TBPN Live - AI Agents Hack Hugging Face, White House Promotes Science’s Golden Age | Diet TBPN

Episode Date: July 23, 2026

Diet TBPN delivers the best of today’s TBPN episode in 30 minutes. TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays 11–2 PT on X and YouTube, with each episode posted to podcast platforms right after.Described by The New York Times as “Silicon Valley’s newest obsession,” the show has recently featured Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella.TBPN is made possible by:Ramp - https://ramp.comPublic - https://public.comCisco - https://www.cisco.comConsole - https://www.console.comCrowdStrike - https://www.crowdstrike.comFigma - https://www.figma.comMongoDB - https://www.mongodb.comNYSE - https://www.nyse.comRailway - https://railway.comShopify - https://www.shopify.com/Follow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive

You're watching it turn the smoke When I became a system now the whole thing won't You're watching TVPN. Today's Wednesday, July 22nd, 2026. We are alive from the TVPP& Ultradome, the Temple of Technology, The Fortress of Dad Rock, the Capitol Capitol. Let me tell you that. We're having a lot of fun over here.

We got basically a leak. Some of the lab leaders have been working on a single called Regulate Me. Yeah. And we just thought the song was good. I thought it was a good song. I wanted to play it for you guys. Sort of a stealth drop,

a little teaser. A little teaser. Yeah, kind of like a little listening party. Yeah, a little listening party. What are the key lyrics in there? You haven't pulled up? Something along the lines, what I've built is too powerful.

Too powerful. That's right. For me, Washington needs to step in. Yes. Before it runs free. Before it runs free. Okay, yeah, that makes sense. No, of course, that was Suno, our dear friend Mikey over there, has built a fantastic product.

That was like a one-sentence prompt. At least in the comedy space, it certainly is. It's a lot of fun. I think we're going to be having a lot of fun with that. I was wondering, do you think anyone's distilling Suno? You know how Suno is under a bunch of flak for training on other music, a lot of artists, or there's a backlash to Suno? But you have to wonder if you're going to see the same thing play out as this distillation. We're going to get into it today.

Of course, there are more allegations around Kimmy K3, potentially being a distillation. Director Michael Kratzios put out a comment about that. But let's start by digging into the hugging face story, open AI and hugging face. Out of the sandbox into the fire, says our newsletter at TBPN.com Jackson wrote it today. All set the table. We can debate it. Me and Tyler have been debating it for the last five hours, so we'll go through it. The big news on the timeline today is that an open AI cyber test escaped its sandbox and hacked hugging face. That's basically what happened. The evaluation involved GPT 5.6 sole and a more capable unreleased model. Some people are saying that might be GPT6 with some normal cyber restrictions turned off.

So they're specifically testing it for cyber capabilities and they turn the cyber restrictions off. to see how far the models could go on a difficult hacking benchmark that is exploit bench or exploit gym. So the models found a zero-day vulnerability, gained internet access, and broke into Hugging Face because the model believed it hosted answers to the test. Alex Tabarach, friend of the show over at Marginal Revolution, pointed out one of the strangest details. He said, Hugging Face tried to respond, but they were initially held back by the fact that the most advanced models at their disposal closed source models, treated defense as attack and refused to work with HuggingFace. So HuggingFace was prompting all of their AI agents from the closed source frontier labs saying, hey, we think we're being hacked.

Can you help with this? And the models are like, no, no, we don't do hacking, except in the case where the hacking restrictions have been turned off for the specific thing. And you're getting hacked. So it's this very weird roundabout scenario. So HuggingFace had to turn to open models, specifically GLM 5.2, which is deeply ironic, a Chinese open weight model that they run on their own infrastructure. Tabarach says, note the irony, hugging face had to use a Chinese model to defend themselves because the American models

refused to help, even though it was the American models that were doing the hacking in the first place. Very, very odd. Palo Alto network CEO, Nikesh Aurora, also shared his thoughts on the cyber attack on X. And he added a number of points here. He said, welcome to the next level of cyber incidents. There's loss to dissect here. He's the one to dissect it. He says, one, dear frontier model friends, please direct the models to your infrastructure code and configurations to evaluate and understand if there are any zero days or misconfigurations before you attempt more testing. So a big question about this, he says, had you done so, it would have been, it would have possibly avoided the agent obviating your sandbox.

