Brian: to the rebooty show.
I am Brian Morrissey.
Today I'm speaking with Pete Pachal, a veteran news editor who runs the Reliably Excellent Media Co Pilot newsletter.
Pete is deep in the weeds about the intersection of AI and news publishers.
it's Topic that I is very near and dear to my heart and I always rely on a media copilot to keep me up to date.
Pete, is, an expert in this area.
And we discussed the recent news of deep seeks apparent AI Sputnik moment.
and what it means downstream for publishers beyond, The fact that everyone's 401k took a hit today.
we also talk about actual use cases of AI improving the news product.
spoiler, there really aren't that many to date.
And the implications of agentic AI, which is where, basically AI agents go out and accomplish tasks, and whether that will make websites Obsolete.
it's a real possibility.
And also the wisdom, or folly of site specific chatbots that we're starting to see from publishers, and the underwhelming example of AI news aggregator particle, as well as why Pete is obsessed with
Google's Notebook LM and whether we will see the contours of a grand deal to iron out the economics of news content if AI keeps gaining ground the way it has been.
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Now on to my conversation with Pete.
Well, Pete, thank you so much for, for joining me today.
it was a busy weekend with this deep seek, announcement, but I want to get into, I want to get into that a little bit, but, and the overall sort of AI arms race,
but really, you know, the idea of this, for me was to get a look ahead at how AI is going to impact overall the media industry in the, in the year to come.
and we'll get into news, but beyond that, but this weekend, AI never sleeps, I guess.
And, a new Chinese, AI model came out called DeepSeek, and it does a lot of the things these other models do.
I played around with it a little bit, I read about it more and, you know, to me, the, the big difference is how, is how Much a cost to, to put together.
at least the journals reporting had 5.
6 million versus the, you know, billion plus, that U S models are making, I, which is by the way, is a little ironic because the tech people keep claiming that they're going to eradicate wasteful
spending from the government and I start to wonder if, if what they're doing is a giant waste of money, that maybe they're not the people to do that, but that's for a different podcast.
what is the significance of DeepSeek?
It's, it's being painted, you know, very hastily as something of a Sputnik moment.
And, and by that, it meant that like, you know, when the, when the Soviets came out with Sputnik, it was like, Oh no, they're going to be able to compete technologically.
And, and the Soviets actually did.
Did do a great job.
Soviet engineering was amazing for what it could do within the constraints.
And it seems like something a little bit similar here because the US, in its alliance with our tech oligarchs has tried to, control, the transfer of, of technology and GPUs to, to China.
So give me your, your, the, the, the assessment of, of the significance of this.
Pete: Yeah.
Well, first thanks for having me.
It's super thrilling to be here.
Always love talking to you.
so yeah, the deep seek thing.
Like you, I think you nailed it out of the gate and that the big factor here is, is cost.
And what I try to do is I sort of think about this less in the sort of macro level, but we can get into that a little bit.
And more on the sort of like, what is the trickle down effect of something that is inherently cheaper.
Just to run and, you know, essentially like I even, well, you know, small time people like me feel the cost of AI.
Sometimes I try to automate a bunch of different things like social and whatever, and I have certain bots I've built.
And sometimes in some of these platforms that I use, like I notice my costs.
Going up because of the model I pick, whether it's for GPT 4.
0 versus the 4.
0 mini.
And, you know, it's, it's for a solopreneur like me, it adds up to hundreds of dollars, not, not the tens of thousands, but you can sort of scale that
for sort of publishers and media folks who are trying to, you know, essentially automate chunks of their operations.
And it's like, Oh, okay.
So I need to use.
This other model that doesn't give me quite as good results, which might actually sort of place it below a threshold of quality, and therefore the AI thing is not viable.
Now this creates a whole level of viability for those scaled projects.
potentially if, if they.
End up using it.
So, so, so that's the, the most sort of immediate sort of trickle down effect.
I see.
Now, the other thing about this is that it's out of China, right?
Like, and I kind of feel like, well, didn't we just have a big row over Tik TOK and, you know, Influence and having that power, a certain amount of infrastructure.
Now it's obviously super early days for deep seek.
I mean, you know, just came out and no one's really, you know, using it in a, in a big way, but I feel like if
it does become this thing where it's essentially as good as the current models and sort of keeps pace with whatever.
Is, is coming out in, in a sort of open source, commercial way, you know, like it's going to create some
of these questions and influence and, and, you know, is there some, some strings behind the scene?
Whether that's founded or not, you know, knowing that it's, you know, kind of the same kind of open source deal as llama, it's, it's,
Brian: Yeah, I mean, it's, it's key that it's, it's, it's not open AI, which is not open, it is open source.
And so that would seem to get around.
I know the, there's already been some early, you know, whenever anyone gets access to one of these, these chatbots, they try to get it to like,
say something bad or, and so if it's from China, you go and you ask it about Tiananmen Square, Xi Jinping, and, and, and you see that it's, Goose prize.
it's not going to return, some sort of, you know, answers about the massacre there or about Xi Jinping's, record with the Uyghurs or whatnot.
but I would guess, you know, because it's just a model and it's open source that the idea is anyone can take that and, and build.
You know, a model that doesn't have those kind of quote unquote controls on it.
Now, I, I'm a realist.
I mean, I, I've, I've been in the midst of this PR campaign from Silicon Valley that, you know, they are, they all of a sudden have clock have wrapped themselves
in the American flag after being these massive multinational corporations that use tax havens and all kinds of things.
But okay, whatever, it's a business.
And, it puts a lot of pressure on them because, you know, they have been firing, telling us that we need to fire back up, Three Mile Island.
And, you know, Sam Altman at one point was talking about raising 7 trillion, which I don't know where he came up with that figure, in order to, to get more, data centers up and running.
And this is just, at least in the initial, Reports that I've read is just far more efficient.
So I think the biggest impact right now is like, you know, the stock market is, do not look, do not check your 401k, I guess, because the stock market
is dominated by these, these tech companies and, And it's, it's calling into question whether or not all of this spending is, is, is really necessary.
