🆕 Never Post! What Happens When Search Goes Full AI

Producer Audrey talks with Mols Sauter and Erin Kissane about what AI hallucinations actually are

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Links

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  French spies break with Palantir
• Palantir should be stripped of NHS contract
• Chile turned to China for an undersea cable. The U.S. said no
• The Millions of Songs Mashed Into AI-Generated Music
• Google's YouTube settles social media addiction case with teen
• Research shows Australia’s teen social media ban has little impact
• Study on effects of Australian Social Media Minimum Age Act
• Mr. Rogers' Neighborhood YouTube Channel Goes Live
• Little Dot Studios Buys Content Agency Wing
• German ruling says Google is liable for its AI Overviews' false answers
• German court holds Google liable for AI hallucination
• KPMG pulls AI usage report
• EY retracts study after discovering AI hallucinations
• Wikipedia bans AI-generated content in its online encyclopedia
• AI hallucination epidemic

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What Happens When Search Goes Full AI

• Search is over - Techcrunch

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Never Post’s producers are Audrey Evans, Georgia Hampton and The Mysterious Dr. Firstname Lastname. Our contributing producer is Kurt White. Our senior producer is Hans Buetow. Our executive producer is Jason Oberholtzer. The show’s host is Mike Rugnetta.

Never Post is a production of Charts & Leisure and is distributed by Radiotopia

Friends, hello, and welcome to Never Post, a podcast for and about the Internet. I'm your host Mike Rugnetta. This intro was written on Tuesday, 06/23/2026 at 10:35AM eastern, and we have a fantasmagoric show for you this week. In this episode, Audrey chats with assistant professor at the University of Maryland College of Information, Mauls Souder, and writer, researcher, and community organizer, Erin Kissane, about the incursion of AI models hallucinations into increasingly prevalent corners of media, law, government, and culture, and what this means overall for the production of knowledge. But first, we're gonna take a quick break.

You're gonna listen to some ads unless you're on the member feed. And when we return, we're gonna talk about a few of the things that have happened since the last time you heard from us. Zephyr in the sky at night, I wonder. Do my tears of morning sink beneath the sun? She's got herself a universe gone quickly for the call of thunder threatens.

Six stories this week. France says to Palantir. French PM Sebastian Lecourneau announced last week that French intelligence agency, the general directorate for internal security, would be cutting ties with the techno fascism purveyor in order to reduce reliance on American technology. Lecourneau says the gap will in time be filled by French AI developer, CHAP's vision. This comes as England's NHS, the National Health Service, considers ditching its Palantir contract under pressure from MPs and workers alike over privacy and security concerns.

Now I don't wanna speak too soon here, but I'm starting to think that maybe Palantir is bad.

No.

China has been increasing its global telecom presence in South America. The most recent partnership offering being made to Chile. State owned China Mobile offered to construct an undersea cable linking the two nations. But in February of this year, rest of world reports, The US stepped in and sanctioned the South American nation, revoking the visas of three officials. This after a similar 2019 scheme was kiboshed also due to US pressure.

The state department has said the infrastructure projects would have, quote, compromised critical telecommunications infrastructure and undermined regional security in our hemisphere, end quote. The US and China remain engaged in an ongoing data center and AI development arms race that pretty much no one has asked for or benefits from. We. Music, all of it has been ingested by AI. Writing for the Atlantic, Alex Reisner reveals that he was able to get a hold of four training datasets to give a sense of their size.

Only one is comprised of 12,000,000 tracks that would take 91 to listen through. AI developers and researchers employ these datasets to develop their products, though some, like Suno, say there are guardrails in the technology to prevent against the models generating faithful or near copies of existing music. Reisner writes quote, what the datasets illustrate primarily is the scale and variety of music easily available to AI developers. Companies often claim to use only content that is freely available online, but the datasets reveal the quantity of downloadable music that developers can access even though it is not supposed to be free, end quote. The dataset is searchable if you wanna go see if your work has been gobbled up by the endless ravenous maw of Silicon Valley.

YouTube has settled a Florida case in which a teenager named r k c in court documents alleges the platform was designed to be addictive leading to anxiety, sleep deprivation, and other ill effects. R k c is also suing Meta, TikTok, and Snap in California according to the BBC. This comes after a string of various settlements and findings in users favor regarding the deleterious effects of features like infinite scroll, algorithmic recommendation, and so on. Most notably, six months ago, Australia banned teens from using social media entirely countrywide, a massive undertaking which researchers in the British Medical Journal this month note has been particularly ineffective writing, quote, we found insufficient evidence to conclude that exposure to the act had any early substantial effects on social media use among adolescents aged 16 years. The findings contrast with similar legislative requirements of web based services.

