, and the exploration that you just
do for the fun and the joy of it is where you learn a lot.
Yeah.
It's being second or third grade and we're doing those, what are those
trigonometry proofs where you have the angle, side, angle, and it
shows that, okay, if you have an angle and a side and an angle, then
this, these two triangles are, what are they called, "congruent?"
I use some argument that we hadn't officially learned yet.
It's like, well, you can't use that because we haven't been taught yet.
But it's true, because if you have this and this, then that has to be true.
Yes, we haven't learned it yet.
I think some of this formalism can kind of beat the joy out of things.
Oh, yeah.
I've, things I love when I find them being
taught formally, become things I hate.
I'm gonna get, I'm gonna get grief for this, I'm sure, but so often
in English classes growing up, they pick some of the worst books,
and you can tell those books are terrible because they won the
Caldecott Medal, and they have the big seal on the front of it, and
it is so heavy with meaning and symbolism that they forgot to tell an
actual story, and it's just, like, I love reading, but this is crap.
If I didn't already love reading, this certainly wouldn't help.
I'm remembering an online English class that I took,
we were all supposed to write a comment on the book.
And I said, "The thing I liked about this book is
it led to one of the best naps I've had this year."
It was so boring and incomprehensible, right?
There was no fun in it.
There was no story.
It was just lots of metaphor and simile and stuff to analyze,
but there's no, there's nothing, there's no substance.
Which brings us back to AI marketing, which is what worries me because
in many cases there is substance behind these things, but it's attenuated
and it's difficult to get to a point where you can see it being useful.
And there's also a lot of defensiveness that factors into this.
People are, in many cases, worried about when, how is this
thing going to take my job away from me as a counterpoint?
I don't see too many jobs accepted at the margins
where that is a realistic possibility in the near term.
So there is time.
If the crypto world is hard to sort out, AI is gonna be so much worse, right?
And like I think that the fundamentals of cryptocurrency, like,
it makes sense and I like it, but then on top of that little
core of truth is this giant pile of scams and garbage and hype.
And so I think with AI, it's gonna be even harder to kind of sort out
what's hype, what is someone just with a cool website and going for venture
capital and taking us off a ride versus, hey, this is a new innovation.
This is a new model.
I think that's going to be harder to sort out.
And that's where we'll hopefully people, I'm trying to
keep myself in the know as much as possible and try to be
able to sort that back to the reference point for that.
You know, it's, I think there's going to come
a future where this is just how computers work.
Like, it just, it's unthinkable to sell a
computer these days without an SSD attached.
It's, similarly, it's going to, oh, of course it's
going to have an AI compatible GPU equivalent.
Whether it can actually display graphics or not is almost beside the point.
Yeah, maybe we've kind of, topped out on what we need in terms of graphics, but
AI, uh, yeah, AI focused processors probably have lots of, lots of room to grow.
For text based LLMs, for the conversational stuff, I'm getting
great results just on my existing Mac hardware, which is not bad.
Terrific when it comes to GPU because that's never been its goal.
But the performance is just fine.
I'm getting in some cases, what, 200 tokens a second?
Yeah, are you using like Ollama or what are you using?
I'm using Ollama with a bunch of obviously submodels under that
where people have, where I've done a lot of, uh, I've done a
lot of playing with some of the custom models, uh, people have
tweaked and done some enhancements on top of Llama itself.
Of course, people playing with Gemini as well, as, or Gemma,
whichever one the, the one that, uh, you can run locally is.
Like, Google's bad at naming things.
Who knew?
Yeah, it, uh, my most capable local machine is, uh, a Mac M2 Max, and
yeah, I use Allama as well, and it is impressive what you can do locally.
Although I do wish I had maxed out the internal storage.
I didn't realize we're going to be downloading these 70 gigabyte blobs.
Yeah, when I wound up building out my Mac Studio M1 Ultra back when the
pandemic was just getting started, it was the first generation of Mac Studio.
I went for the middle of the road processor, and I
wish I'd gotten higher just for the GPU story on that.
Hindsight.
Is it worth paying another $7,000 to correct the mistake?
Eh, not so much.
I was in an Apple store just the other day, and it's like,
I can't think of a reason to upgrade my stuff at the moment.
This is an M1 Max, and then I have an M2 Max Studio, and...