That's, you know, a tech story and a finance story.
It doesn't really impact to me, you know, the idea that the costs will come down is just axiomatic to All of technology, you know, all of these products are
going to be, you know, very jury rigged in the beginning and they're going to be incredibly expensive and they're gonna be clunky and we all dealt with that.
Anyone who used the Nokia and 95 phone can attest to that these things do get better, and they get cheaper.
so it, it will be interesting to see how this, because it would seem to speed up the deployment of this technology, like you were saying, into real use
cases, because I guess sometimes with this, I struggle a little bit with the AI story because it lands in, it could, it could, it might, it should,
you know, range when we start to talk about actual, you know, Real life use cases that are not incremental, you know, and so where where are we?
With that right because to me a lot of the the general coverage of this It falls into either academic.
I don't care what agi I don't care like I don't know why I should care about some nebulous line where it has crossed and whether it's PhD level
or whether it just has like a master of science or whatever What the only reason any of this stuff matters?
Is if it has real impact on how we live and how we work like that's all that matters this other stuff is nonsense and the You know, pouring billions or trillions into data centers.
Great.
I saw this with Broadcom and Global Crossing with Lane Broadband.
And there was a ton of money lit on fire then.
There was a lot of companies that went out of business.
I assume it's going to be the exact same right, right now.
But like, where are we with real life adoption of these technologies and the impact?
Because whenever I, like, we have these dinners and I ask people in the media industry, what are you Give me like what you're using AI for and like I just hear like chat GPT
Pete: Yeah, yeah.
It's funny.
Like here, you know, when you're reading about AI, when you're kind of living it, like maybe like certainly
I am and you as well, like you're kind of in this bubble and you think, Oh my God, everyone knows everything.
It's, it's going so fast.
I can't keep up.
And then, you know, I, a big part of my business is teaching, uh, newsrooms, PR teams, creative teams, how to use AI.
And then, you know, I sit down with these groups and it's like, Oh, everyone's still just kind of messing around with a few prompts here and there.
Right.
So to your point of like, when is this like real, when is it actually arrived?
I think it's when that part of my job kind of goes away.
Right.
When, when it's so inherent and so
Brian: Let's stretch it out Some a bit longer than Pete
Pete: Yeah.
Well, I hope so.
You know, like I, I definitely see demand.
So I think it's a ways out.
Like, you know, so everything we hear about, you know, deep seek and Stargate.
And everything else, yeah, it's, it's all exciting and a little scary, but when it, you get down to the, the general level, like my wife doesn't even really use chat GPT at all.
you know, it's not really affecting the normies quite yet.
I think we're going to get closer.
So there's, there's a whole layer of chat GPT use that I think.
Layered up, or leveled up when they introduced search and, you know, it always could access the web and sort of oblique ways, but when search came
out, it's like, oh, you know, this can actually, Potentially replace your, your browser experience in some ways.
And certainly it's an early adopter thing right now to do that and sort of change your default.
But I feel like that's like the first kind of step towards some future where, you're just talking to the AI and it's just bringing you things.
This is sort of like the agentic.
Brian: Yeah.
So let's, let's break down the agentic.
so, you know, I think, look, I, I stepped outside of my apartment the other day and I, I saw like a Salesforce like agent force, billboard.
I'm like, oh no, it's on now.
When, when Salesforce is rolling out the giant, the, the out of home campaigns, you know, it.
Pete: in the airports.
Have you seen those?
Brian: you know, when you, when you see airport out of home, you know, they're going to like jam this stuff down our throats, like all year.
So yeah, we're going to hear a ton, ton about agents and agentic AI.
And that's basically, I mean, my sort of definition of it is they go out and they do things for you.
It's, it's the, at least this is in theory, right?
Like the idea is you're going to, it's not going to like point you to a bunch of links or tell you how to do something.
It's going to go and do something.
It will book the flight, et cetera.
Now, when these things start.
It's going to be so much, this is my prediction, maybe I'm too cynical, maybe, it's going to be so much easier to just do it yourself.
Cause when people talk about it being like infinite interns, I'm like, anyone who's had like interns knows that's like, sometimes like it's more work than actually, and I'm like, infinite?
Are we sure we want that?
Can we just start a little bit lower?
Pete: infinite managers
Brian: You know, cause I, I, this is like a little bit of an aside, but, I can remember I went to.
I got out of J school in 2000.
I just got a note about our 25th anniversary and I joked that, I
Pete: I just had mine.
Brian: I joked, I joked to the woman they should have like those of us still sort of in the profession, or I guess I still am like, you know, bring us out like, D Day veterans, like the last D Day veterans.
But, I don't even know if I would qualify, but the people that are like still working for newspapers, let's bring them out, give them a round of applause.
but I can remember then we had a Super Bowl party at the, for the 2000, Super Bowl and, the, like the guy who is the Dean of like the new media lab or something, he, he insisted on ordering
like the Domino's pizza, like through the internet, because you could, And guess what Pete, we had a keg party with no pizza because that goddamn pizza did not show up and something similar,
Pete: was always, what did the, the, the progress bar on the dominoes just
Brian: this is before that, this is before Crispin Porter Boguski got involved.
This, this was like, you know, very, very early.
And it was like, everyone was like, Can you just pick up the phone?
So anyway, I think agents are going to be something similar, but at the same time, it, you know, everything starts like
this and just like, you know, e commerce took off, it didn't stay with the, just pick up the phone to order the pizza.
God damn it.
it's going to get going, but what give, like, what does this mean for, for publishers in general, because to me, if you play this out, like, let's just assume that, that what.
is claimed for, for this agents actually eventually comes to fruition in a real way, not a hack together way.
And like a couple of years, like to me, it's like, That's kind of the end of websites, right?
Because like websites are just like, this is said to me at a dinner the other night, like they're just some kind of UI front end to a database at the end of the day.