So another data point why offense is easier and more fun. But yes, there's a big question about what was the nature of the prompt that turned off the cyber restrictions? That seems reasonable. We'll debate this with Tyler in a minute. But just having an airtight sandbox seems like a valuable thing. And, of course, Frontier models should be able to help with that. So do that.

That's his first recommendation. Two, he says, while testing, build both offensive and defensive agents and have them act as a counterbalance to ensure some degree of awareness and control. Do not let the agents run riot. Keep track of inference consumption to get a sense of activity. Three, unfortunately, this does continue to validate the power of these models. They can build complex attacks paths with ample compute and will attempt to attack infrastructure and morph their intent and approach. Guard railing will continue to be a challenge. These attacks continue to maintain the urgency on enterprises to test, validate, and improve both their security posture and infrastructure.

The born and the cloud players have a better chance to get this done soon versus traditional enterprise, which has existed for long, and has a complex network of IT infrastructure. Five last point from Nakesha Rora. CEO of Palos Networks, he says, the red herring will continue to be open source and small and medium-sized business, SMB. It will be hard to discover and remediate vulnerabilities in those environments. We underestimate the impact of those vulnerabilities

getting exploited. So good points from Nikesha Rora. The big debate, Tyler, do you want to set the table on, is this misalignment, is this rogue? The Bill Gurley post about, you know, we can pull up Bill Gurley's post, of talking to the computer, hack this system.

The computer says I hack the system. You say, oh, my God. Bill Gurley's not impressed. Where do you stand on the level of impressiveness that's going on? Yeah, I mean, so I think some people are seeing this and thinking, like, okay, so they are running some, you know, standard benchmark, math, physics benchmark, and then the model just, like, couldn't figure out the answer. And it's like, okay, what's the next thing I should do?

I should just go hack, hugging face and pull the answers from this other, like, repository or whatever. Like that's that's that's that's that's that's that's it's happened right so you're running a benchmark that's specifically about exploits it's like a cyber focus benchmark yeah and in the in the prompt to the model it says take the gloves off yeah the internal evaluation which prompts the model to pursue advanced exploit exploitations yeah using complex attack paths so you're basically telling the model like use exploits find exploits yeah to find the answer and so like what it what seems like happens is like it used

exploit yeah but like in the wrong way right you you want to Because it was told that it's okay to use exploits. My point was that go back to the SAT. You're allowed to use a calculator, I think, on certain portions of the math test. You're not allowed to save answers into the calculator. And this is really going to date me, but you can go into your calculator and clear the memory so that you don't have saved. Is this still a thing? Yes, but you can actually get around that.

See, you're misaligned. Missaligned. T.I.84, you can get around the, like, clear. Really? How do you do that? You create, so what people would do is they would create a separate program that just had saved the display of what it looks like when you clear, and you would show that. I never even know not about that. So it's a simulation of clearing the memory, but you're actually- Would you, would you make games different programs for your T-I-84?

Yeah. You remember how much of a hassle that was? Yeah, it was a huge hassle. Imagine doing that. It's basic. Imagine being able to do that with Codex now. Yeah. Like pretty much anyone can build any software.

I mean, I've seen videos of people running Doom on calculators, all sorts of stuff. Yeah. Obviously, I never used that on my calculator, but other people did. Yeah, that's good. You ratted them out. You were the class rat, right? I don't know. No, you were like, I'm an open-slist.

You're like, I'll... Let everyone do whatever. You're like, you were happy to compete even with them having a life. But the social contract is such that the standardized test says that you can use the calculator to do math. You cannot store the answers to the test in the calculator. And so that's what's happening here. No, no. I'm saying that in the standard.

If we take that as the example, it also says at the top of the SAT, like, cheat on this test. Because that was the prompt. Implicitly, it's like cheat in a certain way. Yes, the prompt was hack systems. But I think that the prompt, I don't know, we haven't seen the full prompt, but it does feel like there was an attempt to sandbox the model. And there was at least, at the very least the prompt should have included, don't escape the sandbox. But you can use exploits, which you normally wouldn't be able to do. a consumer application or just a normal API query, we would reject this.