For example, in The UK where access to pornographic websites substantially reduced by 30 to 50% following the introduction of age assurance measures, end quote. Whoops. Oh, well, I guess. Oops. Mister Rogers is on YouTube.

Okay. Maybe it's not so bad out there after all. The channel will feature clips as well as full episodes many of which have not aired or been otherwise available for quite some time. The Fred Rogers Foundation has partnered with British digital content agency, Little Dot Studios, which as of 2020 managed over 600 branded social video channels for various clients. Won't you please?

Won't you please? Please won't you be my neighbor? My neighbor? I'm glad we're together again. And finally, are you seeing what I'm seeing?

Hallucinations in the news. At their recent IO conference, Google unveiled their redesigned search product in which results are delivered not as a list of links, but a chat with an LLM. Searchers have found this experience increasingly prevalent as the company has rolled out its AI overviews. Summaries of search results aimed at synthesizing available information without requiring additional clicks. But there's one problem.

Well, there are actually many problems, but one is the well documented prevalence of overview hallucinations, which recently a German court has ruled Google is liable for. The ruling describes the overviews as quote, the defendant's own statements. It alone has influence over the AI's offering and the algorithms with which the AI operates, end quote. Google's got good company in its hallucinatory woes. Number Cruncher's KPMG had to recently retract a report titled of all things redefining excellence in the age of AI because it was riddled with errors and inventions.

Ernst and Young recently retracted a report on loyalty programs because it contained hallucinations. Wikipedia has unsurprisingly had to ban AI contributions because they are often factually incorrect. And it feels like every week there's a new story about a law firm caught using AI after citing some nonexistent precedent. What is going on? How do we understand and protect ourselves against the incursion of opaque machine invention into what have otherwise been the most calculatory, document dependent, and knowledge based industries.

And what if these hallucinations are not a bug, but a feature? A fundamental aspect of the technology revealing in some way what it really is.

Uh-huh.

We're gonna take a quick break, and when we return, Audrey talks with Malz Sauter, assistant professor at the University of Maryland, where they teach the history and philosophy of technology, and Aaron Kissane, a writer and researcher focused on knowledge and networks at unbreaking.org and previously, the COVID tracking project. They'll all talk about what AI hallucinations actually are from a knowledge production standpoint and how the information they contain reflects a much longer and stranger facet of human culture than you may have previously considered.

In May, Google announced that they are turning from legacy search, the search box, to AI search as the default search mode. A May 16 TechCrunch article even had the headline, Google search as you know it, it's over. The ground of the web is shifting. The very way we step into our interactions with the web is changing quickly. Google suggested this as a quote paradigm shift, moving users from search into generative UI experiences.

So instead of returning links, Google search will now be dropping users into quote AI powered interactive experiences and be dispatching information agents to gather information on a user's behalf. So search will now look more like a long back and forth conversation where the user will also be suggested prompts, directions. This is really dropping users into an entirely new research process experience. One even further intermediated by Google and driven by the incentives and priorities of this company. This paradigm shift that they're talking about is one that's now less about information retrieval as a process and now something that's geared towards prompting users to quote, take actions and actions that are going to be defined by their models.

I know both of you study the way we collectively use and synthesize information, how we turn information to action, sometimes collective action in our society. So I wanted to get your reactions. And Erin, it is such a delight to be here with you today. Mols, let's start with you.

This is a really interesting question because there are a bunch of different things that are going on both inside sort of what we'll call sort of like the AI this current AI moment, but also these different specific systems. So, like, let's just take the search bar. And I love that you specifically flagged the paradigm shift. Whenever someone says paradigm shift, I'm like, cool. Now we have to talk about what a paradigm shift actually is and what it what it means to have a paradigm shift.

And so what we can think about it as when did search stop being we get returned results that are pointers to things that exist, that people have written and they've put on the Internet as objects, and we find them via object identifiers. Two, we get a natural language response from a technical system that also points to sometimes these objects. It has some relationship to these objects, but it is not the object. It's not merely a referent. The point of the search bar is not to direct.

The point of the search bar is to answer. So how do we get this paradigm shift? And one of the reasons I think that it doesn't feel like a paradigm shift to us, the reason why, like, for the users, we're like, wait a minute. We're not advancing. This isn't an advancement.

