Let Them Eat Tokens: AI Efficiency vs. Global Good
In this episode of "How Many CTOs Does It Take?" podcast, hosts Scott Porad and Brad Hefta-Gaub dive into the pervasive influence of AI, starting with a critical look at Apple's Siri and its struggles to keep up with competitors like ChatGPT. They explore the current state of AI and its varied impacts, from productivity boosts in small resource-strapped organizations to the political and societal implications of AI adoption. The discussion also touches on the potential for AI to do good for the world, highlighted by Scott's viral LinkedIn post seeking practical examples. They wrap up with thoughts on responsible AI use, efficiency versus innovation, and the potential benefits for smaller players in the tech landscape.
Resources:
- How Many CTOs Pod: https://howmanyctospod.com
- Scott Porad: https://www.linkedin.com/in/scottporad/
- Brad Hefta-Gaub: https://www.linkedin.com/in/bradheftagaub/
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Brad: If you're two guys in a garage or two entrepreneurs or one entrepreneur or a small, you know, resource strapped nonprofit,
then maybe that's the way we should look at this productivity gain and say there is something good in that.
Scott: Hello,
Brad.
Welcome to this week's edition of How Many CTOs Does It Take to Screw in a Lightbulb?
My name is Scott Pohrad, and this is my trusty co-host.
Brad: Brad Hefta-Gaub.
Scott: And I don't think it's really how many CTOs does it take to screw in a light bulb.
I think it's how many CTOs does it take to screw in the AI.
Brad: The AI.
It's all about the AI these days.
So many AIs.
Scott: All AI all the time.
I just got off the phone talking to a startup about their AI.
You told me you've seen some things on the Internet about AI this week, and I saw some things on the Internet this week about AI,
and I posted something on LinkedIn that went viral about AI.
Brad: There
Scott: So
Brad: you
Scott: it
Brad: go.
Scott: looks like it is all AI all the time.
Brad: Yep.
Where should we start?
Scott: We should start with Apple Siri.
Brad: Okay.
Scott: I asked Apple Siri something simple the other day,
something that chat GPT voice back and forth could answer in one with its little pinky finger,
the easiest thing.
It was something along the lines of, hey Siri,
what time is the kickoff of Monday Night Football?
Something like that, you know, something
Brad: It's
Scott: so simple,
right?
and it couldn't do it.
It just showed me the link. It just gave me a list of links from a search.
And I thought to myself,
how is Apple so far behind on this?
Brad: Yeah, it's super weird.
Scott: How
Brad: It's
Scott: is it
Brad: super
Scott: they
Brad: weird.
Scott: haven't just done a deal with OpenAI?
They did a deal with Google and Yahoo and all those things to be the search provider.
You think they could be doing a deal with those guys?
Brad: I have heard nothing but the same kind of complaints that you just had about how poorly Siri looks in the context of, you know, and by the way, Siri just decided to that I wanted to talk to it. I'm not talking to you, Siri, that how how far behind it appears.
Based on kind of everything else that's happening in voice based agents.
And so you're not alone in the perception that it makes no sense that Apple's so far behind on this.
Scott: Makes no sense.
Brad: One of the theories that I have heard is that.
they are being more conservative they're waiting for the trends to continue they believe that price performance is going to come way way way down and that they sort of they've been doing like they announced at their last dev days a couple months ago a bunch of essentially on device um small model stuff and you know it could be that they're
You know, they don't really have a cloud business.
They're one of the few, they're one of the mag sevens that don't have a cloud business really.
And they're all about their devices. And so the theory that I heard was,
hey, they're just focused on let's wait,
just drive this, drive these models onto the devices themselves and not play in the cloud game.
Now,
that strategic decision on their part,
I don't know if that's a good one.
Scott: It's a strategic decision that I think will lose them device users.
Brad: Well,
to your point, like as far as you're concerned,
you don't care whether Siri is actually running on the device or is on some cloud thing,
something like that.
So you're just like.
Why? I just want this thing to work correctly and it's not working correctly.
So it does feel like the device is failing you.
Scott: Yeah.