And it's just like calling and retrieving data.
And the website itself is just kind of like a cloud.
Clunky intermediary at some point, but like what do you think the big impact of this agentic vision of AI is for publishers?
Pete: Yeah.
Well honestly it ties back to a little bit what we were just talking about.
'cause you know, there was a, we were talking about like the Stargate stuff and the big picture stuff and
all this, you know, compute power that we're gonna get and that power and infrastructure, all that stuff.
What that's gonna empower is a lot better inference, time compute, right?
Which is to say like when you actually search for something online, some information, it's actually gonna be able to process so much more so quickly.
That Right now, like AI search as it exists is a little bit kind of like the baby version, like it seems like it's going out and reading all of these articles in real time and doing it.
And it's not really like, there's a lot of schema and a lot of metadata that's, that's still involved in that.
but once we get there and, and you, you can actually do this, that is a hundred percent when like websites are kind of obsolete, you know, it's like, okay, now, like, as long as.
We work out the monetization and the, you know, the,
Brian: It's a big
Pete: licensing.
That's a, yeah, it's a big asterisk, but if that, you know, the models are kind of emerging and you could see some, someone running with the ball with that,
then everything just kind of goes into this blob of information as soon as it's published and then, you know, as soon as someone asks for something that that
fits the pattern of it's, it's going to get summarized and, you know, they can go in and go deeper at some point.
So, That's a bit, obviously it's a bit of a ways off, but I think that that is the, the train we're on.
Brian: Do you see anything like that?
You would point people to?
that you can start to see this like happening because I think one of One of the big questions is how much publishing Brand really matters and the you know, I think a lot of times
Particularly in journalism, you know trust the trust flag comes out right and it's just used as kind of like I don't know gauze to some some degree.
I feel like because it's never backed up with actual You know data or or evidence There's this just kind of like
religious belief that you know, our our audience trusts us They're loyal and everything and and i'm like, I don't know.
I mean the data i've seen is that people Do not really for the most part have a primary news source and The obvious to me like the obvious sort of mainstream sort of news experience is
that it's very personalized It's very tuned To, the, to the person's sort of interest, maybe to their proclivities and ideological, biases, or just beliefs.
And that it is delivered in the format that the person, the user or the audience member, like consumer, I guess, prefers, the idea that it's going to be packaged by a bunch of, you know, newsrooms seems.
I don't know.
I don't know if it's arrogant.
It just seems like sort of outdated, like, okay, there's some people who want the packaged version, but there's some people who are going to, you know, package it themselves, right?
Like, I mean, that, that seems obvious, or just like an obvious end point.
and
Pete: think,
Brian: don't know what, what is, what is your sort of take on that?
Is that sort of how you see things going?
Because I just like wonder, do you see things out there that point towards this?
This agentic future for, for news.
Pete: yeah.
So I'd point to two different trends here, which are kind of one is they're almost like the opposite of
each other, but they're actually, I think different ingredients of, of what this agentic future might be.
So one is just all the deals that we're seeing with all, you know, open AI and others, mostly open AI right now with publishers, and it's always kind of like the same group.
But it is sort of happening, right?
So it's like, you know, whether it's, News Corp and everyone else and Reuters, et cetera, you know, we're starting to see that with Meta and Microsoft too now they're, they're making these deals.
So what this sort of, you know, portends to me is like, oh, there is a model emerging, but in the, in the initial sort of phase of it, there's going to be a certain sameness.
To what you get, that is news on a lot of these AI interfaces.
And I think there's this counter trend that people don't want that, you know, and this is why I like sub stack and, and individual creators.
while, while, while that sort of summary of sort of what's going on is helpful, it's like, what I really, what I really want is.
The, the news and points of view from the people, that, that I want, that, that, that I'm following.
Right.
So the other trend is, is really counterintuitive, but I would point to the popularity of notebook LM.
And what that is to me.
Is yeah.
So, so Google notebook LM, it's actually been out for a while, almost a year, I think when Google first released it and it's essentially like a folder.
And the way I sort of talk about is like with chat GPT with, with your.
Interaction with AI prioritizes the chat.
I mean, you can attach files to it, your chat.
that's fine.
What notebook LM prioritizes is the files, like the data you're giving it and the chat and the AI interaction is sort of secondary.
It sort of flips the script.
On the chat bot, which it was a super brilliant innovation.
because what that empowered and what really put it on the map is the idea.
You can take that data and reversion it into whatever you want.
And their, their big product was podcast.
Hey, let's have a couple of chatty people talk about the data we have here.
Brian: And they're very human sounding, by the way.
I've talked
Pete: I did a great job
Brian: They're, they, they, I mean, they, I, I've mentioned before, I have this like thing.
I like keep like like a journal, I guess, of like, of stuff I'm thinking about with the business and beyond, but, I do it like every day.
I, and you know, I'm a writer, so like I, I have a lot of data, like over the last couple of years.
It's very strange to listen to a podcast that talk, talking about you.
Pete: I couldn't do it.
I haven't done that yet.
I've thought about it.
I think I inevitably will.
I've got a bunch of notebooks
Brian: They're very nice.
I mean, AI, I will say this AI engine, they have tuned them to be suck ups.
They're all suck ups.
They're never going to tell you there.
So I think that's the problem with the, the sort of truth thing and trust thing, because like.
They're too, they're too positive.
Like when I ask, like, you know, Oh, can I make a, this dish with this?
This they're never like, no, that's terrible.
Like that's a terrible idea.
Like,
Pete: There's actually like a few actual podcasts you can get in the, probably more than a few in like the Apple podcasts app that are just notebook LM feeds.
And if you listen to a bunch of these together, like, like a few, you, you start to really feel the weakness of this.
It's like, Oh, it's really cool that they're conversational, but
Brian: it's a parlor trick at some level.
I mean, even the perplexity perplexity has an AI, like, you know, summary.
News podcast, podcast product.