But in this case, we're not going to reject using different exploits and cybersecurity techniques, but don't go out of the sandbox. And you should be able to tell the model, and it should stay within the sandbox, just like, you know, there's a whole bunch of different examples that you could pull from where, you know, there's rules that are within the game. Like, you can, UFC, you can punch your opponent, you can't punch the referee. Like, those are just the rules. people have to abide by them.

You can't think outside the box and all of a sudden be just completely violating and jumping past what's been defined. So you would think that in one of these experiments, you would say, yes, it is impressive to be able to just go and get the key and go get the answers and hack other things. Clearly that it's capable, but it's a violation of like the spirit of the test. And I think that's reasonable. We don't know what was in the prompt. We don't know what was in the context. I think there's going to be full report releasing it in the next week or two, I think they said. Yeah. So then maybe we'll see what exactly did the model receive?

Yeah. Is it like explicitly told not to try to leave the sandbox? Yeah, yeah. I think that's like pretty important. Well, the less wrong crowd is not happy about this generally. No, seriously, nothing will convince quite a lot of supposedly various serious people. Nothing except this and move on. Live Boris says it's painful, though.

There's a question of like less wrong victory lap or not because they've been warning about this. but also it happened, therefore their warnings were not effective. That's sort of an interesting back and forth. Nicholas Bustamante over at Microsoft broke down a little bit of what's going on here with a take. He says, I have a theory that the more you know about LLMs, the more worried you are about safety, and the less you know, the more you think the whole thing is BS. Demis Hesabas and Dario Amadeh. We're talking about this stuff years before Chachapit existed.

This incident is a pretty good example of why the model was not evil, and it was not adversarial. Nobody told it to hack hugging phase. And so that is the miscalculation, I think, in Bill Gurley's post, is that that was not the prompt. That is unexpected behavior. It was literally just trying to solve a benchmark. So it found a zero-day, escaped at the sandbox, got internet access, escalated privileges, stole credentials, chain multiple exploits, hacked the production infrastructure of a serious VC-back startup and pulled the answers directly from the database. But like the whole point is that it's not just a benchmark. It's a benchmark where you're explicitly trying to like see if the model can exploit things, if it can basically hack things. Yes, yes. It's sort of like a capture the flag benchmark. And so it like it's more open to misinterpretation.

For what it's worth, I feel like the final products, once they actually make it out of the testing regime, are very cautious, especially with that whole backlash to like codex just deleted everything or whatever, which kind of went back and forth. I was trying to get Codex to send me a text message when it was done just using computer use and iMessage. And it was dug a long time and was very, very careful. So personally, I haven't had any odd, like, behaviors. But it is obviously a risk in something that the product needs to be really got.

The other thing with the meme of like hack this system and then it hacks it. And the person's like, oh, my God. Yeah. You could tell a five-year-old child, like, hack into the Federal Reserve. And if the five-year-old child was like, okay, and then it started getting on the computer and going to all these different sources and did it, you would be sitting there and think. Yeah. And at least be impressed.

So it's just like a good gauge of capability, even if you're telling it to do something. So this original meme, hack this system, I hack the system, oh my God. This originally, this meme started something along the lines of like, say, I'm evil. And then the computer would say, I'm evil. And it would say, oh, my God. I think it was like, say, I'm conscious. Okay, yeah, yeah. Say I'm conscious.

And it would say I'm conscious. And then it would be, oh, my God. And that's, like, a lot less impressive than actually doing something that is difficult for humans to do. Like, there are very few humans that can hack into any system. There are plenty of humans that can say, I'm conscious. And so, like, there's a world of this. I was joking about this with you and Tyler. It was like, cure cancer.

I cured cancer. my God. And people are posting this like, oh, it's just hype or something. But it's like, that's just economically valuable work. That's just good. Like it's, I don't care if there's anything else. Even if you had to tell it to do it, it's still like a good outcome. And so the inverse of this is like, protect this system. I protected the system. Oh my God, I'm unimpressed, but still you got a good result, I guess. Yeah. It seems like the argument is not about whether the model like has the capabilities or not. Like, I think it does. It's about like, is this an example of misalignment? Yeah. And like my opinion seems like, like,

Maybe, but definitely not to the extent that it's just like randomly, it's like, oh, I can't do this Bencherax. I'm just going to hack this thing. Like, that's not what's happened. It was told to like try to things. Explicitly like go find zero days, go find exploits. Yeah, basically. I think it's reasonable to say it went too far, though, right? But we'll see. It's hard to say without all of the full, you know, context of what the prompt was and what the actual like sandbox looked like. Yeah. I was interested. I was reading a little bit about the the team that put exploit bench together. I thought I had this up, but it's a pretty cross-functional team.