And if Google's putting that in their device,
people are going to be like, this is better.
I can just talk to this thing and it just tells me when Monday Night Football is.
Brad: Yeah.
Fair enough.
Scott: This might be another hypothesis.
Apple has always taken the position of privacy.
They've tried to stake out that ground.
And maybe they're not able to have a solution through Siri that meets whatever standards they have.
Brad: Maybe.
Scott: Okay,
well, what have you seen in AI this week?
Brad: Well,
I saw a couple of things that I think were super interesting.
One of the one of the things that came out,
this was not this week, but pretty recently was this Axios, this kind of political newsletter,
did a survey and this was kind of like right before the New York mayoral election.
And so they basically found that.
A plurality of voters in each of the eight states that are the most hotly contested swing states.
So a plurality of voters in each swing states have an unfavorable impression of the AI industry.
The AI will raise their energy costs. This is certainly one of the things that we're seeing and that they believe increased use of AI will make their lives worse.
The higher the income,
the more favorable swing voters are.
are were towards ai and the more likely they were to believe that we make their lives better um and in some states republicans were essentially split on ai where independents and democrats all held unfavorable views so
Scott: Hmm.
Brad: this is kind of a sort of a i mean we don't usually talk about politics on on this podcast and um you know because there's so much to talk about with tech anyway but this is an interesting place where it's like
like you know public opinion is going to read on on tech and and colorado just passed a new state law and california has a really restrictive state law i heard the colorado law has like
individual rights to sue if you believe your in any of your like individual liberties have been uh restricted or infringed by ai so it's like some really super uh like broad wording like what what does it even mean right like my civil liberties have been have been somehow violated by ai like what does that even mean and so now what are you going to do are you just not
not like you can't ship an ai-based product to colorado for fear that you're the individuals will be able to sue your company so that's kind of that's also a little bit like i mean you know that that sounds like that's going to put some kind of a some kind of a damper on ai innovation
Scott: It's going to make work for AI lawyers.
Brad: It could work for the lawyers.
We don't know, maybe.
Scott: I think the energy,
I'm glad,
I shouldn't say I think, I'm glad.
That the energy concern is percolating because I have energy concern.
Brad: Well, the cost of energy has been skyrocketing around all the locations that the big players are building,
guess what,
ding, ding, ding,
data centers.
And that tips into my next little piece of data that I learned.
I think in a recent episode,
you and I were talking about this and I kind of talked about this whole like challenge around like.
like this circular revenue and a lot of these big players are like basically you know kind of doing these deals that that no cash changes hands but
Scott: Mm
Brad: they-hmm. all are both basically both booking revenue well another another piece of data is that the mag 7 um so the apple you know facebook google etc those guys uh they're apparently in the last quarter they had 60 more than 60 percent of their free cash flow was spent on
on building new data centers.
So they're building data centers like crazy,
and those data centers are all going to consume and drive up local energy prices.
So even if you ignore the potential climate impact of all this construction and energy usage,
At the consumer level,
like if a data center goes up near your house, your energy costs or in your state,
your energy costs are going up.
And so, yeah,
I mean, like I said, man,
the rent's too damn high.
Scott: That's too damn high.
I don't want to get too deep into politics, but I will add one puzzle piece to this, which I heard or read lately,
which was.
You know, some states, they tend to be redder states, have more, you know, liberal,
easier to work with sort of zoning and land use and development laws.
And then as a result, things like data centers and wind farms and solar farms and things are getting built there.
And that was causing a little bit of a backlash. So it's interesting how all these things are intertwined.
twined with each other.
Brad: Yeah.
Scott: And I wonder also,
so I think I've said this before on the podcast,
and if not, I'm going to say it now,
which is I worry about the climate impacts of this stuff.
Like is the value we're getting from the fact that I can ask the AI when Monday night football is,
when I could easily just go look at the TV program and is that worth it?
Brad: TV guide, still have those paper copies in the TV
Scott: Yeah,
Brad: guide.
Scott: every week I get a little TV guide at my house.