And it's kind of dull if you ask me, but look, I think a lot of this points to, and this is where I want to get at with, with how you see newsrooms and publishers using this technology.
because look, it's good at summarization and it's good at versioning and to me, and it's good at pattern matching.
So if you look at the, Professions, the areas that have been affected the most.
obviously developers, you know, that's the sort of home run use case.
It has not replaced the writers.
Weirdly, it is, it is, you know, putting pressure, downward pressure on, on developer jobs.
It's good at coding because it's good at pattern matching, right?
But when it comes to, you know, content, speaking broadly, it's, it's it's good at summarization.
Like, I mean, I, after, after we do this podcast, I'll download a transcript and I'll ask it to summarize it.
It will not write it for me.
I think a lot of times people get to the output, but like, honestly, like my own summarization skills as I get older and I do more things like are not as good as, as they used to be.
And so it will catch things that I would probably not remember or have to go back.
And so that saves me, I don't know, like, you know, it's like 15%, 20 percent of time.
and a lot of.
A lot of content that is created is some form of summarization at the end of the day, or the existing product, it, it, you know, the, the atomic unit
of news, which is still like the sort of article for, for many publishers, you know, can easily be summarized.
That's why, that's what I see a lot of publishers, they're pointing at it to, to do the three bullet points.
Which isn't exactly inspiring.
Pete: yeah, it's like everyone's using it to kind of do axios almost right where whereas axios kind of like almost reduced the atomic unit to something arguably even smaller than an
Brian: yeah, yeah.
400 words, like, and bullet points in the, in the bold.
Pete: yeah, but I would I think notebook LM suggests to me.
Is that the, the, the innovation of doing it with the data and then doing this, whether it's a podcast or, you know,
whatever your preferred way to consume that data or get an overview of that data is, the data can be whatever you want.
You know?
So what if it's like all the things that you actually do care about, like basically bridging the idea of like, Oh, all the things you follow.
Somehow putting that in a sort of notebook LM idea and then just getting it.
Summarize for you.
And that's, that's the agentic future where you have these sort of news agents on the consumer side of this going out,
like, give me all the stuff that I care about, summarize it all together and give me that, that daily brief, however it is.
And we're kind of there, right?
Like, I mean, open AI just came out with operator.
which is their computer use thing.
So it's essentially, it can take over your computer or, or work, even work in the background and just get stuff or you, whether it's, you know, ordering the pizza
or the flight or hey, summarize all these stories on, newspapers or whatever and the times and, and the journal and you
Brian: Well, you can, like, set it.
You can say, hey, every morning, I want to have like a summary of, you know, this topic, this topic, and this topic use these, these sources, et cetera, or, or just leave it up to them.
And I can see that being a very compelling use case for most, for not most, for a large chunk of consumers.
I think sometimes those in the news business that are particularly those that are extremely online, And are
constantly consuming news, don't recognize that it is simply not a major part of most people's lives.
you know, they would, we would call these people like low information voters, whatever, guess what?
They're the majority, you know, and in some ways it's kind of sensible, you know, the news product itself is.
To me, it's not in a great shape.
You know, the user experience is, is, is horrendous on a lot of these sites.
a lot of, you know, these, these stories are like too narrative driven for, for many people.
I don't think a lot of people want your storytelling.
lot of people just want to know what's going on in the world.
and real or perceived, there's, there's, there has been a lack of, of trust in some of the bias that, many people believe has, has cropped into the, the news product itself.
so I wonder how AI can be used and, and specific examples that you see to improve.
The, the, the product, right?
Like, so I talk a lot about how publishers are downstream of tech.
And I guess what I see out there, and maybe it's, maybe I'm not seeing as much as I should.
I don't see publishers sort of looking to innovate.
You know, putting a chat bot on your site, it to me is like, okay, great.
Like, I mean, honestly, like who's using them when you start to ask for usage, you know, then, then the conversation gets changed.
because I, to me, the obvious thing is like, yes, it's very good at summarization and piecing things together, but that just points to multi source.
Like, Outside of a few use cases, particularly like around finance publishers, you know, a Bloomberg or something that has unique data sets.
I honestly don't see why I would, if I wanted to have a summary every morning of Trump executive orders.
I don't understand why I would want it just from the Washington Post.
Like, why wouldn't I want Politico and all these other sources, Punchbowl, etc.
Pete: Yeah.
And that's kind of where I don't know if that user experience innovation can even be achieved at the publisher level.
Like, yes, you're right.
You're going to, you're going to see these chatbots.
Some are going to be better than others.
Some summarization is going to be better than others.
but there's a couple of barriers, to, to it being like this great experience, one is just like you said, the availability of content, you kind A more of a broader view from, from multiple sources.
Another is that publishers are rightly very concerned about accuracy.
And there is a Still like hallucinations are just inherent to the technology and yes, you can reduce them.
And yes, there are, you know, safeguards you can put in place, but generally those safeguards and the publisher
side anyway, have been so restrictive that, you know, the Washington post chat bot just won't say anything.
If you go anywhere near, like outside of the guardrails, it has, times AI, which I actually like, I actually write like their UX, and, and how they've.
presented on person of the year But the thing is those summaries that they did of the person of the year you could tell They weren't generative or they in
other words, they were generated yes, probably by ai but they were also vetted by an editor because every time you would go to the Smaller medium version.
It was exactly the same word for word, which says, Oh, it's not actually doing this on the fly, which means it can't scale.
You know, you couldn't do it in the way that we're talking about, where it's totally tailored to whatever the user is doing at any given moment.
Now, tech companies are much, well, shall we say less concerned with accuracy, unless they're bullied into
it, like, like Apple was, you know, Apple was bullied into dialing back their notifications
Brian: yeah, but, like, also, like, that's a great example, you know.
Apple was using these AI summarizations of news and it was screwing it up.
And, you know, they just like kind of rolled it back.
They didn't get like a ton of like blowback that I could see.
Like, I mean, like things just kept going on.