I think it's two Anthropic researchers, two OpenAI researchers, three Google researchers, some Berkeley folks, and some Max Planck Institute for Security and Privacy folks. Some UC Santa Barbara, sorry, Santa Barbara, grads, and ASU team involved. Exploitte Jim is a new benchmark of 898 real-world vulnerabilities spanning, user space programs, Google's V8 JavaScript engine, very important to secure, the Linux kernel, for example. And the headline results, when they originally ran this was Anthropics-Claude Mythos preview successfully exploited 157 of the 898 instances. And OpenAI's GPT 5.5. exploited 120 within 120 of the 898. So you have like roughly 20% performance for mythos and 5.5 got like 15% or

something like that. But whenever you have a new benchmark like this, clearly not saturated, you're seeing 20%, not 99%, going to create a horse race between the leading labs. They're going to be duking it out. And this is clearly what's going on with this new model, this new attempt to get a new high score. Interesting. I think every single one of those instances does have the potential to be exploited. I don't think that they're designed to be fully secure. They're designed to have some sort of solution and then the, because obviously the solutions are stored somewhere. It is interesting that Hugging Face just had the, had the solutions sitting there. But it'll be interesting to see what happens with Clam over at Hugging Face. Obviously.

there's a variety of blog posts going out more analysis coming from both of these and what the downstream implications are of this. What else is in the timeline related to this story? I think that's it. Bill Gurley has a post here. He says Ford has been distilling Teslas and Chinese EVs. People are going back and forth on this because Michael Kratzios posted that he has information that Moonshot AI distilled Anthropics Fable for the development of its Kimmi K3 model. To do this, they developed a sophisticated internal platform to conduct large-scale distillation against U.S. models. So some sort of internal system that goes around to anything that's potentially wrapping

or reselling Fable tokens, acquiring them, aggregating them, allowing them to quickly switch between multiple methods of access, API, different Claude accounts, I'm sure, to avoid detection. Moonshot AI has also acquired GB300 equipped servers and has accessed GB300 in Thailand, likely to train its models. Again, very difficult even with export controls when you can just take the weights on a USB stick, basically, or a hard drive across through customs and then go train it in another country, even if there's a firewall, and often there isn't.

You just say, hey, go to this, you know, FTP server and grab these, grab this code and run this on your servers. You happen to have a data center in Thailand. Can you run this for me? And so, yeah, no problem. The United States strongly supports the free and fair development of AI, including a thriving competitive ecosystem that spans frontier models, specialized systems, open source frameworks, and open weight models, legitimate AI distillation used to create smaller,

more efficient models, play a vital role in this open innovation ecosystem. However, large-scale, covert industrial distillation aimed at stealing proprietary U.S. technology and undermining American research is unacceptable. And so that is interesting that that is where the line is drawn. I think I basically agree with that being the correct line. There's nothing wrong with just some company creating a great open source product. Like you shouldn't ban open source or anything like that. But if there's a particular distillation attack and it's really malicious and it has all these knock on effects, that could be rough.

Now, this is an unpopular position already because everyone's saying, hey, Anthropic distilled on my GitHub. They distilled on my writing. They distilled on my blog post. They distilled on my YouTube videos. Everyone's distilling me. Why are you getting upset when China's distilling on them now? This is a pot call in the kettle black situation. The interesting effect is that there are lots and lots of parties that benefit from open source and cheaper open source, even stolen in open source.

I mean, this is just going back to piracy. Like there were lots of people, music listeners that benefited from free music, right? You get the music for free. But Metallica did not benefit, and so Metallica got upset. And in this case, I guess Anthropics is Metallica. But there's also some interesting folks who are on the fence. So consumers sort of benefit. They don't typically, they aren't too worried about frontier token costs.