It's not, you know, you can easily go look.
to look up you know just ask google what time does you could type it in what time is monday night football um and so i do worry about the the roi so to speak on the climate and then there's the other thing is are we are we seeing over investment here right i mean like is this an arms race are we going to have a a bunch of zombie debt you know like shopping malls like a bunch of zombie data centers out there
Brad: Well,
yeah,
and I think that's kind of what I was saying before is I'm starting to hear analysts in the space who are bullish,
whatever techno optimists who are saying like,
oh, yeah,
like, I mean, I just heard this interview with where Sam Altman was like,
oh,
for sure, we know that there's going to be an overbuild. We just can't predict.
We have such demand right now.
We're still building as fast as we can.
But surely there'll be some kind of infrastructure overbuild. So like the idea that like the the the you know, the head of the parade of like, you know, AI optimism is saying, oh,
I am certain that we are overbuilding infrastructure.
Right.
Like.
That seems like a pretty big deal to me.
Scott: Yeah, that's right.
Well,
I guess there'll be a cool thing that comes out of that,
which is that we'll see the price of tokens hit the floor when basically everybody's got these capital investments that they just want to get anybody to use them.
So they're going to bring their.
margins basically done it's going to be the ultimate commodity unless i guess some models can really do well data centers will be the commodity because it's just power it's just electricity i guess uh the models unless they can really differentiate themselves um will be commodities too and it seems like i'm starting to get the vibe not not no pun intended that of the of the models i pay attention to it's claude that's sort of starting to differentiate itself a little bit
Brad: Yeah,
there's a lot to...
a lot to unpack there i mean i think there's no doubt that you know another another uh interesting podcast i heard recently which there there was some there was some sort of classic uh elon problems with the statement that he made here but he was basically making the case that like of course like token prices are going to fall of course uh because everybody's working to try to make these the the more compute happen with smaller effort right like that's
that's the big thing and he like compared like the amount of electricity that the human brain uses which is like ridiculously small you know it's measured in you know it's measured in watts not you know gigawatts right and how much you know he made some statement about like you know look we built all of humanity you know on this this small power consumption now
Scott: Wow.
Brad: that's that's ignoring that's ignoring
you know the network effect of a lot of humans and and history and that's the you know language and the major thing that we do but but again i think this kind of speaks to the the whole trend of conversation right the trend of conversation in the in the leaders of the parade is all around yeah we're pretty sure we're overbuilding yeah we're all trying to basically lower the compute cost yeah we're
we're all kind of like you know building like crazy right now but we think this is all gonna um the prices are all coming down and so you know that's like
This is very, very similar to the the turn of the century,
Scott: Mm
Brad: the turn
Scott: -hmm.
Brad: of the millennium,
Scott: Mm
Brad: when
Scott: -hmm.
Brad: it was all about building out fiber. And
Scott: All about
Brad: so
Scott: fiber.
Brad: and,
you know, like the same exact like the same exact type of just on the edge of, you know, kind of dicey financial transactions that that Enron went over the edge and,
you know.
Broke the rules on that kind of stuff, that circular revenue,
that stuff is happening right now with these big players.
Scott: But hey,
the stock market's going up because of it, so we're all benefiting from that, right?
Brad: unless
Scott: And so,
Brad: your electricity
Scott: yeah,
Brad: prices are going up so
Scott: that's right.
Brad: it's interesting i just think i just think it's an interesting thing like what what's going to happen here uh you know if again like we put our cto hat on right like there's no doubt in my mind that like my engineers are benefiting incredibly from this like they're so much faster than they were even a year ago and you know to your you mentioned that you know you kind of put
kind of posted that thing on linkedin this week about like you know uh what vibe but verify right like it's for real it's happening what but is that all of a sudden is there some backlash coming even bigger backlash that's coming that's and what's going to happen then
Scott: If history is a lesson to be learned from,
there is a backlash coming.
I don't know what it is or when it's coming,
but I think it'll be coming.
I see a lot of uses of AI that aren't very interesting.
So for instance, on my stationary bicycle at home,
there's now an AI summary of the ride that I'm about to do. It's like, really?
Is that necessary?
