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You're watching TBPN. Today's Tuesday, April 28th, 2026. We are live from the TBPN Ultra on the Temple of Technology, the Fortress of Finance. We got a quick show because Jon Gray from Blackstone is joining in 20 minutes. We're going to run through a bunch of stuff. I wrote about this in-car surveillance thing. It's going viral. It's sort of fake news. We got to sort of truth zone it, but also it's coming and it might not matter because if you get in a robo taxi, there's definitely going to be a camera on you. But the fear is centered around this idea that there will be a requirement from the federal government that every new car sold in the United States will be required by law to have technology. Uh-oh. That puts constant surveillance on the driver. And this is happening sooner than you think. By 2027, that's just 12 months away. AI in your car will determine if you're sober and fit to drive, automatically turning off the vehicle.
It's almost May, by the way. I know. We're what, eight months away, I guess, from 2027. This is the real AI 2027 problem. This is a big... We are having audio issues. It's most likely a nation state. Potentially. Possible. We are under attack, but we are working on it. It's like watching a dubbed foreign film. Well, maybe we can play this video of what happened the last time America tried to pull back on driving a car while intoxicated. And some of the response, some of the backlash from any attempt to restrict drinking and driving here is viewed... Can we pull this up? Okay, we're working on it. Production team is being humbled this morning. Humbled. Anyway, let me read through some of my take and then we'll play that funny video. So, sounds scary. Okay, John actually says, 'Audio sounds good to me for what it's worth.' Let's go. Let's see. How about this? Does this sound okay? Does this sound okay? Does this sound okay? Does this sound okay? Hopefully, it all sounds good. Yeah, let's play this video.
Drinking and driving here is viewed by some as downright undemocratic. It's kind of getting communist when a fella can't put in a hard day's work, put in 11, 12 hours a day and then get in your truck and at least drink one or two beers. They're making it laws where you can't drink when you want to. You can't, you have to wear a seat belt when you're driving and pretty soon we're going to be a communist country. Communist country. What? What? When was that? Was that the... Apparently that's real. I've seen that video before. I always thought it was fake. I didn't realize that that was real. That feels like 80s, 70s, something like that. 80s. Okay. Well, there was backlash then and there's backlash now. Some of it's a little bit overblown. This sounds very scary. You know, constant surveillance. The real crazy version is a camera that's watching you at all times. The government, the police, and the automaker can just turn off your car whenever they want. That sounds bad. What's actually being proposed? What's actually on the timetable? So, the rationale for this is good and I think most people would agree that it is a reasonable thing to do to try and curb alcohol-related vehicle accidents, drunk driving. There's more than 10,000 alcohol-related deaths each year on US roads. That's a ton. Anything we can do to stop that, reduce that, totally worth working on, totally worth pursuing as long as it doesn't violate a whole bunch of other liberties or create more problems than it solves, right? We want net positive impact here. Technology is getting better at detecting intoxication and it's getting a lot cheaper. So, why not just ship drunk driver detection systems with every car from the factory? That's the proposal. There are a bunch of potential downsides that we can get into, but it's important to get the facts straight about where we actually stand today. So the core concept here is generally correct. Congress did pass a mandate directing the NHTSA to create a standard for advanced drunk driving prevention technology in new passenger vehicles. Now the 2027 date that people are citing, that's not a hard deadline. The law was passed back in 2024 and in the actual law it basically allowed for delays. So they said the NHTSA will only issue a binding mandate requiring automakers to actually roll out this tech when the tech is ready. And the NHTSA currently says that the technology is not ready. So in theory, the tech feels close, but the scale of the problem is so big. You can see why there's a delay here. Alcohol detection systems exist and are typically deployed for drivers with DUIs. You're familiar with blowing in the tube probably. Hopefully not personally, but the problem is that those little hoses that you blow into, those are active systems. They require you to actually sit there and do that for a minute. The government doesn't want that. That's not what the proposal is. They want passive, which means breath sensing. So there's just like smell vision. Basically, if it smells alcohol, it doesn't turn on the car. The other one is fingerprint reading. So, you put your finger on the start button and it scans into your finger and sees how many alcohol particles are inside. I guess that sounds sci-fi, but we're close, I guess. There's a couple other ways you can solve that. And then camera system. Just look at the driver. If they look drunk, then don't turn on the car. So, all of these seem like they could be close to being roughly accurate right now. Like you can imagine an AI startup or a university lab putting something together at a hackathon that's 90% of the way there, maybe 99% of the way there, maybe even 99.9% of the way there. But the problem is that Americans drive a lot. The rough estimate is that there are almost a quarter trillion driving trips per year in America. It's basically every American, all 350 million of them basically, taking an average of two trips every single day of the year. So 224 billion trips a year is what the rough back of the envelope I did was. And what that means in practice is that if this system is 99.9% accurate, you're still looking at tens of millions of incorrect results every year. And the fact that probably 99.9% of these trips are not inebriated. Like drunk driving is not 50% of trips. It's not 1% of trips. It's a very small amount.
Think about how people would abuse this new system. It'd be like students being like, 'Sorry, I couldn't make it to the exam.' Exactly. I ate my lunch. My car wouldn't start because of a false positive on this. And so even if you're at 99%, you're still looking at tens of millions of incorrect results. The vast majority of those are going to be people who were sober. You know, somebody wants to get in their car for their morning commute. They're a little sleepy or they wore some cologne that triggered some sensor system, flags them as intoxicated and prevents them from starting their car and it's infuriating. The tech will probably get there with enough time and effort. So it's worth looking into who supports this and opposes it. The mandate was actually bipartisan but there's starting to be a backlash from libertarian conservatives who are worried about Orwellian government controls. There's an idea that there will be a remote kill switch which leads to a bunch of dystopian possibilities. That is not in the current provision. That's not what's actually being proposed right now. But you know, it's possible that at the end, the end result of this process of back and forth, you do wind up with that exact capability. And so people are worried about the system going off while you're driving at speed on the roads and then the car just shuts off and you get in a crash and that's like actually more dangerous than potentially the alternative. And so the middle ground seems to be what's called pre-drive lockout.