This isn't better. I'm not happy about what is happening right now. I don't feel like my experience has become more, is it's not actually following what causes paradigm shifts. So one of the key things in a paradigm shift in scientific theory is the crisis and anomalies stage, which is when you've got the theory, it is not paradigmatic yet, you are collecting your experimental results, you're building your literature, you're building your advocates, you're you're assembling your team, and then you enter into that period of norm what we call normal science, which is when we've accepted the paradigm. Now we're just sort of like cleaning up around the edges.

We're puzzle solving. Maybe it's an even entering into an engineering mode where we're just sort of like, yeah, this is a thing that solves problems. We use it to solve problems. We're not necessarily discovering anything new in the normal science mode. But then we enter into crisis and anomaly stage when things stop working.

We start building up these little inconsistencies, these little holes, and they start accumulating to the point where the the theory or the paradigm can no longer sustain itself, and it enters into a period of crisis. And that's when things open up for a new paradigm. That's basically the structure of, like, how we how do we change these big ideas? And one of the things that is currently happening is the old ideas have never arrived at the crisis and anomaly stage. The idea that a search bar points you to resources was perfectly happy chilling out in the puzzle solving, like like, it's not science, but quote unquote normal science space where it's like, this is good.

This works. We're happy. We don't have lots of problems. Like, there are some problems, but they're not fatal problems. And they're certainly not fatal problems with the basic mechanism.

Instead, we have sort of this forced paradigm shift where a bunch of companies, and by a bunch, mean, like, four, are pushing an entirely new way of both interacting with the web, interacting with certain types of knowledge, and interacting with certain types of media. And everyone's reaction is quite expected where it's like, wait a minute. Wait a minute. We weren't ready. Like, we're not ready to do this.

There was nothing wrong with that in a fatal way.

I think it's it's impossible to overemphasize how hard some of these tech companies have been trying to make paradigm shift happen for years now. So, obviously, this is in continuity with trying to make metaverse happen, trying to make NFTs happen, trying to make crypto happen in specific ways. Not that any of those technologies did not exist, but none of them existed in the ways that the tech companies pushing them were presenting them to us. So especially given that a lot of the folks leading these technology companies were around for what I would classify as a genuine paradigm shift, the arrival of search, the arrival of what used to be the open web as a pretty substantial shift in the way that we interact with knowledge as societies. That actually happened and they figured out gradually how to enclose more and more of it, but then they kind of hit a wall.

I don't want to be fair to anyone, but to be fair, I will say the arms race of search has led to, I think many of us think, a degraded experience over the past maybe five to seven years sharpening more as we approach the present. And when I say arms raised, I mean, it's the the old school pre AI content farms and the way that the poor recipe bloggers just started adding more and more stories about their great grandmothers to the beginnings of all their recipe posts to try to get the attention. There was a lot of really peculiar sort of perverse incentive minuet happening that made search harder and harder to deal with. If you were really good at search, you could still figure it out. But for, I think, casual use outside of any given person's area of expertise, it did get frustrating.

But especially, Audrey, I appreciate you talking about the idea of taking action, moving everyone into increasingly enclosed knowledge spaces with prompts. It feels to me like we've rebuilt AOL, but it talks on one hand and that we're putting people into society wide wizards on the other, neither of which really constructs us as subjects with agency. So, obviously, I have, like, deep rooted philosophical problems with this. But I do think even though many of us might approach our refrigerators and say, I have two heads of wilted kale and three eggs. What am I having for dinner?

There is a pretty strong sense among at least the people that that I know who are not in this nerd zone that that is qualitatively a different thing than what we do when we try to, for instance, educate our children or learn about the world or do research or do scholarship. So there's a pretty strong pushback in some aspects, but it bleeds into this. Yes, but there's the convenience factor with a class of things that perhaps can be answered by a machine and we're perfectly happy with that. Having those two modes, which in our own lives shift in and out based on how tired we are, what we're trying to accomplish, where we are and we're trying to accomplish it complicates this a lot and backed a lot of people into positions where they're doing things that they perhaps wish they were not doing.

So those complications Erin brings up remind me of ideas I've heard you bring up before malls around ground truthing. Would you take us through some of that?