So I actually, you mentioned LinkedIn,
I actually had a post on LinkedIn this week that went viral.
Before I tell you about my viral poster,
can I tell you about another post I saw that has nothing to do with AI,
but
Brad: Yeah,
Scott: simply
Brad: sure.
Scott: has to do with sage wisdom?
Kent Beck,
you know the name Kent Beck?
Brad: Yeah.
Scott: I think Kent Beck might be a little bit of a curmudgeon, but I also think he's very wise.
And he told me on LinkedIn,
he wrote this message to me personally and basically to everybody else that follows him. So it wasn't really personal.
He said that his washing machine told him that two undersized loads is more effective than one oversized load.
Brad: Oh,
Scott: And
Brad: I
Scott: he said, even my washing machine knows agile principles.
Brad: love it.
Scott: I loved it too because it's true.
It's really true.
Okay,
I wrote a post that went viral this week.
Every once in a while you just put something out there and thousands of people.
glom onto it. And I started my post with these words,
a rant on AI.
That's probably what got everybody's attention.
Brad: Yeah, I'm sure that's what pushed the algorithm.
Scott: I had read something, we may have discussed it here,
according to an MIT study,
AI is being used most effectively for back office efficiency so businesses can cut costs and make more money.
Hooray.
And then I ask the question,
what about doing good for the world? What about making people's lives better?
I'm still looking for these kinds of AI uses.
What is that's what's most interesting to me about AI.
I would be grateful if you left examples in the comments and I got many comments with some that I think are good examples and some that I don't think are good examples. To me, that's the most that's that's what I'm interested in with AI.
That's what I've been thinking about.
You know, I think listeners of this podcast know certainly, you know.
No, I was never like an AI naysayer, but I've been on the back end.
I haven't been on the front edge of AI like you've been on. I've been on the back edge of AI.
And where I'm at right now is like,
okay,
this is cool.
There's lots of cool stuff happening here.
Like, but I'm not really interested in like saving a minute of time for some people in some department somewhere.
I'm interested in doing something that.
is interesting and cool and
Brad: What
Scott: cheap.
Brad: was the best example people gave you?
Scott: Gosh, the best example,
I'll just read you a few.
First of all,
people,
technical people can sometimes become sticklers. Have you ever noticed that?
Yep, that chuckle means you've noticed it, you've seen that happen before.
So
Brad: I've seen
Scott: the
Brad: it.
Scott: notion of AI and ML get a little mixed up sometimes.
Brad: Oh, yeah, sure.
Did some of your ML buddies respond?
Scott: One person said,
I read about a fork, like an eating utensil that canceled out hand tremors to make it easier for people to eat.
And then another person chimed in and said, well, that's really ML.
That's not AI.
Brad: Ha ha ha ha ha ha ha ha ha ha.
Scott: Another person said,
and this was interesting.
And this is a person I really look up to.
I know actually all these people are people I know just about another person I really look up to said to me, well,
I work with a lot of resource strapped not for profits and for them saving a little back office money is really meaningful.
Brad: Yeah.
Scott: So that's interesting.
That's a positive way to look at him.
Another person actually has listed a number of examples.
I actually have not gone through all of the examples that he listened to.
But he just pointed out places,
something called Alpha Fold, which is helping drug design.
Duolingo, which,
by the way, I don't know if you know this,
I am a Duolingo user rocking a seven.
750 day streak on Duolingo talked about you mentioned pointed to some examples of how anthropic and open AI are trying to get into AI for science they don't really know exactly what they're doing open door which is trying to I guess solve some problems in real estate I'm not really sure that wouldn't be possible without sort of
deep research ai so that's just some things that got mentioned i'm just scrolling down here um this person pointed out a company that managed to save i don't know if it was a person actually i don't know exactly who but someone saved a bunch of money in hospital bills um
Brad: Yeah.
Scott: here's another list of things that i'll just stop after this one another actually this person i don't think i know who they are um now see this is where i think it gets interesting right okay
Brad: This person said, look, just last week he saved five hours in lawyers doing stuff,
$100,000 a year in SAS costs,
which allowed him to hire another person.