We need a tinfoil expert because haven't the tinfoil enthusiasts... uh have been saying that the sort of remote... Are you using tinfoil enthusiasts to mean conspiracy theorists? I've never heard that before. It's good though. That's a new one. Okay. Yes. So tinfoil enthusiasts. Yes. Will definitely... well, have been claiming that the remote shut off button has existed forever. Oh yeah. Since the 1985. So when some sort of witness or something like that just gets in a very inconveniently timed high-speed wreck. Oh, that is shut down. Okay. I was unfair to the conspiracy theory. It's interesting though. But yeah, so I mean the current consensus is around maybe pre-drive lockout being the more moderate solution than actually shutting the car off once it's driving. Still incredibly inconvenient if there's false positives. And then you also do still run into some potential negative outcomes where you go to the beach, you have a couple glasses of wine, you're not planning on leaving, but then the tsunami warning goes off. You need to get back in your car and your car says no. Like I don't care that there's a tsunami. Oh, I don't care that there's a tsunami. You have had two glasses of wine. You're at 0.08. You can't drive right now. And you need to tell the car, well, in this case, I'm okay with driving drunk because the tsunami is coming and I'm at the beach and I had a couple glasses of wine. And the car won't be able to, you know, potentially deal with that nuance, right? And there's a whole bunch of other scenarios that could potentially play out where the judiciousness is difficult, but potentially unlocked. You know, AI agents, I don't know. You know, you ask these models, what would they do in some certain scenario? Maybe there's a solution. Yeah, I think there's a much stronger argument for rolling this out as soon as the average vehicle is just full self-driving, has full self-driving capability. But then you don't need it because you can be as drunk as you want. No, I still think there's going to be this big window where you're not going to be able to... Paul specifically because if you need... I don't know, as long as somebody needs to sit in the front seat of their car in any type of situation. I like the idea of level four self-driving. You get in the car, there's one button you push to say, 'Hey, just put it in self-driving mode. I've had a couple drinks. Don't let me take the wheel. No matter how hard I try.' It's not negotiable. It's just Playmobil level. And then there's a second button. And for that you have to do a full blood transfusion. They centrifuge your blood and make sure that you have the purest blood possible to take the wheel and be able to actually drive the vehicle. I don't know. Maybe something there.
I did have a take on this though, which is that Doug DeMuro, friend of the show, founder of carsbids.com, has always talked about the eras of cars, you know, the air-cooled Porsches, then you have the fully manual, no electronic systems, no stability control, no traction control, those types of cars. Then you get into the manual gearboxes, the no turbos, no hybrid systems, and then the modern supercar era is just a bonus if it's not a full electric car. It's like, you know, it's going to be a hybrid, but is it at least there's an engine of some sort. And that's what car collectors are sort of marking these moments where it's like it's the last manual, it's the last non-hybrid supercar made by Ferrari or something like that. Yeah. And there's going to be a world where you're like, 'Oh, that was the last one that didn't have the camera that looked at you 24/7 or whatever.' And I think it creates this new class of vintage... Investment grade. Maybe not investment grade, but certainly something that people... I mean you can already see people reacting to this even though the post is a little bit overhyped. You can already see people reacting to it being like I got to buy a 2026 and hold on to it forever and keep it in great condition because I don't want that. But anyway, there's been a pushback on this stuff for a long time. Tyler, do you have anything on cars? Are you old enough to drive? I was just thinking like what do you think the premium is for a car that you can still like drunk drive in? I think your car is going to go... This is not even worth joking about. Yeah. No. Anyway. Bad joke. Move on. Moving on. What else is going on? Oh, we got to talk about the GPT-5.5 prompt for Codex which seems to have a duplicated line trying to get it to not talk about creatures. Tyler, you dug into this. What is actually going on? Yeah, so it just seems like there was some emergent property of the new model where it always tries to talk about kind of creatures and goblins, raccoons. Yeah, ogres are in there. Trolls, ogres, pigeons. And so... so then they have to counteract this, right? You have to put in the system prompt to not do this. Where is this creatures? Do not talk about... never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it is absolutely and unambiguously relevant to the user's query. This reminds me of those old image prompts where there would be a negative prompt that specifically said do not put six fingers on the human's hand. But what a weird one. And what an odd line to throw into a coding agent. Like do we know anything else about this? Have people dug into what is actually going on here? I mean it might not be just the coding agent. It's probably just the model in general, but... It's the model itself. It's goblin mode. The model itself yearns to discuss creatures, goblins, raccoons. It is an emergent property of super intelligence. Vi says they had to put this in due to my effect on the company. Goblins and creatures sort of followed me in through the front door when I joined and we are only just now starting to understand the downstream effects of their presence. And Tibo says, 'Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it's absolutely known.' There's so many. If you know, you know. So, somebody says, 'My 5.5 Codex said goblin with a flashlight when referring to a bug fix yesterday.' What? There's a billion goblins inside your model weights. You just have to get them out, says Tyler Cosgrove. Anyway, we can dig more into that. There's a whole bunch more OpenAI news that we can go into throughout the show today, but we are very fortunate to be joined by Jon Gray. He is the president and COO of Blackstone and he's in the waiting room and we will bring him into the TBPN Ultradome. Jon, how are you doing? Welcome to the show.
Great to be with you guys. I've never had a preamble on ogres and goblins. Very exciting.
We are in odd territory, odd times with the AI boom. I'm sure we'll talk about all sorts of different elements of it, different implications in the global economy. But I'd love to start with a little bit of background on you. I know you've been with Blackstone for a long time. I'm fascinated by the decision to join, what the firm was like when you joined, and how it's evolved over your tenure.
Well, I came here in 1992, straight out of college, straight out of Penn. My senior year in college, I met a young woman in romantic poetry class and a month later, I got a job. And now 34 and a half years later, same woman, same firm. So very simple, very boring. And when I joined this place, it was small. We had 75 people. We had a small M&A advisory business and then we had an investment business with 750 million of capital. Wow. And it was exciting because we were doing the private equity business and investing. And you flash ahead to today and we've got a firm that manages over $1.3 trillion. And it's been a remarkable ride. Exactly. It would be hard to imagine because when we started at the firm, when you go to meetings, you'd have to tell people what Blackstone is and what we do. And that's obviously changed quite a bit. And credit to the founders, Pete Peterson, Steve Schwarzman, who continues to drive things today. They just had a vision that they could do more. And the alternatives business, private markets was a tiny industry and it started in private equity. But Steve in particular had this idea that we could do other things. So we went into real estate where I moved after about a year at the firm. We expanded into hedge funds, ultimately into credit and later on into infrastructure and growth equity to the point now where we have this massive scale and can give almost any sort of capital solution in the private markets. And I'd say the key thing that's really changed is what was very much a niche business serving a small number of endowments and pension funds and just doing high-octane investing in private markets, private equity, real estate, has evolved today to serving insurance companies and individual investors and sovereign wealth and all different people around the world and doing things at high-returning strategies and low-returning strategies all around the globe. But the most exciting thing I'd say is that the firm has stayed remarkably constant. That the commitment to excellence around the place, the drive, the entrepreneurial spirit, that's what allowed it to grow. And it still feels like even at this scale like we're running a small business which is not what maybe your viewers would expect but we still have tons of pride of ownership doing the right thing for our customers and we know at the end of the day the only thing that ultimately matters is that we deliver great performance. If we don't deliver a premium to our clients they're not going to come back and so everything's focused around that and obviously operate with integrity as well.