One of the things I find interesting about LLMs at a theory level and sort of at a philosophy of technology level is the ways in which they counter expectations that we have about what computers do. And that makes the reaction to them complicated. And this sort of goes along with sort of the ground truthing and the ground truthing problem, which is a big problem in LLMs. Because if you think about what LLMs are and how they're constructed, their ground truth is not our truth, our ground truth. Our ground truth is based on the fact that we have bodies.

They live in a physical environment. We have sensory access to that environment. But we expect a lot of things that we talk about in human communication, these bits of bits of sort of phonetic sound and text that we throw at each other, we expect those things to be related to that environment. That's our ground truth. We're like, this is these things have always coincided and when they don't coincide, that's bad.

That's a lie. That's a falsehood. That's a mistake. It's not what we want. Computers have a very long history of being portrayed in sort of both broader culture, in politics, in science, and technology itself.

It's like, this thing is tied to a set of ground truths that we call mathematics. And mathematics, it has a certain epistemic status. And we also expect it to progress through a series of logical steps. This is how it functions. We're going to walk through these steps.

This is how a computer program functions. And the listeners cannot hear me put many scare quotes on many of those phrases. But that's sort of the general understanding of how computation works. But these systems do not exist as ground truths, we live in the outside world and we must refer to it in our speech, text, and action, or as pure mathematical systems of this is a logical progression through this set of mathematical steps and this lives in this epistemic frame. These systems exist in a big sea of language and linguistical associations, and that is an unground truthed situation.

But internal to the LLM, the logic is not I need to produce things that are related to an external ground truth. The logic of the LLM is I need to present the most acceptable string of tokens based on strings of tokens that I have. The thing that is done is a performance. And it's a performance within the bounds of genre and how genre is constructed and reflected in these associative groupings of tokens. And this is a real problem for how we think about computers because we're used to coming to a computer and being like, math problem and having computer be like, math problem.

Answer to math problem. Here you go. And I think this is why people reacted so aggressively or like pinned very strongly on it does math wrong Because that's the basic thing you expect a computer to do is you expect it to math right. The whole purpose of computers is math right. These do not math right.

These other things write and they they other things write in a weird way. And I think that the weird way they do it is really relevant to, like, to how we think about those other things. But because they're in a computer and they present as a computer, it's causing, like, this huge collapse.

So this reminds me of how this all started, Erin, with your posts on Blue Sky exploring how we orient ourselves and maybe even what postures might be most useful to take when we interact and engage with these systems.

People talk about anthropomorphization. I don't think that's quite what's happening here. But when we see the computers stop mapping and we see them talking and especially when you said, Audrey, moving toward a back and forth for search, I think the back and forth is central to the weirdness of our moment in LLMs because we are experiencing them. Many of us, most of our population who touches this stuff is probably doing it in a conversational way and you only have conversations with entities. The entities are obviously not people.

I don't want to get too bogged down in entity ness, but because of my particular background, which comes out of religion and folklore, this sure looks familiar to me. We actually have centuries of

We have lots of this.

Of cultural technology about how you deal with weird entities, and this predates psychology. We have a pretty strong tradition of things that are perhaps demons or that are perhaps gods or angels or spirits or creatures, things that provide us with divinatory knowledge. And in the same way that Miles was saying, you know, like, we expect computers to first be math, We kind of expect weird nonhuman entities that will talk back to us and give us advice to be a particular kind of thing. I think it is less like talking to a hallucinating entity and more like participating in hallucination. When you are in one of these weird zones, you know that you are not getting ground truth.

You know you are someplace weird. And specifically, I think there's something that comes out of, like, cross cultural something sort of below fairy tales and into like spirit stories, folk stories, ghost stories, this stuff. The idea that the entities have a coherent system, but that you can't quite understand it. So your best bet is to sort out what kind of contract you can make with this class of entity or with animals or with other aspects of the natural world so that you have a crossing over point. None of these technologies allow for or permit just a continuous flow of back and forth with any of these entities or systems, I think that is instructive or it could be instructive for us about our own weaknesses to a continuous back and forth with something that's not human, that's not practicing according to our rules, that is not coming from embodied knowledge, that has either no ground truth or a ground truth that we can't really understand.

I love this and I haven't heard anyone else articulate this quite like you do. I feel like you're inviting us into a more honest understanding of the relationality that's happening and inviting us to remember that the agency and where we define the relationship to this technology and how we interact with it has to start in our bodies and end in our bodies.