He automated accounts payable so he could get.
his vendors paid faster and so i don't know if those are actually really that interesting and then it goes on there's lots more comments here for any of for the 39 people who listen to our podcast just go to linkedin find my profile find my posts you'll find well this one
Scott: your your pro your linkedin profile is always in the show notes so they just click on
Brad: there
Scott: that and
Brad: you go there you go so i don't they know but that's the stuff i'm looking for that i think is interesting um to try and
Scott: i don't want i don't want to be in that stickler department like
like ai versus ml but you know carbon robotics uh their local seattle company that's built um a laser weed uh laser weeding tractor and they have like gathering all this photographic data and they're like boom for sure it's all it's all ml it's all it's all ai in that sense and
Brad: What is a laser weeding tractor?
Scott: It's basically like, I think somebody even said this on your post about pest control.
Basically, it's all for farmers to basically get higher yields out of their fields because they don't have to put pesticides,
they don't have to put herbicides. They can basically like use this tractor and it's like it's automated. It's like drives up and down the field and like zap weed.
Yeah.
Yeah.
Brad: That's cool.
Scott: I know the founder,
Paul Mike sell of that company.
He's Paul's Paul's a super smart guy.
Worked with me back in the day at Real Networks. One of those 10X engineers for sure.
Brad: Super smart people,
man. They got to be super smart these days.
Scott: Yeah.
Brad: We need AI for dummies. That's what I'm going to make. I'm going to make AI for dummies.
And it's where you can just ask stupid questions and it gives you answers at an appropriate level.
Scott: I don't want to say we already have that in Siri because Siri will just like light up again and think I'm talking to it.
How do we boil this down into like actionable things for CTOs and for executive engineering people or how do we be better partners with our other stakeholders?
Brad: I'll tell you about a frustration I have actually in a hot take I gave to the CEO I'm working with this week.
And I hope I'm not going to get myself in trouble for this,
but what's the worst case scenario? I get fired.
what's the worst case sir i get fired and then i can't pay my mortgage and then i'm homeless and then i die and you know there's worth ways to go so um and there's a stop in there before homeless there's a stop at my mother-in-law's house where my mother-in-law and my wife one of them end up killing the other and going to jail and so you know it's
Scott: Wow, that's a dark turn.
So
Brad: a dark it's a dark turn
Scott: let's hope that doesn't happen.
Brad: It's easy.
I see this happening in our company.
It's easy to find opportunities to make people more efficient.
And when I said to our CEO this week, I was like, can we just stop doing everything,
all the make more efficient stuff?
Just forget about it.
I mean, people want to do it, do it.
But let's stop putting emphasis on that.
Could we just figure out how to use AI to actually achieve our mission,
which is.
all our mission is to change lives one task at a time has actually been our mission but like how can we actually like provide our service better with ai like that is what is going to grow our revenue what's going to grow this business and ultimately which is going to serve that mission like because people naturally go to i can do this thing to write this document faster we can do this thing to automate this thing in accounting because it's just very tangible right like but it's harder to get the momentum going on
on the product slash business side so i guess if there's a lesson i want to say to ctos out there is you know try to channel that ai energy towards actually making whatever you're working on better and that can be difficult and i'll tell you something we're doing we're about to have an ai focused hackathon coming up pretty soon actually we're not calling it a hackathon we're calling it a
let's just call it a hackathon we have a different name for it because we want people to be a little bit more expansive than that but like create some space for people to just go play and figure out what could we do with this like i have an idea that i want to do with this hackathon of like what we could do
Um,
but in my day-to-day, what we're focused on, what our business priorities right now is not taking a week to screw around to do Scott's silly idea that maybe it'll work,
but we're going to create some space for people to do that.
So, um,
I think that's something that is CTOs that we can do to create the room for people on our teams to find ways to use AI to have.
meaningful impact on the world as opposed to just meaningful impact on the bottom line of the company I don't totally mean to sound like a Marxist here but like and I'm not by the way but like you know I just feel like so much of what we do
is something about this technology revolution compared to what have I been through I've been through the first dot-com boom so the e-commerce boom well actually let's go back the first dot-com boom had a few parts to it it had online media and it had e-commerce and then
Scott: Mm
Brad: I went
Scott: -hmm.