Yeah. I want to talk about the entrepreneurial DNA of the firm. It feels like the partnership is extremely entrepreneurial. That's definitely a core value as Blackstone's grown from one strategy to 80 strategies, 80 plus strategies, I think. What is the process for standing up a new strategy? How organic is that? We've seen venture capital firms go from they were doing Series A's, now they're doing growth equities. They just sort of bleed into the other strategy. And I'm wondering if there's a more deliberate process where there's someone on the team who's going out and exploring, finding a new opportunity, or you notice that, hey, we're engaged in a strategy and we actually need to sort of split this off and it's like cell division.
I think it's all of the above. There is no master plan, but somebody comes along to us. In fact, yesterday we got a call about an opportunity in an area that's adjacent to something we do where we don't have a focus. It was somebody who wants to give us a serious amount of capital and said, 'Hey, would you be willing to do a business?' So, in that case, it came from sort of reverse solicitation. Obviously, when we were a smaller firm, you didn't get a lot of those, but I would say it was always this sort of basic idea of adjacency where we were doing something. You know, you're doing private equity, you're doing real estate, and infrastructure sits right in between those two. Or you're doing higher-risk debt capital, but maybe we can move a little more senior. And then ultimately, you move to very senior capital. And the same thing in real estate, opportunistic, then more stabilized, then debt. And I think the key is can you use the intellectual capital? That's really one of the great assets. It's the people here and all the insights. And if you think about investing as pattern recognition, which is you connect dots. If you have a broader platform and you can connect a bunch of dots, then you can be better at these adjacent things and you end up serving the same customers who would prefer you to show up and say, 'Oh, you can do private equity really well and you can do real estate and you can do credit. I'd love to work with you. We really trust your organization.' But the key is there's got to be a market opportunity. You've got to be able to deliver that return and then you've got to have the people to do it right because the worst thing is to say, 'Oh, there's a great opportunity. I can raise money for SPAC.' And then you raise tons of money and you end up not delivering for the customers. So the standard has to be, can we deliver a premium return? Do we have the expertise? And do we have the people to do it?
Yeah, I'm sure we're going to talk about artificial intelligence, but is there a second macro trend that you have locked on to that is an overarching thesis? I mean, we've been following the peptide boom and what's going on in GLP-1s. Like there are big stories in financial markets broadly, or manufacturing is another one. A lot of interesting... and I'm just wondering if there's anything else that's actually...
Yeah, I'd give you a bunch. Yeah. I mean, and we spend a lot of time trying to be thematic. You know, one of the things I've learned over time as investors is you're so focused on your model. What is page 52 of the model, this assumption, whatever. But when you look back over time, I often say it's the first paragraph that matters. What's the basic business, the industry you're going after? Definitely matters who your management team is. But doing it in the right theme, right? The theme, the right neighborhood makes all the difference. I don't care if you're the greatest investor operator in the world, if you buy department store chains or legacy media companies, right? There are just businesses where the winds are in your face and you'd love to do things where the winds are at your back. Now, you can still overpay. You could have the wrong business model in a good neighborhood, but your chance of success is much higher. So, as an organization, we're constantly saying to ourselves, what are those things? And so to the question, I'd say there are some basic ones. There's a global shortage of housing since the GFC. We've been investing against that. We've been selling goods obviously really now for 25 years, increasingly online. Owning last-mile logistics has been an incredible business because every time you buy something from Amazon, it goes through one of these last-mile logistics hubs. There are geographies. India has been moving towards capitalism, you know, more physical legal capital markets infrastructure and so building a great team there investing in the right sectors that has been an unbelievably successful theme for us. Japan has really reemerged in the last three or four years as a place that's open to foreign capital that's allowing companies to restructure allowing people like us to take companies private and that's creating a lot of energy and excitement. You mentioned life sciences. I mean if you think about this AI and a number of products that can be created and yet it's all still going to have to go through phase three trials and we've got a big business that does just that. We love that. That's an area where obviously human beings are going to continue to invest a bunch of capital. The physical world, the reindustrialization is massive. Probably the biggest theme beyond the data centers for us today which we can talk about is what's happening in electricity. I mean, all of the things, the data centers, the robots, the autonomous vehicles, that reindustrialization, it all needs power. And it's everything from LNG to renewables to pipelines to electrical equipment to utility services. The way to think about it is you try to find some great thing like data centers. Yeah. And then you turn it upside down and say, what are all the inputs that go into that? Or today, sadly, defense feels like it's going to be a massive tailwind business, right? Every country around the world is going to be spending more on defense. And so, I think as investors, getting your heads around that and positioning your portfolio in private markets or public markets to say these are the areas I have the highest conviction. The best is when you can find something one derivative off. Because today, as you guys know, the hottest things tend to get really high multiples. But can I find that thing that's not quite as sexy? And for us, of course, the data centers have been an unbelievable way to play it. Then you get the benefit of this without necessarily having to pay a huge price.
How are you grounding your thesis around artificial intelligence and the growth there? Like are you obviously there's a million data points about revenue and multiples and valuations and there's a lot of good news where no matter where you look, but do you ever zoom out and look at how you at Blackstone are using artificial intelligence, the value that you're getting for it, where it's working, where it's not working, and use that to sort of level set on how real, how impactful this technology will be?