Yeah, I'm on a laptop myself, M1 Max.
It's, it, I got it as a quick laptop in a hurry for reInvent
in 2021, and I haven't felt the need to upgrade it since.
Of course, I also travel exclusively with an iPad
Pro, so I'm probably not the best example of this.
If I need some actual heavy compute, well, that's what the cloud is for.
So, I'm curious as far as, what is your history with AWS?
You've been around the ecosystem an awful lot.
It's fun talking to folks who've been in this back.
We can remember when there were enough services that most
people could hold them all in their head at the same time.
Okay.
This is an interesting one.
So, I was doing a research project with some professors at the UW.
I was an undergraduate at the time, and they were finance professors.
And we were looking at this lending marketplace called Prosper.
And Prosper, it was a peer-to-peer lending platform where someone who
was applying for a loan, say they wanted $5,000 to deal with a plumbing
emergency, and they'd write who they were, and they'd have their standard
loan information, but they'd also provide a writing sample and a photograph.
So you get all the standard loan information, right?
What's their credit score?
What's their debt to income ratio?
That stuff.
But you'd also have their writing and a photograph.
Or several photographs.
And at the time, we had a relatively new service.
This was 2007, I think?
We had Mechanical Turk.
And so I wrote a bunch of Perl scripts for these
professors to put all these images onto Mechanical Turk.
And for those of you who don't know Mechanical Turk, you can
pay one cent or two cents or three cents, and you can get
people to do these little jobs called Human Interface Tasks.
A lot of those jobs are now replaced with image recognition, that sort of thing.
But at the time you'd use it for, you know, looking
for something in an image was a good use of that.
And so we'd ask, is there a dog in the photo?
Is there a puppy?
Is there children?
And try to figure out, did these photos that people were putting
in to their loan applications, did they add extra value in
terms of people estimating probability of repayment, right?
Maybe, uh, the people who put puppies in their loan
photos, are they better loan candidates and why?
These were behavioral finance professors.
And so I spent a lot of my undergraduate, my
last year, writing a mountain of Perl scripts.
I learned about Mechanical Turk.
I actually, I asked my dad.
So my dad, Jeff Barr, Chief Evangelist, AWS.
I asked him, we set up a little meeting with these professors.
And it was all, it was just such a little ecosystem at the time.
It was so fun just how, how small it was.
We wound up building out a lot of stuff in Mechanical Turk in the early days at
Expensify for receipt optical character recognition on that and understanding
what a receipt is, because there's, uh, there's a lot of variety in receipts.
These days, systems are pretty decent at doing that, but,
you know, 2012 when I was there, that wasn't the case.
Mechanical Turk was great for it.
You'd spend fractions of a penny per read on
this or a couple pennies and it would work out.
Yeah, absolutely.
So that was my first exposure to AWS.
Later I was in grad school and I was helping a, another finance professor.
She had written this, she had this really expensive GPU rig, and she had
written this simulation that had run for like three weeks on her desktop,
running the simulation over and over again for different parameters.
And she had submitted this paper to get what is called reviewed by her
peers, and she got really nervous that she wanted to make sure that the
simulation was reproducible, but she only had three or four days to do that.
And her simulation took three weeks to run on her local machine.
And so at that time there were six regions.
And so I maxed out what my account could do, which was a hundred
instances per region, and that was the first time I had written
a program that could spend a substantial amount of money.
And it was really simple architecture.
It was pull from an SQS queue and committing private keys to GitHub.
Yeah, I accidentally helped someone start a Bitcoin farm once.
I don't think that there are too many people from those days who didn't.
I'm so glad that GitHub will detect that now.
That has saved many a person from financial ruin.
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What
I find interesting is that the large scale of company that I tend to
spend most of my time talking to, if there's a breach and someone gets
keys and starts mining Bitcoin, it's a lot harder to detect because,
yeah, my personal bill's what, $50, $70 a month, something like that,
depending on how aggressive I've been with serverless that month.
And yeah, okay, now it's $5,000.
I'm going to notice that or $50,000 or $500,000.
Whereas when you're spending tens of millions of dollars a
month, that starts to really disappear into the background noise.
You gotta be paying a lot of attention to even notice it happens.