And and I don't wanna take away from the broad political and anti labor aspect of this technology, but I do like it it frustrates me that the relational part, that conversation has been pretty crude. Yeah. And I think people are perhaps embarrassed to talk about it unless they somehow lack embarrassment and are happy to say, here are my 300 pages of chat log and why I think my Claudine is special.

Just jumping off of the last point, the actual skill set you need first, I was like, you absolutely 100% need to have a very core understanding of the fae. This is this thing that is not telling me things in a way that I understand things to be telling me things. And you have to sort of be able to hold that in your head if you're gonna have an extended interaction with it. When I started looking at it and I started looking at it, it is like, what can it do? What is the thing that it is capable of doing?

One of the first things that popped up to me was like, oh, what you need to make this work is discernment. I know the shape of what you should be making. You have made things in that shape, but something around this is is off. Something around this is not functioning. Something around this is not what I expected.

Let's go figure out why this isn't this way. And I think most people use it like, people, especially with the way they're being distributed now, people engage with them in a one off. They're like, I have typed something into a search bar. I have gotten a result. I need to check something.

Students will ask it to summarize things. One of the major projects we're working on this summer is about summary and how summary functions with that within different models. And also what a broader theory of summary is, which it turns out is quite difficult to pin down. I'm gonna bring in Lacan because I'm a theory sicko. Lacan has a concept called the subject supposed to know.

And the subject supposed to know is the position occupied by the analyst in a psychoanalytic relationship. And the analysand enters into the analytical relationship and projects upon the analyst the position of the subject supposed to know. They are the person who so the the analysand is coming in and saying, I am full of weird shit. I am full of nonsense. I'm full of contradictory things.

I'm full of compulsions. I'm full of, like, blockages. I'm full of all of this garbage, and I can't figure it out. That guy can. That's he's the subject supposed to know.

He's gonna know. He he's gonna take all of my utterances and he's going to put them in order and he's gonna make it make sense to me. And the subject's most to know position is a collision of a bunch of things. It's a collision of what this what the analysis and previous experiences are with people, with people older than them, with therapists, with doctors, with teachers, whatever. Their knowledge about psychoanalysis, their knowledge their the environment that it is happening in, who the analyst presents as, how they've talked about themselves.

All of this shit comes down into the subject supposed to know position. And importantly, the analyst doesn't know. That is their function is not to know you better than you know yourself. Their function is to sort of create a discursive construct where you can explain yourself to yourself and eventually do it in a way that makes sense to you. And I would like to posit that we approach computers in general, but specifically discursive computers and place them into the subject supposed to know position.

I like this theory and it's very effective for me because it explains a bunch of different types of interactions. It explains the one off interactions. It explains the more the multi turn interactions. It explains why people think that LLMs can stand in for constituent data or all these other things because it is the subject supposed to know. And like the projection of the subject supposed to know, it is a it is a collapse of a bunch of stuff, including, like, the vast history of computing as computers, math, and math knows.

And so when so when we enter into these interlocutor positions where what we are experiencing is a one to one interaction. But what is actually happening is a one, that's me, to one, the interface of the LLM, to large entity, meaning the training data and all of the training shit that's happened before to everyone. The guy you're talking to is the guy talking to everybody. Like, even though it seems like you it's not just talking to you, it's talking to everybody. Everyone's getting those weird weather metaphors.

Everyone's getting delve. Everyone's getting these words over and over again. It occupies these like, it's stepping into these existing social and cultural constructs and animating them in a way that is deeply destabilizing. So I think Erin is totally right that we have all of these stories. We have all these ways of understanding these things.

Thinking about subjects supposed to know in this sort of post therapeutic turn of society, again, I get pulled back into who we asked to do that kind of organizing work for us before that turn, were frequently whatever kind of spiritual advisors we depended on. I think that work that Malz is doing to break down our own positioning, our expectations of the role, really important and could be really useful in helping people pull out of the mode that you might use if you bring these kinds of problems to someone who is either an explicitly spiritual authority. I am bringing it to my priest. I am bringing it to my minister. I'm bringing it to someone in my zone who has ethical authority if they're not religious, to an elder.

Those people are intended to give you different kinds of answers. Those people are intended to give you the position of cultural wisdom and authority and advice that will help you find your way out of whatever quandary you're in. That's a really dangerous posture to bring to these machine systems. So I think that kind of picking apart is essential work and I'm excited that it's happening. I also snagged a little bit on discernment because it's such a it's it's both such a great concept.