Absolutely. I mean I think the thing driving us is seeing the power of this technology as it gets deployed. Now I think all of us are frustrated that the technology is so powerful but getting it inside of companies is hard. Yeah. It's sort of the beaker to bedside problem in clinical trials, right? Like we've got this great medicine. How do we get it to the patients? How do we turn it into something usable? That is the challenge. But we are definitely finding more and more use cases. The first thing I'd point out and our companies, their LLM spend and we have by the way we have 270 companies, 13,000 pieces of real estate. It's massive in its scale. Our companies' spend on LLMs was up 15-fold Q1 of this year over last. Now it's off a small base, but it tells you what's happening. And all of these companies are trying to find ways to be more efficient. We own an accounting firm. They're trying to make obviously tax and audit much more automated using this technology. We own ancestry.com and they're trying to do things with content creation which is telling an immersive story based on your family history as opposed to just giving you a bunch of dates and geographies and so forth. And by the way, content creation in a lot of ways is the easiest. You know, coding, music, movies, because the rules aren't as important. Probabilistic works better than... you know, software is great because it's deterministic, there's yes or no. But content is the easiest place we're seeing pickup but I could go through we have a company that does lab-grown diamond grading and of course reviewing these things visually with the AI is improving the efficiency of that company. At Blackstone we're trying to make our investment process better take in all this data from what we have in the outside world look at our historical memos, read the diligence that's here and say to the teams, these are the areas you should focus on. It's not making the decisions, but it's a tool that's making us much more efficient. So I would say to us on the compute side, it still feels like it's very early days in the implementation, but we can see particularly in rules-based businesses, you know, transaction processing, legal, what is a billable hour going to be? This feels like the path of travel in a big way, but I think it's taking more time than most of us would hope.
Yeah. How have you been processing the idea that certain moats might be eroded? There might be more competition in certain sectors of the economy going forward. Is the moat section of every investment memo getting longer these days? How are you investigating that?
I would say the uncertainty section of every one of these memos is getting longer because investing is hard and what you did historically was look at a 10 or 20 year history of a business and industry and it just may not apply right. And we've seen this in the past right, the yellow pages which I may be dating myself with you guys but you used to get a plumber opening up your yellow pages find them when the internet came along they disappeared. Mhm. Taxi cab business which still exists but obviously when Uber and Lyft showed up it changed the world in a really profound way. Now the issue is in 50 different verticals they're going to be impacts. And how do I think about it? Autonomous vehicles which reduce the accident rate by 95% on serious accidents like won't that happen and what does that mean for collision repair? What does that mean for auto insurance? So I would say the areas of greatest risk today are obviously in sort of the white-collar world. It's the software, it's professional services, information services and there you're spending a lot of time trying to understand what the world may look like. Mhm. And as a result, what you're beginning to see both in the public markets and the private markets, I describe it almost like the Red Sea Parting where obviously there are companies viewed as AI winners, could be LLMs, application software, could be the digital energy infrastructure. That's easy. Then there are companies in the physical world that are pretty unaffected. We took a company Medline public at the end of last year. It's in medical supplies, manufactures, distributes them. No impact basically from this and that's easy to underwrite. And I think what you're going to see, I think you'll see a recovery for instance in an area like real estate that's been very much out of favor the last four years because of higher rates and a bit of overbuilding that's going to come back because people are going to say oh that warehouse that's going to exist that hotel is going to exist. I think sports obviously and so I think there's definitely a tendency from investors now to look at this physical unaffected AI world, certainly the AI benefiting world. And then this other area is fascinating because some of these companies could end up being very attractively priced and they may need to change their business model, but they have real incumbency. So we have a business that does revenue management for hospitals, helps them with their billing, basically what do you charge for certain procedures. Now they need to incorporate AI into the business. But if they do that, they should be a winner because they have the trust of their customers. Yep. And that's super valuable. Yeah. So I would just say the risk levels on investing have gone up, but I also at the same time the opportunities have gone up as well, the upside.
How's your recall on your thinking around the dot-com era? There was very similar fears around how the internet would disrupt different businesses. We had Rick Caruso sitting here yesterday and we were asking him about this and he's like I never thought my category of retail would go under even though at the time everyone was projecting that like hey no one's going to, why would somebody go to the store to get something if they could get it shipped directly to their house. And so yeah I'm curious if you've reflected back on that era when you started your career and kind of tried to understand where you had good intuition where you were maybe off.
I think it's a great analogy and Rick is a very good man. It's funny if you look at retail I think that does resonate with what we're talking about in software. So if you go back 25 years ago, you know just as the bubble's bursting as Amazon's starting to become a marketplace for everything you could have said retail will be an apocalypse. And by the way, Sears, Kmart, Toys R Us did not make it. Yeah. On the other hand, Walmart, I think it's up sevenfold. Costco's up like 25-fold. TJ Maxx is up 40 times and has a $180 billion market cap. That's crazy. And for those companies that won, they either had something that was infrastructure-like, groceries, or had a great value proposition, really understood their customers. They found a way to navigate it. And I think that is the kind of way to think about what's coming to so many businesses, which is if they just sit and operate the way they have, they have enormous vulnerability. If they do something and have a market position that's protected, you know, they can end up doing much better. In terms of my own accuracy, I think I probably at times may have been too negative on some of the retail if I look back at it. And some of it obviously ended up thriving and doing quite well. And so you try to have a little bit of mental flexibility. Yeah. Well, it's good to have a mental model of like, am I looking at a Sears management team or a Costco management team? Yeah. And it makes all the difference in the world. I've been the chairman of Hilton now for almost 20 years. And when Airbnb came out, which is an amazing business model they built, a bunch of people are saying it's the end of Hilton, whatever. You know, the stock has been a rocket ship. Chris Nassetta the CEO has done an amazing job. It had a differentiated business model. It offered something fundamentally different and so both of those companies ended up thriving and doing great. So I do think that is the hardest part today because the technology is moving so quickly and is so capable it's making it harder. What I would say as investors is anything in this AI uncertainty world, we'll see these multiples come down because people are, until there's a sense that there's a paradigm that hey this business model is going to survive or may end up thriving but right now I think people are taking a step back and I do think there'll be some baby thrown out with the bathwater. There'll end up being some software companies that you could buy at very reasonable prices. But this is the sort of stuff. The other thing I would just point out for us because of the risk that exists, one of the easiest ways is to be in the picks and shovels. So invest in that electricity, invest in those data centers because you don't know who's going to win of the incumbents, who's going to win of the new model companies, but you do know they're all going to need AI factories, are all going to need power. And that for us has been really the biggest strategic pivot we've made and we think it's going to pay huge dividends for our investors.
Well, we appreciate you taking the time to hop on the show today. We've kept you already 5 minutes long. We would love to have you back and go way deeper. This was a fantastic conversation. Do it again soon. Have a great rest of your week. We'll talk to you soon.
Hey, it was an honor to be with you guys. You have a great show. Take care.