Brad: through the social media boom and then I went to the gig economy boom and I went through the cryptocurrency blockchain boom and now I'm like in the AI boom and I feel like for some reason this one
more than any others naturally not through any malicious intent just naturally is lending itself to benefiting the capitalists as opposed to the proletariat oh we have the bourgeoisie as opposed to the proletariat right and so i guess as as leaders we have to use whatever
Well, I guess if you're a Marxist like I am now, apparently,
we have to use whatever influence we have to say how can we actually use this technology for better for the consumer as opposed to just better for the bourgeoisie.
And that's my take.
Scott: Well, and...
Yeah,
so this is definitely getting into the politics and philosophy, and it'll be interesting as I ponder how I want to respond to that.
There's a version of there's I sort of feel like I kind of want to play devil's advocate with this.
You
Brad: Do it
Scott: know, there's a fair amount of what you just said that I 100 percent agree with.
And then the but the argument that I've heard to counter that is,
but what about the solo entrepreneurs? What about the two guys?
guys in the garage they now they the one person that said something like hey i work with a lot of like small cash strapped non-profits and they spend quite a bit of time you know trying to figure out how to be more um optimal in their usage so so to me that story this idea that like well there's not anything that's it's not the case that the only people that benefit from efficiency gains and productivity gains
are big corporations with lots of people where you end up doing risks because of that productivity gain they're not the only places that productivity gains result in good things i mean that's that's the that's your point about the capitalist you know
basically get more done, get the same amount done with less people.
Brad: I
Scott: But if you're two guys in a garage or two entrepreneurs or one entrepreneur or a small resource strapped nonprofit,
then maybe that's the way we should look at this productivity gain and say there's actually some there is something good in that.
Brad: agree with that entirely.
And I saw that comment there before,
and I'm glad we went through those again because it makes me think,
okay.
To me,
that's interesting.
Somebody saying,
I'm going to make this up. I don't know. I'm making some, I'm making a flux capacitor such that, you know, community health organizations can manage their case load more efficiently and then they can take on more patients and so on. I don't know,
whatever would work.
Like, well, there you're saying, hey, I'm going to use AI to actually do some good for the world.
And so you're right.
It just seems like maybe it's just the space I'm in is.
I just see people tend to lean toward just making employees more efficient.
But I guess what you're saying is depending on the context in which you're in, whether you're in a big company or a small company,
actually making employees more efficient has different benefits.
Scott: Yeah.
Brad: Yeah, that's an interesting way to think about it. I guess, okay, maybe I'm just a jerk actually.
Scott: No, I mean, I mean, I mean, you know,
there's this concept that you hear in like in venture capitalists, they often get around and they talk about like,
oh, or, you know, sell side analysts or whatever they get around,
they get it together and they're like, oh,
that company needs to get more fit,
get fit, get fit.
Right.
And that's like that's like large corporations speak for increased productivity and cut staffing,
right,
like lower, lower costs as as part of.
productivity gains and that basically means lay off people or if people right and you know i i'm sure you've been there before like i know i've been there where um
when it was you know roaring roaring hey hey hey um we were you know higher like crazy because you're just trying to move as fast as you can and you've got to and you know everybody's super busy so you're you don't have time to think about efficiency you're just busy cranking stuff out as fast as possible and it's it's a true statement that like companies in that in that particular part of the cycle they will hire people that they don't
necessarily have something for all of them to do uh long term right and
Brad: I've never
Scott: i
Brad: had that
Scott: mean
Brad: problem.
Scott: i i mean i i've definitely had the problem of growing too fast and growing beyond our means and then later kind of coming back and going ah we probably didn't need to hire all those people
Brad: I was responding to not having something to do. Yes, absolutely.
That's a pattern I see.
very consistently at companies I've been at, companies just get out over their skis.