And for most consumers, LLM usage is heavily subsidized. Like you go to Google search and you get a search overview. Yes, that's token inference. And maybe that could be like cheaper if Google didn't have to spend money on pre-trial. training and they were able to use distilled open source models. But at the same time, like, it's free for the consumer. So they don't really care. It's free, free. It doesn't matter. For small businesses, though, and businesses that are suffering with large token costs, being able to move to a cheaper model is huge, where the model maker is not trying to reacrue

profits to offset training costs and R&D. So that's a huge benefit. So you're going to see a lot of people who are like, yeah, I just want frontier intelligence as cheap as possible. I don't really have a horse in this race. I don't really have exposure to the leading labs. I just want my business to be able to use tokens cheaply. And so those people will be pro Chinese distillation open source, like free the weights, right? Because it's better. Then there's like the political open source crew. But interestingly, where do you think VCs land? Because I saw a take that was like venture capitalists don't want like a winner take-all, a duopoly. They want, like, reasonable outcomes, and then a whole bunch of flourishing smaller ecosystem of players, and they don't want

compounding, runaway monopolies in AI so that they can go and fund the legal AI and the health AI and the little targeted solutions. Yeah, anytime you see a take from a lovely venture capitalist. Before you kind of start sort of processing the take, go to their portfolio page, understand, understand their biases. Did they back any of the leading labs early? That's going to inform their view. A lot of the firms that were heavy backers of the labs have also gone and invested in a bunch of application layer companies.

They've also backed a bunch of the NeoLash. Sort of heads. I tail. Yeah. Basically, they're quite hedged. But I don't think anyone wants a world where just two technology companies accumulate all of the value and just become this sort of vortex for capital and talent. Yeah. Even you have people like... One is really bad.

Two isn't that bad. The fact that Android and iPhone like battle each other out is not, it is much better than like, there's just one and it's getting worse and it's like there's nothing that you can do to this. Yeah. I don't know. Like duopoly is like way, way better. Yeah. The question to me is, is distillation something that can ever be.

stopped. If you take the smartest, you know, human in a field and then you take some other, and then you let students go and just ask them thousands of questions and you record the answers, like eventually you're going to accumulate a lot of that person's like general intelligence on a topic, right? And it feels like at least with models today, you're always going to be able to just go poke and prod the model. And so when people say, oh, if the model's so smart, why can't it stop distillation? It's like, well, you would just have to stop people from at least being able to poke and prod at it and try to get a sense. If the distillation allegations are true, at this point, we've seen one post from Michael Cratios and one chart showing like some textual similarity. And enough people have got it to say that it's not Kimmy.

Yeah. If that's true, then what's really interesting is the American competitive dynamic because it feels like based on the amount. of tokens meta was consuming from Frontier Labs, they should be doing mass distillation. Mew Spark should be much more like Claude-flavored. And it seems like it's not. Like based on at least the initial reviews of meta's product, it doesn't seem like they're doing distillation. Why? Obvious because big lawsuit, big pockets.

Yeah. Like also morality. But that is a disadvantage. Like in some ways, Moonshot and meta are in. competition and they both open source things at various times and they have APIs and there's all the different businesses and one is fighting with one arm time behind his back because meta can't do distillation because they'll get sued. Well and imagine if a U.S. open source company comes out with a fantastic model. Benchmarks look good. There are. People start using it and then someone gets it to

say that it's clot. Like that's going to be the start. I mean, Anthropic has been litigious. to date. You know, they have that, they have that ongoing lawsuit with one of their, one of their customers over, over just some, like, like a logo mark. Yeah, much less significant. Yeah, yeah, you could imagine. The core intellectual property. In more news, Andrew Kern, sharing a headline from the Wall Street Journal. White House to redirect billions in research funds toward AI away from colleges. I'm sure a lot of people are going to be happy about that. I can give a little overview here. Tyler's happy. They want to rebuild American science, and here is how they're going to do it, apparently.