Thank you, man. Up next, we have Colleen Aubrey from Amazon Web Services. You know it is AWS. She's the SVP of applied AI solutions here with us in the waiting room. We'll bring Colleen in to the TBPN Ultradome in just a minute. Last question I wanted to ask, we didn't get a chance, was the barbell strategy. I wanted to hear his take on this idea that you have Josh Kushner buying the Giants, the most legacy thing possible, and then the AI labs, and then you have Ellison owning Bugs Bunny and a bunch of data centers. And it's this weird new normal of you buy the oldest possible thing that is resistant to any sort of disruption and then the exact opposite. But we are joined by Colleen Aubrey from AWS in the waiting room. Let's bring her in to the TBPN Ultradome if we can. Let's give it a try. Hello. Welcome to the show.
Good morning and thank you.
Thank you so much for taking the time to join us. Please introduce yourself and tell us a little bit about what's going on today with AWS.
Sure. So, Colleen Aubrey, been at Amazon for over 20 years now and joined AWS 2 years ago. Okay. And I've been on this journey of looking at how can we bring to life some of the operational expertise that we've developed at Amazon into agentic products and put them in the hands of AWS customers. And today was really sort of great to announce two new products, Amazon Connect Decisions, Amazon Connect Talent. We announced Amazon Connect Health a couple of weeks ago. And this really expands the family of Connect products that we have adding to Amazon Connect Customer which is a 9-year-old product that we've been developing.
So can you help me understand? I think most people will be familiar with AI chatbots and many people will be familiar with AI agents and coding agents that they fire off a prompt and maybe it goes for five, six, eight hours sometimes and then comes back with a fantastic response. But when you're deploying an advanced model, a frontier model, an agent into an enterprise system that's deployed on AWS, what are your clients looking for? How are they thinking about integrating an agent into a platform? Is it that they're vending the agentic workflow to their customers in turn? Can you walk me through some of the examples of how enterprises are actually deploying agents in practice when most people are probably familiar with the more point solution they type the prompt themselves.
Yeah. Well, let me first start by saying that I think we're early in that journey. Yeah. And certainly in my conversations with customers, a lot of what I hear is people looking to automate processes. Sure. And so for me what that triggers is that the mental model is looking at how work gets done today and then putting AI to work to do that same process. And personally my point of view is that that misses the bigger opportunity. I think the bigger opportunity is much more transformative and we can't assume that how we work today is the sort of gold standard for how we might work when we have this new capability in our hands which is to be able to develop fairly complex agentic teammates. Yeah. That can work alongside people in the business. So we're really going after this mission of how do you develop an agentic teammate which is in the business with people and is actually transforming how work gets done and do that in a way which is intuitive and natural so that transformation doesn't come with heavyweight change management. And so we really have gone back to the drawing board and trying to think about how will work happen in a number of different areas in decision-making within supply and demand planning, in healthcare, in recruiting and in customer journeys.
Sure. Sure. I feel like AWS's strong suit has always been understanding complex systems, being able to deploy a ton of resources, but then also being able to monitor, understand everything from cost to performance. How is that changing in the age of AI agents? I imagine if I have a bunch of digital workers doing stuff, I want a water cooler where I can tap someone on the shoulder and say, 'Hey, how's it going?' I want analytics on how different work processes, even if they are fully automated, are continuing and progressing. What does the analytics stack look like in the future?
Yeah, I think it's a good question and certainly in the agentic teammates that we're building. There's a good amount of thought that we put into the observability, the trustworthiness, like an agentic teammate's ability to explain why they've taken some action, why they've come to some conclusion, the reasoning that they've gone through. And an example of that is in Amazon Connect Health. In this case, we're working on behalf of providers preparing sort of summarization of a patient's history before they meet with a patient. And in that case, every reference, every conclusion is traceable. Yeah. Into labs, into previous visits, into medications. So that the physician in this case versus a builder and SDE has the opportunity to be able to observe the work, to be able to reason over the work, to be able to also course correct as necessary. And so for me I'm really much more thinking about how I make an agentic teammate trustworthy and part of the team and that observability comes to life in different ways. Of course under the covers we have to solve for price performance, we have to solve for latency, we have to solve for managing the efficiency of deploying many agents under the cover to actually be able to deliver the experience and that's some of the hard work that we're doing on behalf of customers.
Yeah, I feel like it's potentially underappreciated and maybe this is an outgrowth of the fact that the first AI models that most people interacted with were sort of low-powered chatbots that did hallucinate. But the hallucination problem has, at least to my experience, basically gone away. And it feels like the next challenge is actually educating people on the reliability, the traceability that you mentioned. And of course I'd be interested to hear a few different... there's a whole bunch of different projects that you can embark on to build confidence around the traceability and reliability. I did have one last question though. Since you've been with Amazon for 20 years, I'd love to know how has the company changed? How has it stayed the same?
You know, I think certainly for me this sort of passion for inventing on behalf of customers has remained pretty consistent through the time that I've been at the company. And so really going deep to understand a customer problem, but then also pulling back and asking ourselves, is there a better way? Can we invent a way of solving this problem which is meaningfully better than what exists today? And do we have a new unique point of view about how we would do that? And that's really what we're trying to do with this Connect family of products is really ask ourselves honestly what is the unique capability, the unique operational experience that we have that we can bring to life and I think that has remained consistent. Otherwise you know Amazon's always evolving, always changing and you know our businesses go through inception, they go through scale, they go through reinvention and now is a great time for all Amazon teams to be thinking about reinvention and how do they deliver their products and services to customers now we have this new AI capability in our hands and it's exciting to see the energy around that and I feel sort of like a freshness in the organization as we go through this next phase.
That's great. Well, thank you for coming on the show and congrats on the progress. We'll kick it over to Anthony next. Have a great rest of your day. We'll talk to you soon. Up next, we have Anthony who is a VP and distinguished engineer at AWS as well to continue our segment on AWS and detail a little bit of the OpenAI integration and new stateful runtime for agentic systems. And so we have...
Anthony in the TVPR. Anthony, welcome to the show. How are you doing? What's going on?
I'm doing great. Thanks for having me.
Thank you so much for taking the time to join. There's been a lot of discussion back and forth, and I think it'd be helpful to start with just like a 101 of what is a stateful runtime? How are you thinking about agentic systems? I think everyone knows LLMs are next token predictors. Maybe they're stochastic parrots, but how are you thinking about the capabilities that come from this?
Yeah. And then how does that tie into the announcements today around some of the new models being available?
That's great.
Yeah, the best way I would describe it is that we've seen kind of an evolution of how folks interact with these AI models over the last few years.
It started out exactly as you mentioned with just token prediction.
The early completions API from OpenAI was exactly this. You give it a string, it gives you some more strings.