Scott: And so in those environments,
in a world where, I mean, this is an interesting like,
you know, if AI can help me.
take my current employees and make them more productive,
then maybe I won't accidentally hire people that aren't sustainable for me.
So that's another version of the productivity has a different lens.
And if you're the solo entrepreneur who's trying to bootstrap, then that's definitely where you're at,
right?
You're just trying to get as much done as you can with the least amount of resources possible.
Brad: Okay. And now the solopreneur, the small business person,
that's interesting.
I got a question.
Question for you.
In our world, in the technology world,
like there's kind of like frameworks you can get, you know, it's like it's a whole package.
I'm wondering if we could make like AI,
this is kind of like a business idea,
AI solo entrepreneur in a box.
Like you just you got everything here. You've got your people operations,
you've got your finance,
you've got your
what marketing website I don't know what else even you need you need you got your legal AI stuff it's all right there maybe it's not maybe it's just a layer on top of some best of breed stuff but like really it's almost like kind of like a workday or a Zoho kind of thing
Scott: Yeah, Zoho is an example of that,
and there's a handful out there that like, you know, kind of a.
I mean, I don't know all the names of them,
but, you know, definitely there's the when the gig economy thing was was taking off like in every and all the states started cracking down on like self-employment, then there was a boom in there was a boom in companies that basically were like,
oh,
we'll help you form your LLC. And also while we're at it, here's the solo entrepreneur in a box,
Brad: Yeah.
Scott: you know, so here's your built in here's your built in, you know, boilerplate legal contracts. Here's your built in.
will sell you business insurance and so yeah
Brad: oh all
Scott: i mean i well
Brad: the good ideas are gone but
Scott: i mean probably
Brad: what did that guy in the patent office say like in 1921 i don't know everything that could be we don't need a patent it was like the head of the patent office it was like we don't need a patent office anymore everything that's been invented has been we've invented it all yeah
Scott: anything that can be invented has been invented yeah
Brad: who could imagine anything else
Scott: Yeah, exactly.
All right. So so so there is this tension around like productivity gains and the implications of that for, you know, everyday workers.
And then there's the tension of like,
yeah, but, you know, hey, this gives people an opportunity to be solo entrepreneurs,
et cetera.
What about your other posts that you had about LLMs don't eliminate the need for experts?
Tell me more about that.
Brad: Okay, that wasn't really my post.
It was just reposting a guy named Chris Sod.
I think that's how he pronounces his last name.
I'm acquainted with Chris. We met a long time ago in the mid aughts.
I think he was working for a company that we,
that my company was.
um buying their software and then we got to hang out a bunch of south by southwest and then i think he went on to be like early at uber and
Scott: Yep.
Brad: if i recall and he's a pro he was an engineer and a product guy and he's he's really bright on the startup stuff and i love his attitude and he had this post about um
how he was talking about how how you know people are saying oh you know chat GPT is killing the need to hire domain experts and somewhere in there he said you know LLMs don't
eliminate the need for experts they amplify the need for experts and it actually goes right back with that thing you quoted earlier which is another post which was vibe then verify and it's really the verify part which is and this is what we did the same thing we've talked about with software development and having the agent go write you some software it's the the job a lot of the job is turning to the verify part where you actually need the expertise
And then we've talked about this, too,
and I don't know that anybody has the answer to it, which is, well.
How are people going to get the expertise?
Scott: Yeah.
Brad: And which actually leads to another post. I didn't write this
Scott: Wait,
Brad: post.
Scott: wait, wait, before we go off the vibe, but verify and the need of the expert, I'll tell you a funny thing. Literally, this just happened today.
One of my very,
very senior developer DevOps senior guys,
he was like, he basically was trying to say that we we've we were all Docker Docker compose in most.
in most of our our stack especially our local development stack and then we started using kubernetes now in the cloud and one of the ideas that was floated by one of our new devops guy was that there's this there's this miniature version of kubernetes instead of k8 about called k3s which is like a mini kubernetes and and my my senior devops guy was like
Oh,
I'm going to try to I told Claude to convert all our Docker stuff into K3s and it went crazy.
It started going all over.
It was just running all over the place.