Oh gosh, I was working for a company that shall remain
nameless, but they gave every consultant and every person
who needed it the same Root credentials to their AWS account.
Everybody, there's no...
In my early days, someone emailed me theirs, which scared the crap out of me.
And so they had this app that could have run on a Raspberry
Pi, and the spend was like $30,000 a month and growing.
And they didn't know what to shut off and what not to, and it was a, it
was a well funded organization, so they could kind of live with this.
And I think there was some accounting maneuver to subdivide this, but
yeah, it was really terrifying what can happen through these bad practices.
Oh yeah, I care a lot less, to be very transparent, about
the big companies taking the unexpected financial blows.
They can absorb those.
It's the independent learners who are just figuring out how this stuff works.
Maybe they trust the wrong person on Discord or Whatnot and suddenly they're
staring at what they believe to be an insurmountable amount of money.
$700,000, that's more than I'll ever make in the course of my life.
Which is not generally true, but it feels like the world
is ending then, and AWS has never been great at making
people feel reassured while they're looking into that.
I haven't heard too many stories where they
haven't made it right, at least the first time.
But you're twisting in the wind for a week or two first, not knowing.
Yeah, there's that moment where you're
like, "Oh my gosh, what am I going to do?"
And does it even cross your mind?
Okay, do I, if I get on chat, are they going to forgive me if I call up support?
And yeah, like you said they usually let you off the hook unless
you are phenomenally egregious and have done this multiple times.
But if, you know, if they determined that it
was a genuine mistake, they'll look after you.
Yeah.
It can be frightening to get a bill that's, Multiple times your monthly income.
Oh yeah, it's horrifying, and I'm just glad that it seems like
I haven't had seen nearly as many of those stories lately.
I think a change that is absolutely for the better that is in the
process of rolling out is mandating MFA when you spin up an AWS account.
It's- so many other things mandate this, and it's just such a no brainer.
Well, it'll act as a brake on growth.
If someone's not willing to give a phone number for a text message
or use Authy or something like that, then I don't know that you
want them in your cloud environment in the first place, do you?
No, I agree with that.
Use MFA.
That is a good idea, and even the inconveniences that it can
sometimes cause, like, you know, if you're not good with your
backups and you lose your phone, well, yeah, that could hurt.
You're gonna have to go through some, you
know, some manual steps to deal with that.
But the blast radius protection that it gives you
is well worth that, and that's what we always say.
Limit your blast radius, right?
If you have an AWS account, you can turn off people being able
to start GPU instances or the SAP HANA instances, the X ones.
You don't want to accidentally turn one of those on.
I haven't- I confess, I haven't put a lot of those in place for our
internal corporate org, just because everyone who has access to touch
that stuff has multiple years of experience within the AWS universe.
So there's, at some point, we're absolutely going
to have to get some religion around stuff like that.
And we do have segregation of who can look at data, but
at this point, it's assumed that, oh, if you're spinning
up a GPU instance, you probably know what you're doing.
Maybe it's time to revisit that assumption.
Yeah.
I think we have it in our larger org just to make sure.
Okay.
And it's not to stop people, but it's
saying, okay, there's a hurdle because this?
This hurts.
So just make a hurdle in place so that you, if
you're doing this, you know that you're doing it.
Don't- it's principle of least surprise on some
level I think is really where it winds up hitting.
Speaking of surprising people, so when you talk to folks who have been at
big companies, And are being confronted with areas for improvement when it
comes to their, their cloud spend, you and I were talking about this earlier.
It's why I call myself basically marriage
counseling between engineering and finance.
There's a lot more people and behavioral
aspects to this than there are raw math.
The reason that cloud costs are complicated is only
partially due to the fact that arithmetic is hard.
There's a lot more to it than that.
What's your take on it?
I completely agree that many of the issues are people issues, right?
People who might be scared of change, or want to protect territory,
and don't want any- there's a lot of those types of things.
And also, people don't want to look bad, their careers are on the
line, so if you say, "Oh look, we can save you this amount of money."
It's easy for someone to react and say, "Wait, why didn't you do that?
You were my AWS person.
Why do we have to hire these external people who are then
pointing out what you should have been doing in the first place?"
But that's what you don't want is this finger pointing to start happening.
So ideally when people see the savings that can do that, they
have to say, "Okay, I know you were doing the best you can.