These APIs have advanced over the years to where that string starts to get parsed and you get tool calls.
Or you get reasoning, or you get other kind of capabilities. And what we're seeing now with agentic development is that folks are taking those tool calls, executing tools, performing things like compaction or extracting memory. And this is a super powerful mechanism, and this is really the thing that has caused at least like my career to dramatically change in terms of productivity and what can be accomplished now. And I think the next phase for AI, I truly believe, is taking a lot of what we've learned in the coding space where most of what's happening is happening locally on a person's laptop or maybe their development machine and making that be deeply integrated within the cloud where like real enterprise applications live and getting all those same benefits. And so what we announced with Amazon Bedrock managed agents powered by OpenAI is a new API that really has three parts. So the first part allows you to create what we call a runtime, and you can think of the runtime as the definition of the agent.
This contains skills which tell the model how to do new tasks. This includes like tools like MCP servers that you want to configure or other built-in tools and a memory policy so you can tell it how to maintain short-term memory or long-term memory or whatever new memory mechanisms might come over time. And then the next part, and this part is really the special bit, is the environment. Today when most people are using tools like Codex, they're running them on their laptop and the agent effectively lives on your laptop. That's good and bad. It means you can do all the things that that person can do. But it also means that agent doesn't have its own identity. You can't create agent-specific policies. And a lot of enterprises are trying to figure out how to strike the balance of enabling these agents to work but also making sure that you can set the right guardrails on them. Environments in Bedrock managed agents really solves this. It allows you to give a dedicated compute environment for that agent. It allows you to create specific policies around governance. And most critically, it gives that agent a unique identity within AWS. So as a security team or an administrator, you can create policies around what that agent can do. We think these things are absolutely critical to enable agents to be used in real-world enterprise applications. And then finally, there's the inference API, the thing that you actually talk to the agent through. And that API is very familiar to existing APIs like the responses API from OpenAI. And so a lot of existing applications can just work once you've created this agent.
Can you reflect a little bit as a distinguished engineer on...
Wait, before we move on.
If I'm an AWS customer today, what should I do to experience what you just described? Because it was a lot of corporate lingo, which I love. I'm an enthusiast. But I want to... what would be your recommendation given this new set of capabilities? What should I try doing to start? What kind of value might be unlocked in the organization in maybe a more straightforward way?
Yeah. Today Bedrock managed agents is in limited preview and that will expand over the next coming weeks and so you probably have to wait a couple weeks.
But in order to actually use this, it's really as simple as making two API calls.
So you can go into your AWS account and make an API call to create a runtime. And then once you have that runtime, you decide what type of compute you want to associate with the agent. And then you make another API to create that environment. Once you've done those two API calls, that's it. You now have an endpoint that you can take an existing tool. It can be Codex, it can be like a web chat-based system or you can just use the OpenAI SDK and integrate it deeply within your application. But it's really that simple. It's just a couple of additional API calls and then you're off to the races.
Interesting. How are you thinking about the different roles of engineers right now? There's been this trend of managers and CTOs becoming individual contributors at labs and then simultaneously there's been individual contributors who are effectively becoming the manager of many agents and so we're sort of going both ways. But where is the highest leverage point for someone who is on the distinguished engineer path, like the ultimate individual contributor, but the world is changing?
Yeah, I can tell you that like in my role, I am coding almost every day.
I took the day off today to come and do this event, but I'm spending almost all of my time coding. I'm having probably the best time of my career.
What my experience has been with all of these coding tools is that once you make coding fast, once you make the actual art of generating the code quickly, what really matters is your understanding of algorithms and data structures, architecture patterns and things like that. So I think what you're finding is that a lot of very senior ICs, folks that have a deep understanding of software architecture are now able to do really amazing things because they understand how to prompt these models in a way to be able to generate new things.
Is it less frustrating? Are you having the most fun you've ever had?
I've always felt in my career that I was limited by typing.
Like I don't care. I don't mind typing. I don't mind writing. I love writing code. But you know, you can think about a problem and you can think about solutions and then you're like, okay, this is going to take me weeks to actually implement.
And that's just something I had always become resigned to is that it's going to take me weeks to solve that problem. Now I think about the solution to that problem. I do some prompting in Codex.
And I have the solution by the end of the day. And that is so incredibly rewarding as an engineer.
Yeah. That's amazing. Well, thank you so much for taking the time to come chat with us.
Absolutely. Great to meet you.
Have a good one. Cheers. Goodbye.
Up next, we have Colin Zima from Omni. He is the co-founder and CEO building the semantic layer powering AI-driven analytics. Do I blink?
Do you not blink?
Apparently not, but I was blinking at them once I saw that.
Oh yeah. You weren't... I was communicating.
Have you been picking up on the drink Coke with two thing? They demand that you drink the... I wasn't gonna do that. You stared them down. Said no. But I obliged every once in a while with the two-handed Diet Coke. If I see somebody who's like, 'Oh, they're not reading the chat. Drink the Diet Coke with two hands.' If you're reading, I'm going to sip a Diet Coke with two hands.
Anyway, our next guest is in the waiting room. Let's bring him into the TVP Ultradome. Colin, how you doing?
I got a two in a drink for you. There we go.
There we go. He's reading chat. This is great. Introduce yourself. Introduce the company. Tell us the news.
Yeah, Colin Zima, CEO at Omni Analytics. We are building the next great data platform. So, a product that can do everything from AI to spreadsheets to dashboards. We're trying to consolidate all of BI into one tool. And we're doing it on top of a semantic layer. So, a layer that can explain how everything in the business works so that AI does stuff reliably.
How generalizable is the semantic layer? Like this has got to be some trade-off because different businesses have different ontologies. How are you thinking about creating something that's flexible but simultaneously uniform?
So I mean on the one hand a semantic layer is actually pretty straightforward. It's just a bunch of text about the business. So if I'm going to go write a semantic layer for ChatGPT or Claude right now, that is what the skills framework looks like. It's a document that has lists of stuff about the business and that is completely unique to every single company. On the flip side, we've had semantic layers in data for 50 years at this point.
And it's the specifics of how all the tables in a warehouse fit together. And what we're doing is just bringing that, like bridging those two worlds together. So it is completely specific to every business.
Yes, exactly. Like a Snowflake or a Databricks.
So I mean I imagine that there's still a world for databases in the future. How are you thinking about that? Do migrations get easier or changing schemas get easier in the future or does this get harder because the data is just so much more? How are you thinking about the evolution of databases and how you'll use them?