And I don't know exactly what it did.
I still need to go in there and unbury it from all the rubble it created
Brad: Yeah.
Scott: and figure out if it made any progress or not.
Brad: Okay.
So my friend, Sean Nolan,
my friend,
I consider him a mentor really.
He was, I worked for him.
I mean, this will date us. I worked for him in the 90s.
He was the CTO I worked for and he was a great CTO to work for. He's super bright.
He's a he's a bright guy and he's just a high energy guy and positive and he's curious and he's retired now from actually having a day job,
but he's always he's a tinkerer and he's never going to stop being tinkering. And so the other day he was he posted about how he was curious about some question.
Oh, I'll just give a little bit. Apparently,
the United States government subsidizes regional airports and regional airlines so that everybody can have access to transportation.
And so he had some curiosity about that and he went and dug up some data about some different things and then he did some analysis and he fed this all to ChatGVT.
But when he asked ChatGVT or Cloud Code, I don't know what he was using, he fed it to the model.
I'll just call it the model,
the board.
He fed it to the board, but he said, I need you to write me.
A program,
I want it to be a node with JavaScript that takes these three data sets and does these things to them and outputs a CSV because he knew once he got what he wanted into a CSV, then he could analyze it in the way he wanted.
And I asked him, I asked online,
and then he ended up writing,
this was a blog post that he posted on LinkedIn and I left a comment there and then he wrote another blog post in response. And what I said was.
Sean,
why did you ask it to write you code?
Like you're an engineer and it allowed you to double check that it was doing it right and that was doing it your way, but you could have asked it to do the analysis all the way through to get you whatever answer you wanted to know about regional airport subsidies because you're curious and couldn't help yourself.
But you wouldn't have been able to verify if it was right then in that case.
And most people don't have the skills to actually have it write you code that you can then run locally that you can then get your CSV that you can see if the results are right and so on and so forth.
And I just pose that as in the vibe but verified dilemma. That is.
a problem,
which is if we ask, he could simply ask the question
Scott: Yeah.
Brad: to the model and the model might have come up with the right answer or might have not come up with the right answer.
We know the model would have answered confidently.
Scott: Yeah.
Brad: And so
Scott: Well, it's really still bad. It's still bad at math.
It's really still bad at simple math. Like I,
you know, I use it all the time to do things like nutrition tracking and stuff like that. And it'll tell me like,
oh,
that meal that your breakfast had,
you know, seven grams of fiber in it and your lunch had 15 grams of fiber. So you've got 11 grams of fiber so far for the day. And it's like seven and 15 does not equal 11.
What are you talking about?
how
Brad: How can
Scott: yeah
Brad: you rely on it for anything then?
Scott: so that's why i think to your point though that's the reason like you've got to verify what it's doing like if you just take it at face value it's like for sure gonna just yeah it's a mess still that part is still a mess there
Brad: It's a mess.
Scott: you go
Brad: Here's what I'm taking from this conversation before we wrap.
I'm going to go try to find.
I'm going to have to find I'm going to go talk to the not-for-profits that I support in our local area and I'm not just going to go do some product management, some customer development and try to just see like are there ways that we could build some small products.
Scott: Yeah.
Brad: Maybe some small SaaS services or something that would be inexpensive or free to not-for-profits that would help them be more efficient or effective.
How could our food bank,
that's the one, you know, we support the local food bank.
How could the food bank benefit from this stuff?
I
Scott: let
Brad: don't know.
Scott: them eat tokens
Brad: Let them eat tokens.
That needs to be the title of this episode.
I know you're the guy that comes up with the titles.
So let them eat tokens.
Can we finish on that?
Scott: finish on that wow that was quite a run yes
Brad: Brad,
it's been fun this week as always.
Scott: good talking
Brad: I look forward to talking to you next week.
Scott: what do we say
Brad: Smash rate and subscribe.
Review,
rates, subscribe,
all of it.
Scott: Do it all.
Brad: Thanks, everyone.
This episode of How Many CTOs Does It Take Podcast was edited by Saffron Epigal. Our theme song was AI Generated by Brad.
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