We brought in some experts to help you.
And look, there's so much more on the table.
We're really excited.
Now we can do this project and that project."
And you're right.
It's a marriage counseling to kind of help people
see it the second way and not the first way.
The tack that I like to take is I approach it from the perspective
of, look, no one is going to build something successful while trying
to do it for the absolute least amount of money physically possible.
The fact that I'm talking to these people is a sign that they've succeeded
to the point where, okay, now it's time to come in and do some optimization.
I stressed the blameless aspect of it extensively, because even
in my own accounts, I could go through and find significant
savings if I could be bothered to do it, but it's a saying.
"Yes to focusing on that means saying no to something else."
Where do you draw the line?
What is the priority?
Because when everything's the priority, then nothing is.
Where do you want people's energies focused?
Because there's a certain mindset, and I admit I'm one of them, where you can, I
will spend gleefully a month just knocking a few hundred bucks off the AWS bill.
I cost more than that.
So what is the actual value that I'm contributing?
At some point, I, one of my roles is to tell people, "Okay, stop
saving money here, and go back to doing the thing your business does."
That's a really, really good point, right?
There's only- there's diminishing returns to this process.
That's why having to automate what you can, I think we're big believers in that.
So, for example, GP2 to GP3, right?
That should be automatable.
I view them in buckets on some level.
Like the first pass is generally, okay, great.
Click three buttons and you'll save 10 percent.
The next 10 percent is going to require some re engineering work, and
the 10 percent after that is borderline taking hostages in Seattle.
So there's a, it gets harder and harder once the
low hanging fruit gets found and, and sorted out.
But there's also a question, increasing the
enterprise of how you handle governance.
How do you get 15,300 teams all rowing in the same direction?
And that's where it has to be- it's that relational thing, getting the top
down buy in, but then also having the credibility with the engineering teams.
Hey look, we're doing things, this is- we know our stuff.
We're trying to do things that are generally
applicable, and that's the other thing we find.
I'm sure, you know, people in my position, your position, you get to see a
lot of different AWS accounts, and so you can think very generally about them.
Whereas often when you talk to someone at their company, and
they've been there 10 years, and they've nurtured it from the
very first, EC2 instance up to where it is today, it's very
easy to convince yourself that no one else uses AWS like we do.
It's one of those ideas where, you're right, at enterprise
scale, no one is going to use it exactly like you do.
But there are patterns, history rhymes, there are, okay, great,
maybe your naming structure is different, but you're still going
to run into the same foundational problem that other companies are.
I mean, it's like the marriage counseling example again, right?
You're doing this.
And messaging is tricky of this because you can't give it
as a consultant under the tagline, "You're not special."
It does not go well, because who, who wants to be like everyone else?
Yeah, exactly.
But at the end of the day, they said there's patterns,
there's things that you can do that are generally applicable.
And that's what one of, like talking to private equity firms who have a
portfolio of companies, and they want a policy across their companies.
That often resonates a bit better, we found, because they're in
the mindset of thinking at a process level about companies and a
process level about operation, whether than like some idiosyncratic,
here's the one AWS account for this one, I don't know, company.
There's a lot there, but I do want to get to one more topic
before we call it an episode, because you are a Chief Evangelist.
Huzzah!
Talk to me about content creation.
What's your process?
Quick self-promotion.
We have a show, AWS Made Easy.
Myself, my co-host, Rahul Subramaniam try and stream every week.
We interview AWS guests.
We try and cover AWS news.
We rate and review articles, that sort of thing.
I got some really great advice early on, which was get to 20 episodes.
And I heard somewhere that like on the Spotify distribution, most podcasts
are like three or four episodes, and then they just vanish, right?
It's a couple of people, they meet up for a few drinks, do
it in their garage, launch a podcast, they lose momentum.
So my first thing was get to 20 episodes, and then we did that.
So number one is prioritize shipping it over quality.
And I'm sure you've seen that, you know, with video editing,
there is no end to how much you can kind of polish an episode.
I've never touched it.
I've always just handed it off to professionals.
It's the most common piece of advice I give to
people who ask me when they're starting out.
I was like, okay, what microphone, camera, et cetera, should I buy?
Doesn't matter.
You can record something just fine on your smartphone to get you started.