Yeah, I mean using sort of public trading as a proxy for this. It seems like the data warehouses have found like a nice middle ground in between the SaaS apocalypse and the pure-play AI companies.
Like we need somewhere to hold all of the data.
And so I think that databases will probably be here for a long time.
I think what has gotten interesting is that picking up your data infrastructure from one tool and moving it to another tool has gotten substantially easier. Like SaaS used to have a good bit more lock-in than it does today.
And yet you still need a database that's holding all the stuff, but the portability of it, I think, is the new question.
Yeah. Is there a piece of this pitch that's like cost-driven? Because with some of the advanced models, it feels like if I just threw a million dollars of compute at a problem, I can have it go and parse through every PDF and use an API to turn it into text and turn it into CSVs and write custom Python for it just to answer the question of like what was revenue last month, right? And that feels inefficient. It feels like this is a good solution, but is that the goal or is it something faster? Speed, cost, everything.
I don't think that we started there. But I think that to your point, like savvy people are sort of coming around to this because on one side, these models are smart enough that you can just sort of throw it at, you know, Google Drive and Slack and your warehouse and you can actually answer every single question. So you can get 80% of the way there with literally no thought, which on the one hand is a little bit scary building a data company because it's sort of like, again, why don't you do this? I think to your point, you probably don't want to reinvent your ARR metric every single time you query.
And ultimately, if it's a one-off question, you don't want to build a dashboard on the fly every single time. So people are starting to come around to realize that this is a cost-performance optimization problem.
And it turns out that the analytics products that have existed for the last 20 years or 50 years or whatever it is actually do have some sort of good solutions to these things. I think at the same time trying to fight the idea that you can just bring ChatGPT to the warehouse and get an answer is a naive version of building product. Now, every single person is going to compare your SaaS product to sitting the thing on the warehouse or just setting it up yourself and doing it in Claude. And so figuring out that balance is like the goal of every SaaS company now.
And cost is a part of it.
Okay. Like a bit of a hot take I want you to respond to. There is like a muttering around like AI psychosis in the enterprise, like people vibe coding, like things that don't actually create value yet. And there's a question about like where's the useful token spend versus just the explorative sort of performative token spend. I think there's a lot of real stuff to be done, but there's also some crazy internal tools that are just like, you know, self-perpetuating. And it reminds me of people had dashboard psychosis like a decade ago. I worked at a company where somebody was like, 'Oh, we need all the dashboards. We got to have every metric.' And I'm like, you oftentimes you have a question and you just need to go answer that question. You don't need to be checking like what's the website traffic on my website every single minute. Like sometimes that's not useful. Sometimes there's already a dashboard for it. So how do you think about rolling out like dashboards or analytic products that are actually effective and like what coaching needs to happen versus just like raw consumption.
It really comes down to pragmatism. So the example I love to give is Guitar Center is a customer of ours. They have sent spreadsheets to every single store for the last 30 years that have every single SKU and like the week-over-week, day-over-day sales.
That's not a process that needs reinventing. Like they're going to send the spreadsheets to the stores for the next 25 years. You need products that can do that.
You're also going to have a dashboard like I want to know what our plan is and I want to go compare like our ARR on a weekly basis to where it is relative to plan.
You're also going to just have a question that you need answered that you didn't predict in advance and need to go answer questions.
And I think the challenge is that every vendor sort of has this point of view that's like, you know, dashboards are the way or Tableau was visualizations are the way to do everything and then I was at Looker and semantic layers were the way to do everything. And I think what you see is that there's a little bit of truth in all of these things. And quite frankly, right now it's AI is the way to do everything. And we're into, you know, how many billion tokens can you spend to go answer your question.
We probably want a tool that does all of those things and actually makes them fit together.
And it's sort of like the... it's not the sexiest pitch. You know, every single thing that you are doing is right and you need a little bit of all of it.
But I think that there is space for pragmatism in the world where we can invent things on the fly sometimes and that is a great way of doing it and we don't need UI and we have good UIs and they do things and you know websites are good and we can go back to them again. So it's both.
It's not the sexiest pitch but it was sexy enough to get the Series C done. How much did you raise? Tell me about the round.
We raised 120 million out of a 51 post.
Massive.
Quick, could you give us a quick history of the company? When did you actually start the company?
Yeah. February '22. So 4 years and a little bit old.
We raised about $27 million as we got the company started. Did our B about 12 months ago at a $650 million valuation. So we're building for about a year and a half and we've been selling for two and a half.
So business has been pretty good.
Fantastic.
And what were you doing? What were you doing before this?
I was at a company called Looker that got acquired by Google. So a direct competitor to my previous company.
You know what you're doing. Well, congratulations on the progress.
I love the... the chat loves the pink, by the way. I love the pink.
Great. Are you guys like fully just... are you going to own pink?
We embraced the pink. We sort of fell into it. We were going to a conference that was all blue and gray.
And one of our marketing leaders was like, 'Hey, wear some pink. People will notice you stand out.' And then we just turned into a pink company, so we embraced it.
Fantastic.
I love it. Very smart.
Well, congratulations. Thanks so much for taking the time to come show us.
We'll talk to you soon.
Thanks for having me, guys.
Have a good one. Goodbye.
Up next... interesting username. I didn't get to ask him about it. Drink Zima. It sounds like some type of like cool caffeinated beverage.
Yeah, that does say Zico coconut water.
Get a very cool caffeinated energy.
Maybe that's the next job. The next thing he can buy so bring it back.
Up next, we have Alex Epstein, the author of Fossil Future, live in the TBPN Ultradome, taking us through what's going on in the world, what's going on in energy markets, what's going on with OPEC. Great to see you again, Alex. Thank you so much for taking the time to come on down to the TBPN Ultradome. Please get us up to speed. What should we be paying attention to?
Look at this black on black.
You look fantastic.
Good with the hair, too.
Oh my god. Do you guys remember what we talked about last time?
The Strait.
The Strait. Yeah. Yeah. Yeah.
So, by the way, interesting fun fact about AI. So, I think most of what I said last time was vindicated in terms of the main thing was this Strait needs to open and there's no substitute for it and there's all these other little things you can do, but nothing compares. And that's still true. I would add you need to enduringly open the Strait. So if you cut a deal with Iran and they have control over it, even if they give you control for a year or whatever, that's not... then you've actually made the situation way worse than it was before the war where everyone figured we really have control over the Strait.