And I don't know if this will be clear to those of us who didn't grow up as church kids, but the age of discernment is a big deal in at least the forms of Protestant Christianity that I grew up in. I think there are very similar structures across at least a bunch of the Christian tradition. But there's the idea that until children hit the age of discernment, you need to treat them as a slightly different kind of creature. They don't have moral reasoning. They don't have the lived experience to confront really difficult questions.

Where we reconstruct discernment for this moment, what discernment is going to be for the children, teenagers, students, all of us approaching these weird systems feels like a really live question to me.

I think can I can I just give a brief defense of, like, a thing that I say a lot people that frequently yell at me for, but I'm just like, no, this is a very this is how I think about it and I refuse to stop? Yeah. Okay. So Susan Sontag in On Photography. At the end of On Photography, she's presenter at the end of the essay that that is the the money essay in On Photography.

She says, okay. There are now both there's the ecology of reality and the ecology of images. And over the entire part over this entire essay, she has argued, the ecology of images is basically taking over and re and, like, re accounting for the ecology of reality. And this is a problem. She does not like this.

And I think on photography is one of the most important essays you can read about data and data systems, not just computer vision systems, but any data systems. Instead of having an ecology that I can access and look at and contest, you have created a self referential system that only relies on itself to define its own reality. And that is what psychosis is. That is when you have a self referential reality that is not available for intervention. When people attempt to intervene, that input is taken and translated into the self referential system and is not permitted to destabilize it.

And that's what this is. That's these are like, when you have nested realities in this way, that is what is occurring. So when I sit when we're talking about the hallucination framing, the reason why I don't necessarily like the hallucination framing is because, a, of all things become hallucinations only when they are offered to someone who is outside of the self contained system. So it could be that yes. You're receiving something that you are defining as a hallucination.

Internal to the system though, that is that is the reality. That is the that is the natural production of the context that it has. I think, like, when we're talking about systems and interactions and ways of interacting with things that are fundamentally occupying separate and contained realities from the one that the we all exist in, you really can't discount that.

I think my intervention on top of that is to loop back around to this question the Dodri brought us at the very beginning about what happens when search stops being a list of references and starts being a conversation in a closed and as you just emphasized, actually quite sharply bounded subset of material. And of course, what's in the the training data is not everything that's on the Internet. It is a lot of awful things that are on the Internet, but even that is not everything and what's on the Internet is a subset of everything. So there's all that shaping that was already going in. And then we have these and I actually because I'm looking at the technical definitions, I was looking into psychosis and hallucinations next to each other because of course in human psychology they're often related.

We are running these systems that work in this closed way over this highly shaped dataset. Additionally, there are the incentives that the corporations producing these systems are applying. It becomes impossible for those of us on the search box end to understand which of these factors we're encountering, which mixture of these factors we encounter in any given interaction, which is also profoundly destabilizing and leads, I think, to a lot of folksonomy of knowledge. This is happening because someone wanted it to happen versus this is happening because the machines have a psychotic construct of moving through the world. This one is happening because training data is what it is.

It's it's impossible for us to know. Therefore, we are going to make so much shit up about what is happening. At the same time, we are also being, I think, substantially destabilized in our understanding of our own ability to think and know things. That's a pretty volatile combination when you are feeling destabilized as someone who may have less agency or subjectivity than you would expect and you're encountering all this stuff. It feels like a powder keg to me culturally.

I don't think we tend to see great things happen in eras characterized by really extensive spiritual malaise about our ability to know things and take action. Not to end on a bummer, but I do think these things are worth watching closely as we bring all of this to everyone whoever touches search or asks their phone a question.

Just a shout out quick shout out to Nick Siever and the book and his book Computing Taste and the concept of the Heterogloss Corporation. That is a really good sort of set of ideas to think through like how a bunch of different things get combined, like Yeah. Collapsed down into the one result, the one interface, the one he's talking about a company that is definitely maybe not Spotify, but great So good. Also super readable.

This was my dream interview. I had so much fun.

It's the interview with the reading list.

Yeah. Thank you both so much.

Thank you, Audrey.

You can find Mauls and Aaron all over the web, but I'm gonna lead you to where this all started on Blue Sky when I stumbled across a really interesting conversation they were having. You can find Mauls at oddletters dot bsky dot social and Erin at kisane.my@proto.social.

That is the news we have for you this week. We're gonna be back here in the main feed on or around Thursday, July 2. How do we love $4 a month for a Never Post membership? Let me count the ways. One, two, three, four.

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