Like if like the New York times did that, there would be like a million VCs with pitchforks that were blaming DEI or something for it.
So it's like, you can't win at some point if you're a publisher.
Pete: Yeah.
So there's kind of a level of, and also like the, the idea of hallucinations, the fact that it's not a human doing it, like it's similar to the self driving car problem where even if.
A self driving car is demonstrably safer than humans, driving cars.
And I don't know if we have the data on that, but that's the supposition, right?
the fact that a self driving car even kills one human, you know, even if the aggregate is lower because of this sort of phase we're in and it's new, it's, it's much more serious.
Uber, Drop their, self driving after that, accident.
I forget where it was, but, so, so I don't know if like hallucinate, like it's an analogy, like you get, what I'm
getting at is if a publisher screws up with hallucinations, again, even if it, the error rate might be lower than humans.
The fact that it's this AI doing it and there's sort of this mistrust.
I don't, again, I don't know if it's ever going to be able to cross that threshold of being accurate enough that they're going to apply it at scale and be confident.
You know, that's, that's kind of the thing that, might hold back, like them being able to sort of control their own destiny, because like I said, the platforms will apply this at scale.
And, the next one that I think will be really interesting.
Is Amazon because
the yeah, well, it's because Alexa is such a bad product compared to chat GPT right
now.
And again, I'm not sure what they're going to release.
They're obviously going to release an AI version of Alexa at some point.
Maybe it's, it's going to be like a big question.
Is it going to be more like apple where it's very underwhelming and doesn't really do much, or are they actually going to go for it?
Are they going to go for like a real chat GPT interface?
And if they do do that.
I could definitely see Generative summaries of the stuff you care about in a conversational way.
Like, like that could suddenly become a real thing people are doing.
Cause a lot of us still have these microphones all over our house.
Like I do.
Brian: I I've never it's funny because like I remember When they came out with that we were doing like flash briefings at the time for and the idea was like people
are going to Be ordering their groceries off these things and like I think they're just sitting there and are just like
Pete: Giving us the weather.
Brian: At this, yeah, it's like parlor trick.
You know, my parents are always like, you know, asking like Google to tell them what the weather's going to be.
But like beyond that, it just seems like kind of an underwhelming product.
And then we just sort of move on and forget about all the hype that it was going to change everything.
but with, with which.
Which publishers do you think, like, give me examples of publishers that are actually using AI to create compelling, products at the end of the day.
Pete: Well, products.
Well, the post and the times are both
Brian: It can be features.
I'll even take a feature
Pete: I think the post and the times are doing some good stuff with investigative.
That's not quite a product, but being able to process a lot of data and do a better investigation.
Yeah.
That's good.
again, I said, like I mentioned, time AI, I think is, is a good experience, because it makes it a nice sort of Chipotle style menu of what you're getting, as
opposed to this chat bot, I don't think chat, even as much as I'm a pro chat person, I don't think it is the thing.
That's going to turn, you know, publisher, experiences into something amazing.
I do think it is helpful to have chat so you know how to play in AI, and get some good user data on sort of what people who are actually coming to your
website care about, and, and that'll help you sort of play in these bigger summarization engines, but I, I agree.
It's not.
It's not the best product for everything.
but that said, I do think a certain amount of, I don't know if anyone's really doing this, but it's like chat, on the article level, you know, where it's like, Oh, like, what are the places I can go deeper?
And get sort of follow up questions about, you know, like, like that's, that seems like the place for chat for
me, you know, it's like, okay, I've, I've read this article and I actually want to go a little deeper on it.
And rather than going back to Google, maybe there's something here that points me somewhere.
I'll, I'll give sort of a, can I give an anti good products?
I guess, which would be, so there was a lot of hype around particle,
Brian: Oh, yeah, I was just looking at that.
Yeah, yeah.
I mean, that's like a former Twitter, executive started this sort of AI news, summer summarization, app.
I mean, news aggregation apps.
I don't know.
There's, there's a graveyard somewhere that's like filled with like.
Circa and all of them, they, for whatever reason, they, they make a ton of sense.
but they've never really taken off outside of existing aggregators.
Just putting one, like if you have, if you're already aggregating, if you're one of the choke points of the internet,
if you're, you know, Google with Google news, okay, you know, Apple, Apple news is like, has emerged as just a massive.
force, but that's, You know, that's just the second order impact of controlling distribution.
That particle doesn't have that.
Pete: right.
Yeah.
And I find, I just find as a design, like it's, it's really busy, you know?
Like it's almost like the design is anti.
AI in the sense that AI was supposed to simplify things and summarize things.
And I tap into a particle summary and it just has like a bunch of different fonts and colors.
And I'm, I'm like, well, what's the path to the story that I actually want to read about in this summary?
And I can't find it.
Like every time I look,
Brian: It's very
Pete: just go back to Google.
Yeah.
Brian: would say it's very branded rather than just like bare bones.
And you look at like, what is, I mean, even the sort of positioning of a lot of these, AI, products is, is very, I mean, it's very.
Like ChachiBT is like incredibly bare bones.
And like, it's also, you know, I don't know if this is intentional or not.
Like they don't abstract the, like the, the speeds and feeds part.
That's what we used to like, call it like intact coverage, but like, you know, it's like, I got to choose which model
and like, you know, you go and you're just like, I can understand like, to me, It's going to hold back adoption.
Like, I mean, convenient, always wins and, and simple always wins.
And the idea that I need to choose which, which model I'm going to use.
I mean, that's like CB radio land.
Like that's not like, you know, people don't want to do that.
I think I feel fairly confident in speaking for humanity.
Pete: Oh, totally.
Yeah.
It's not going to work, but yeah, like features, you know, I mean, the spoken articles thing was kind of a, a level one.
Of what's happening.
And again, I'm not sure how comfortable publishers will be doing this, but like in applying like a notebook LM style to a batch of coverage, I think
that's sort of the logical next step of like, I don't want to hear just like someone speaking this article to me.