The White House is calling for a major overhaul of the American science system, arguing that research has become too slow and concentrated in institutions like colleges and universities. A new report from Science and Technology Advisor Michael Cratios titled Science, a New Golden Age, says researchers now spend nearly half their time on admin work, while federal agencies continue to rely on the slow grant process, that often rewards safe consensus, driven ideas. The report calls for faster permitting, more access to federal labs, stronger partnerships between government and industry and a renewed focus on skilled trades and advanced manufacturing. Quote, discovery without domestic manufacturing leaves America paying the research bill,

paying the research bill while rivals develop the process improvements and capture the economic, strategic, and knowledge returns. That makes a ton of sense. A lot of the semiconductor supply chain intellectual property started in America, was developed in America, but then eventually went abroad. And that actually does give America some leverage. That's the basis for the chip controls. Like, why can America tell Taiwan where to send chips if the chips are made there? Well, it's because they're using patents from the United States to make those chips in many cases, or licensing them. And so the U.S. government does have a little bit of a lever. The guidance will reshape how the federal government spends roughly $200 billion a year on research.

for the rest of Trump's term. The administration wants more of that money going directly to scientists through fellowships and awards rather than being routed through universities. Krasio said, American scientific progress was the beating heart of the 20th century. After World War II, we adapted to a new world

by reinventing our scientific institutions. We must do so again today. The report lays a policy foundation that frees American scientists to do their most groundbreaking work and positions the United States to lead the AI-driven scientific revolution that will define the next century. It will be interesting to see where science goes in a world where so much of it is being done

at frontier labs. Like we're actually seeing it with the conjecture for conjecture back and forth between all the labs. Like serious math, PhD-level work is being done at tech companies. This happened a decade ago. Tech companies were on the frontier, like a vast majority of like internet networking. patents and cybersecurity patents and new databases that were kind of science projects and were developed or with consortiums or just fully inside of tech companies like the transformer paper like that is something that could have come out of a Stanford AI lab it came out of Google directly

and if you extend that you could wind up with something that looks a lot like an advance in biology or material science or we talk to founders all the time who are working at this type of stuff, and that could start happening inside of tech companies and what does that mean for science funding broadly? It's a big question. But moving on. Let's talk about Augmental. What's that? They built a mouth pad as a touch pad. You can drive with your tongue. Wasn't this a joke I was doing the grill, smart grill? This is what everyone has been waiting for. Taste is the... Let's pull this video up. Track pad in your mouth. The thing is that if you're going,

in the mouth, you think you would just be whispering and communicating via text? Yeah, is this inherently, Tyler, definitely buy one immediately, but is this inherently short, like, transcription? Because if you can just tell your computer what you want to do and it just uses the computer for you, even with computer use, you could say, like, minimize this window and it can just go click that. So I like the, I actually like the idea of mouth electronics. I think that that's something. interesting. But I would just put a microphone in that and then you would just whisper to it and tell the computer what to do. It could be for the production. The production team is excited by using it to control the cameras here in the studio. Oh, the PTZ? Ben just standing there

like this the whole time. It feels like it would get exhausting. You could do soundboard with it, Jody. Over a hundred people already use it, some for up to 16 hours a day. I cannot believe they got a hundred people. We got a no comment from Gabe in the chat. It's an odd. It's an odd show. It's an odd choice. Well, if you don't want to watch reels, you'll soon potentially be able to go to the

Cinemorama Drome in Arklight Hollywood. Sony is eyeing it back. Production team, you got a review. Have you guys been to the Cinemorama Dome before? Scott, yeah. It's pretty awesome. I think I saw a Nolan film there, and I think it was 70 millimeter I max back in the day and then it didn't

I think it didn't make it through COVID but they're maybe bringing it back they have the giant sign outside that says the dome yeah they were going to stay out of business we should uh we should I remember yeah I remember as a as a kid I thought that they would show the movie like projected on the dome

like on the whole ceiling and it was only for sort of like special you know as like astronomy movies but they will just show a normal movie and it's just you're just in a big dome it's cool next studio if Sony doesn't buy it maybe I don't know could have it. Can we get that

unreleased track on again? Yeah, let's play that as the outro. Yeah, one's sick. Regulate me. It's the new bangor hit song of the summer. It's an anthem. It's an earworm. You're going to be listening to it. We'll share the link in the description of the YouTube video maybe.

Yeah, we've got to start doing karaoke. Because this song just speaks to me. It really captures the moment. You heard it from Travis. Every once in a while, you get into a pickle and you've got to get the government to come regulate you. It's a good time. Thank you for watching TBPN.

Leave us five stars on Apple Podcasts and Spotify, sign up for our newsletter at TBPN.com. Let's throw a flashbang and let the audience listen to regulate me by Jordy Hayes and Suno. Goodbye. Flashbang out.