If the content's good, people will forgive an awful lot in production
value, and if your content isn't good and isn't compelling, it
doesn't matter because no one's going to stick around to see it.
It's trash, but it's so well produced, trash doesn't matter.
No one wants to watch trash.
There's an attention economy.
I agree, but also, at some level, you do need to pay attention to that stuff.
And maybe it's just, you know, when your head gets into it, you hear a great
piece of content, but you're like, It sounds like it was recorded in a bathroom.
But maybe that's part of having been in that
content creation space for a while, right?
Maybe I would have never noticed it before, and now I notice.
That's almost how, like, people, audiophiles
say that it kind of ruins music for them.
Because they say, "Oh, it doesn't sound right.
It was recorded on this instead of that."
So in general, try and prioritize shipping.
Try and do the best we can quality wise in
a bounded box of time and money and effort.
And yeah, most importantly, like I said, make it usable, and
try and distill down our experience of, you know, dealing
with a lot of AWS accounts to make it useful for people.
People will be able to submit questions and we try to make shorts and clips.
That's been really nice to be able to give people a small
taste of it because, you know, our episodes are an hour-ish,
and being able to have a 60 second clip that shows, it just
plants a seed and then a link to more, that's been really nice.
It's nice to see people grow, but I think
that people also try to early optimize that.
And the problem is there's no end to it, right?
There's literally no end.
And then as a tech person, right, it's fun to nerd out on the
gear and the stuff and the switchers and the distribution.
And then you have the AI layer, which is, can I automate everything?
And then it takes 30 minutes to get your audio working to join a Zoom call.
I've been there.
Yeah, exactly.
I mean, if I open up my audio devices, it's like nine different things, right?
Because you keep changing your setup.
Okay, sorry, is it this one?
Is it that one?
Is that one?
Oh, wait, I'm on my UMC 404 HD today and not my Blackmagic.
But I think it's with any approach, right?
Try to do the best you can within a bounded level.
And ideally, it's about the listener and adding value for them, and we
always try to ask our listeners for feedback, answer questions when they ask.
Not making it about ourselves, but about remembering
who the audience is and try to add value for them.
I find that you have to write with someone in mind.
Otherwise there's, you're just speaking in generalities and it doesn't help.
Yeah.
Think about who, who is our persona?
Persona is someone who, you know, they have AWS, managing their AWS
account is one of their many responsibilities, and if they listen
to us, they can pick up something useful that can help them without
having to hit refresh on the AWS What's New page like you and I do.
Exactly.
I have one last question for you because I'm going to invite you to embarrass
yourself as, you know, it is always the way it works when you make predictions.
Where do you see the future of technology going?
You've been around in this space a long time.
I have as well.
Where do you think the future is in darkness?
Is it awesome stuff?
Is it something in between?
I'd like to be an optimist, and I hope that we're heading
more towards the Star Trek universe than a dystopian future.
I think about some of the building blocks that we're working
with right now with LLMs and all the generative things.
There's a great scene in Star Trek First Contact where the crew
of the Enterprise is transporting to earth and they've traveled
back to the late 21st century, and they say, "Okay, beam us down.
Switch us to late 21st century civilian clothing," and thinking about okay
what had to happen for that to work right there has to be some AI about well
what what clothing were the civilians of this time wearing and what were they
doing and there's a lot of stuff that had to happen in order to make that work.
And I think we're playing with those building blocks right now, right?
That our descendants are going to be playing with, you
know, Bedrock 3.0, which might power a transporter.
So maybe that's the case, or I'm hopeful that's the case.
The flip side of that is the amount of monitoring that we can
do on ourselves and trying to squeeze the humanity out of some
of the processes in the name of, I don't know, efficiency.
So I worry about that.
I'm hoping that- in general, I'm an optimist.
So I want that.
I'm hoping that we tend towards the Star Trek outcome.
I do too.
I really hope you're right.
I really want to thank you for taking the time to speak with me today.
If people want to learn more, where's the best place for them to find you?
Find me on LinkedIn, Stephen J.
Barr.
Type that in, look for a guy with my face, and that's probably me.
So, thank you.
Stephen Barr, Chief Evangelist at CloudFix.
I'm Cloud Economist Corey Quinn, and this is Screaming in the Cloud.
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