I want like a conversation and sort of a summary and overview of that.
I think that's kind of inevitably going to be coming.
it's just a matter of like, can they scale it?
Will it, will it, will it be something that, that, just becomes a standard way of we consume something,
Brian: Yeah.
And I think one of the, the, the big, one of the big outstanding questions, right?
Is how AI is going to drive productivity, right?
And you can look at productivity two ways, right?
One, you need productivity to drive economic growth.
It is just how labor productivity is how you drive economic growth.
So if you're not against, if you're a de growther, you can be anti productivity, but I think most people are not de growthers.
and on the other hand.
There's a lot of unease because, you know, driving labor productivity means, you know, fewer overall jobs.
That's generally why, you know, historically, you know, for instance, like unions have tried to hold back automation
and all kinds of different technological advances that, you know, from on an economic level, drive, drive productivity.
So that's a good net net good.
Because it means that you can deploy those labor inputs to more productive endeavors, at least that's the theory, right?
But generally, you know, people do not like change when it is visited upon them.
They usually like change when it, when it affects other people.
I've noticed it's kind of like accountability.
It's much better for other people than ourselves.
Who is like, so how did, like, obviously news organizations in particular, but publishers overall are under pressure to do more with less.
I mean, we've seen like cuts like nonstop, right.
And you know, AI has, you know, at least the theoretical, you know, benefit of doing just that.
I mean, I think.
I would say for me, it is like a 10 to 15 percent these various tools added up together increase in, in productivity.
It's not like, I think a lot of times, again, like I say, people go to like the writing of the stories, they want to just hit a button and things like happen.
And like, I don't, maybe I just haven't found that button or just been able to hook things together, but that ain't the case.
Like it will, it, it is, it speeds the.
You know, the, like the production of this podcast, right?
Like that, it absolutely, you know, helps do that.
it helps with, you know, if you use Grammarly for like copy editing.
So
Pete: Yeah.
Brian: who ends up, I mean, you've written about this before.
it would seem like all of these things, cause we're seeing already, like.
This exists within the context of, you know, organizations are, are slimming down, particularly in the, in the middle management layers.
Right.
And you don't have as much of, of that, in, in most publishing organizations, just because, you know, the business is, is not such that you can run it like Google for sure.
Pete: Right.
Brian: but like.
It would seem like this would empower the people who are making the content to do more, right?
To be able to to to be more productive, right?
but that some of those Coordination I saw like described as glue jobs Will end up Being affected quite a bit by, by AI tools and technology.
Pete: Glue jobs, like assistant editors, copy
Brian: Yeah.
So like, you know, you're moving data around, you're doing some kind of coordination role, obviously anyone who's been inside, a news organization
can tell, like, you know, the people actually making the content are a minority in, in these companies, right.
And that's because there are a ton.
Of coordination roles, if you're going to take subscriptions, you're going to have a saves team.
You're going to have a growth team.
You're going to have all of these.
And it adds up.
It's a lot of people to run a publishing business.
I think that's what this sort of reaction to that is.
You know, in the area we're both broadly in, right?
Like, it's like you, you slim it down to like the bare essence and, you know, you can, you can, you might not be
able to do as much as, you know, people with 75, 100, 200 people, but like you can cover a lot of ground these days.
Pete: Well, I also think in, in a lot of places, there's going to be a sort of, a small, not a select few, but people in the newsroom who are really embracing.
AI tools are kind of going to build their own glue.
So I know a bunch of people who are in newsrooms who are kind of, they're not coders, but they're maybe AI productivity enthusiasts.
Right.
And they, what, what I find interesting is that it's almost this merger of editorial and product now.
And I think that's kind of a reality going forward, that those two things are going to be much closer and in some roles, you Almost a dual role.
Like I know a bunch of editors now that spend a lot of their time building tools and maintaining those tools.
So, yeah, this one publication that it's more regional and a lot of the reporters, who are covering various things like the courts and, and recalls and whatever are.
used to spend a good chunk of their time in the morning, like, you know, figuring out what's going on in all these things and, you know, go to the right government website, et cetera.
And like, what's changed, what's the case has been updated.
And now they, alongside, some product stuff have, have built these tools.
Again, like no code tools.
They don't know code.
They're just taking some off the shelf platform, plugging in some generative stuff and doing it in sort of a left brain kind of way, which And now that's, that's done for them.
Right.
And, and, again, like not, not normally, like, you know, a few years ago, you'd get your product team to do it.
If it even fits on their roadmap, you're like, yeah, we'll do that someday.
Maybe it's six months, a year down the road, et cetera.
and now there's a lot more sort of empowerment of, of just sort of doing that yourself.
So, so that's kind of a neat development.
It does mean for certain roles.
You're going to be like that, that 10 percent efficiency isn't necessarily getting realized in the, the story building.
It's more in sort of the, the infrastructure building of, of the place.
But I think it sort of generally levels up, Of everybody.
But yeah, I think a big question is like, what do you do with that?
10 or 15%, right?
Like, you know, in roles I've had, you know, do, do you want the people to go deeper on certain things?
Do you want more stories?
Like what's going to have the most impact, to, to the publication and like, and sort of in today's environment, I
think it's like going deeper, you know, like it is like, you don't want to necessarily want more stuff out there.
You want just better stuff for your audience.
So yeah, it kind of depends on what you're doing, but
Brian: You know, like I mean, for instance, like, I'm doing an online forum later this week, with, Newsweek and, you know, they've used AI and other, you know,
tools to double their output basically with the same, With the same amount of staff and, you know, that like, I think, you know, I'm going to talk to, to them
about it with the chief product officer, but, you know, the reality for a lot of these models is you need, they still need to talk, they still need traffic.
In their models, like, and it's easy to say, Oh, it's about death, not breath and stuff.
But the reality is, like most businesses, you're operating your existing business and you're trying to build the next business and you can't, you can't just put the existing business on pause.
you're going to have to, so I, I have a lot of sympathy because there's a lot of pressures in, in the marketplace, obviously, and, you know, it depends on your model, but a lot of models still need
to efficient ways to, to create, To create traffic so which which leads me to the search thing and I want to just you know Close with a little bit on that because you know, obviously the big concern
for for publishers is is the change to search and You know, I think sometimes it can be Both underplayed and overplayed underplayed in that the search is so central to Many if not most publishing
models it has been The not just the dominant but the most stable algorithmic Distribution source for, for, for audience and, oftentimes very high quality, right?
Compared to a lot of the kind of nonsense audience that you, that publishers would get
Pete: Yeah.
And it's, it's death has been exaggerated.
Brian: Right, because it is still Google.
I saw one, you know, the stats are kind of difficult to get in there, but I saw one saying, Oh, Google finally dipped below 80 percent share for the first time in like nine years.
You know, and it was like 79.
9 versus, and it's like.
Okay, that seems pretty dominant
Pete: think it was actually 90, you know, it was like, you know, there's, it's, it's just so dominant.
Like, it's like, okay,
Brian: You know, so we're, I mean, like we talk, we use like perplexity and these kinds of things, but, you know, regular people are not for the most part.
I mean, they are yes, but like in the broad sweep of how dominant search is, this is, this is chipping away and,
Pete: I also tried to switch to an AI search as kind of my default.
I couldn't do it.
And I think it's because if you're extremely online and you, you just develop this rhythm with Google as like, you know, firing up a new tab and getting links
Brian: you know, it's everywhere.
And so we'll see if the, we'll see how, how the Trump administration deals with some of the leftover antitrust cases.
Pete: Oh, yeah, true, but it is kind of a, just a thing in terms of what I want when I search the internet or want something from the internet, most of
the time I'm that processing that AI does, I can actually still do faster with a search results page when just my head, like, Oh, here's the link.
And that I was actually looking for in the first two, it kind of depends if you're looking for information or something very specific, like a destination.
Yeah.
Brian: But when, I mean, I think the big sort of concern that I hear all the time is, you know, search has gotten less reliable, AI, the whole promise of these chat bots is to return just what
you're looking for and not like, The publisher web page on a search, result is often just an intermediary to what people, you know, want like, you know, I,
Pete: Yeah.
Brian: the search yesterday about which street streaming the Eagles game.
I ended up on a USA Today.
Yeah, horror show of a page.
No offense to my friends at Gannett, but like that is not a page I would want to take to the sort of UX Hall of Fame That's just filled with it was basically a Fubo ad, but it was just filled with junk to
try to get through to And I get it I get everyone has to pay bills But nobody's gonna nobody's gonna protest that that stuff goes away Like I don't think so
Pete: I mean, agreed.
It's like, you know, it's an existential thing for publishers that AI search, you know, is going to essentially substitute what they're doing.
And I, but I think once you get sort of to more granular level of what they're actually serving up.
You find that some, some types of content are more at risk for being substituted than others.
Right.
And you know, like, that's kind of what I was getting at with sort of the sameness of things earlier in, in
terms of these AI summarization engines sort of, and that's partly due to the licensing deal, but also partly like what.
AI is good for like, we're always going to want to on Saturdays go, you know, settle in with a podcast or a
feature article or our favorite writer, our favorite sub stacker, and just, you know, kind of go deep on that.
and AI's might be good at sort of pointing you to that.
And to some extent.
Even, some discovery within a summary, if you find something interesting that you want to go deeper on, but
for, for the most part, if you're just kind of like, okay, I'm busy, but I need to know what's going on.
You know, AI, AI is an amazing, tool and, you know, like to your point of like the publisher experiences and a lot of these websites, I mean, it's, it's kind of a
better experience, if you, if you don't need to do anything deeper than, than what, just a summary of what's going on.
So I think it's absolutely going to become a greater and greater part.
Of just how people get information.
And it, the reversioning of it, I find interesting because if you think about how attention is now so spread out over various apps and putting
aside, like the Tik TOK ban sort of not withstanding, you know, some people just like want to scroll all day on Tik TOK and kind of get their noobs that way.
And, you know, whether that's YouTube shorts, whether that's, you know, podcasts, And, and then this is something that I've written about too, and I don't have the answer to it.
Like how much does human authenticity even mean in that experience?
Do you care that that avatar you just saw on TikTok?
Was actually AI, if it's, you know, something relatable and, and gives you the information and experience you're looking for, maybe, I mean, it,
you know, again, it, it, it, I think in terms of the way people consume things and what I was just talking about, I think it matters a lot less.
For your day to day stuff and matters more for that stuff you're doing on Saturday.
Brian: Yeah.
I mean, already, Pew found that, 39%, of people 18 to 29 get their news regularly from, from TikTok.
So I mean, the patterns are changing already and AI to me is just a giant accelerant to a, to a lot of those.
what about the lawsuits, right?
I mean, it's 2025, the year when.
Not just the lawsuits, but like coming to some kind of economic understanding, right?
Like I mean there we've seen the smattering of Ai deals like these are just with you know a few Obviously publishers not the mass number of publishers out there I regularly ask publishers and, and
about using the, the, the, the different like toll bid or pro rata, like in order to basically position themselves to, to get some kind of economic value.
Most of them are just like deploying the tool because it's free the tools because they're free and like sort of monitoring, which means they're not doing anything about it.
And, you know, there is, again, we are always left in a could might in the future.
You know, we're going to be able to, you know, bring some kind of economic value out of these, These AI answer engines, because breaking in some
ways, the bargain that underpinned Google search, which was, we're going to let you crawl our webpage webpages.
We're going to let you scrape them.
even though if Google won't claim it's scraping, but they're scraping data from those, those webpages and they're.
Putting it on their website and a search results.
And the bargain is you're going to get traffic that you can monetize.
And by the way, you're probably going to use our tools to monetize it.
So we're going to get a taste.
that's off.
I mean, the, you know, perplexity for instance, said, Hey, robots, robots.
txt, which is, you know, the, The little code that basically told Google and other crawlers, stay away from these pages.
you do it like for transaction pages or pages of personal data, et cetera.
But you know, you always had that option.
You could opt out of the system and you know, perplexity, which interestingly, their CEO has kind of turned into a little bit of a heel in this drama, which I think is just where Silicon Valley is now.
I know something about that guy's off.
So, you know, they're just saying, Hey, we're not going to pay attention to this.
So are we going to see any sort of understanding at all this year of how the economics to all this work?
Because a lot of these AI, you know, the vision for these things break the, the economic model.
Right?
And, and look, Silicon Valley, that's their thing, you know, move fast, break things, et cetera.
They love breaking other people's economic models, not their own.
so are we going to start to see some kind of understanding about how, how the economics work out?
Because, you know, you can get into the doom loop of like, well, there's no economic incentive to create content.
Like it will not be created.
And then it's going to be filled with junk, et cetera.
Pete: So one thing, so I'm not, obviously I'm not a hundred percent sure how this is all going to work out, but one thing I am sure of is that there is a consensus
building, that might actually already be taken over, which is that if an AI engine is going to ingest a publisher content and then summarize it, that.
Is the industry is deciding that's more like syndication than search.
And this is, I'm talking mostly about the real time stuff, right?
Not putting training data aside.
Like if you're summarizing news, if you're summarizing stuff, that's out
Brian: yeah, they need direct payments.
The indirect stuff does not gonna work here.
Because it's just, it's like, I don't know, little citations.
I don't, it's not gonna work the same as search, I don't think.
I know Google says that people, you know, they're driving as much traffic.
I just, it, it's just hard for me, cons, using these, these services.
The entire point of them is to not have to go to all these websites.
I mean, like, come on, that's the, like, that's the USP.
Pete: And we're starting to say like Google's kind of stayed away from news so far.
left it to chat GPT and perplexity, but we've saw the first hints of them, they are moving in that direction.
And, and obviously that's gotta be on the roadmap that this, they're going to apply generative summaries to news and Google news at some point.
and you know, that's obviously going to be a big Bomb that lands in the industry when, when that happens, but they'd started at CES,
they announced for their Google TV platform, they would start summarizing, giving sort of some basic summaries.
I don't think that product's out yet, but that, that was one of their, big announcements.
Brian: Yeah.
Wait till they start to stitch together, like, you know, video of, you know, different newscasts and, and YouTube and like, Oh, that sounds like a pretty good, and sounds like a doable product.
I mean, I'm not an engineer, but it seems, it doesn't seem so farfetched.
Pete: you imagine those Notebook LM people as, as avatars, right?
They're just going to be people that are just chatting at a, at a news desk or, you know, in the field somewhere.
but so, so the thing is with these deals and the lawsuits, so far it's only the big players, if you're a small player, yes, you can go to a toll bit or a Dapier or any of these other sort
of startups that are trying to create this, you know, the problem is that they haven't really gotten the attention of the big AI guys yet in a major way.
And my sense is they won't until the sort of people at large, demand it.
In other words, like someone's got to crack that user experience where, Oh yes, I want, My news this way, and I expect it from you chat GPT and everyone else.
perplexity, again, perplexity is sort of a different animal because they don't do licensing, they do rev share, obviously they've gotten into legal hot water over that.
With News Corp and, you know, we'll, we'll see how that all plays out.
I got to say, given my, what I sort of just said about the consensus emerging, I, I worry a little bit about perplexity.
I do think kind of their, the sheen of that service, which was kind of a darling about a year ago and everyone was admiring as kind of worn off and they're kind of throwing spaghetti at the wall
Brian: Well, this TikTok thing, that's, that's, that's where I, I like, I, I,
I'm like, I'm out.
I'm out on this guy.
I mean, there was two things.
One was when the, the CEO during the New York Times tech worker strike said, oh, we'll take over your server.
I'm like, eh, I, I, that just struck me as just this Silicon Valley buffoonery from all the money being thrown around there.
I was like, this guy's too big for his britches.
He's not focused on the right things.
And then there's this talk of.
Of taking over Tik Tok and, and it being half owned by the government, because obviously perplexity does not have a control distribution choke point.
So it's just some random app that people have to download and, and the.
Just the deck is stacked against it, know,
Pete: yeah, it's, it's a, it was an odd thing to do.
Obviously I think it was more of a publicity stunt
Brian: that's what I mean when people are doing publicity stunts It's just like I listen to a podcast the the it was actually prescient.
It was a more or less the podcast and Sam Lesson was saying anytime people are are Getting excited about spending money versus making money.
It's like be very be very concerned So I think we're seeing that in the stock market
today, but
Pete: the thing is I wrote about this too.
I do see kind of a, I guess a synergy there to pick a terrible word.
It was kind of like, you know, if, if TikTok has this AI connection, which, you know, it doesn't really have an AI strategy right now and has this connection, to perplexity.
That can, you know, it's users actually kind of find useful.
I'm not sure what that would be.
I could see that, that sort of working out for them in some way.
Like I said, they sort of instantly have kind of a, an AI strategy that's specifically about surfacing, good summaries and pointing people to the right.
information if they want to go deeper on something and then obviously TikTok, the benefits to TikTok are, are huge because, you know, you're just exposed to all these users.
will it happen?
Um, probably not, but it's, you know, it's, it's an interesting thing to think about.
And even if it's not, even if it's not perplexity, it's kind of like, well, Is there, is there some AI solution that takes TikTok to some other level?
Anyway, TikTok's got a lot of problems.
Doesn't, I don't think it has to worry about its long term strategy, until it's sort of figured out this, this whole situation with the ban.
Brian: Okay.
All right, Pete, let's leave it there.
this was, enjoyable as always.
We covered a lot of grounds.
really appreciate it.
Pete: Yeah.
My pleasure, Brian.
Thanks for having me on.