But fun fact, since you're talking about AI tokens, so in preparation for that, in addition to consulting experts and thinking about the issue, I have my own internal AI called Alex AI Pro, which I've invested over a million dollars in. And it's nuts. So to talk about... and one of the things I've invested in is I don't get enough compute. I don't get enough compute from off-the-shelf AI. So you need, you know, if you can run your own agents then you can do it. So that query which I think led to very valuable content was 48 kilowatt hours.
Think about that. That's three Powerwalls.
That's a ton. So, yes, I know.
How long was that running for?
What?
Oh, that's crazy. And what is it doing? Like pulling data from the internet, pulling it together, writing.
It's really god mode. I'll show it to you sometime.
Well, actually, so here's an announcement for the first time. That a version of that AI is now free to everyone who works in government. So, it's gov.alexpstein.ai.
Yeah. It's so at some point it's free. We're going to... if you use too many tokens, we'll have to just charge you cost beyond that. But yeah, I mean I have my... I have a lobbying firm which is the only pro-freedom lobbying firm, the Energy Freedom Fund, which is a 501c4 that I'm the unpaid president of. And I figure like one of the best ways to spend those dollars is to give people a pro-freedom AI. So I'm not going to make any money off those queries, but we'll at least cover our compute cost. So this is a real-world example of I believe that if you know how to intelligently integrate AI, you can make use of a lot of energy.
Sure. Sure. Sure. Yeah. Of course. Because like the results that come from good research or good policies and good consulting fees and all sorts of...
But you need to train it. So a lot of the work is just literally breaking down everything I do and my researchers do. So we just... I just built one today which is the policy validator which is anyone is free to send us policies and we'll lobby for them in proportion to merit, not in proportion to payment. We don't take payment for this kind of thing.
But I needed to replicate, hey, I have these two really brilliant researchers and then I'm pretty good and we have some other pretty good people, like how do you break that down? And it turns out there's about 25 questions you need to ask to get the credibility of the people. Is this a pro-freedom policy? Is this going to increase energy abundance? Are there better ideas? And if you know how to really do it, you can get a... and you have human validators at the end of it.
It's wild in terms of what you can do.
Okay. Let's start with there was a... on the Strait there was this interesting piece in The Economist that was arguing that the market was simply not processing or digesting the fact that even if the Strait were fully open today there's still a massive shortage of energy that is effectively delayed and that that would have ripple effects on the economy, inflation, all sorts of things. How have you processed the impacts, the downstream impacts? I think a lot of people see it at the pump when they go and fill up their cars if they drive gas cars. It's starting to show up in other places. But how are you thinking about just what's at stake, why the Strait being open is important from first principles?
Yeah, I'm very sympathetic to that argument. It would be just miraculous if it didn't get a lot worse in terms of prices. I mean, you're dealing with a situation we talked about last time. You have a certain amount of spare capacity. So, you know, we... international agencies released a reasonable amount in terms of their oil reserves. But these are all very temporary measures.
It's like 30 days here, 90 days there, 180 days.
And there was already a bunch of supply.
Yeah. No one's sitting on 5,000 days of oil.
And the thing you have to realize is, you know, in America, we're very America-centric. So, you know, we don't even think about Canada, let alone Asia. Okay? And a lot of what's happening with the Strait is oil that is intended for Asia and Asian consumption. Now, the Chinese are in an interesting situation because they did build up a bunch of spare oil. Now, there's questions of other things they need like sulfur and helium that go through the Strait and I've heard interesting claims about that.
But we're already seeing in Asia various shortages. And you know, one analyst that I like likened it to, okay, you're starting... like one part of the Titanic is starting to fill and not everyone on the Titanic realizes this is happening, but you're cutting off a huge... whether it's 14% or 20% or whatever, you're cutting off a huge percent of global oil supply and that cannot last.
And even if you solved everything today, it takes a while to bring it back.
And right now we're in ceasefire mode.
Which is not creating enduring... that doesn't enduringly open it up.
Yeah. I heard I think it was Rahm Emanuel was saying that the Gulf states do not want Iran to have a veto over the Strait even if the Strait is opened. Now the conversation has shifted to what does it take that America is potentially responsible or is being held responsible for removing that veto, right? Is that your perspective?
Yeah, my perspective is it needs to be enduring. So in advance of this there was the idea that hey if America ever goes into this to Iran obviously we're going to keep the Strait open, obviously we're going to prioritize that. That unfortunately did not happen to the extent that it did. I mean, you know, they're different people in the administration, but overall, I mean, we have to just be objective. I'll praise them where they deserve praise, but like they were not prepared for this in terms of whatever the final decisions were. I think within a week of our last interview, not because of our last interview, but I just talking to people in the administration, they all became very clear that Hormuz is non-dispensable. Before that, there had been people saying, 'Oh, we have Venezuela, we have all the...' just all nonsense.
We talked about that with Venezuela. It's like 1% maybe.
Yeah. One. You might get to one. No. At some point... might get to 1% and we're talking about 20%. So we're talking about are there 30 Venezuelas to do business with?
So it's like they understand the importance but it's still in this mode where Iran now is known to have... look, Iran has proven that they can control the Strait of Hormuz in a way that the US cannot obviously counteract. So if we cut a deal with them where they again... where they have... where they can use the same power to stop us anytime they want then it's not open, right? Open is a little bit ambiguous, like it can be open momentarily but it's open on their terms. So basically you need... without giving any strategy because I don't know the exact strategy, it needs to open on our terms. That's the only way you have a victory.
Let's shift to OPEC. Can you give me a primer on OPEC? It's the Organization of the Petroleum Exporting Countries.
Yeah. Yeah. And now it's, you know, OPEC Plus and...
OPEC Plus. So yeah, take me through the history and the impact.
Cartels. I think the easiest way to understand this... no, it's important to understand cartels and I think people have a uniformly negative view of cartels which is plausible but a little bit exaggerated.
So you take the people that aren't a part of cartels... there's no like...
Yeah. Exactly. Well, you think about the... if we go look at the early oil industry where, you know, Rockefeller is criticized as a monopolist and we created this thing, the Sherman Antitrust Act and other things to prosecute so-called monopolists. And I'm totally against these laws for any number of reasons. I don't think the government should be able to create monopolies that it enforces by force, saying, 'Hey, there's one producer. Nobody can compete.' But nor should it be able to say, 'Hey, you're really successful in this market and so I've decided that you're too good.' And one of the things that people will counter with is, 'Well, what if... economic dead weight loss?'
What do you mean?
Just the idea that if you actually do control 100% of a resource, you can charge dramatically above market rates, which reduce demand and wind up having like less human flourishing because you have less energy produced in fact.
Yeah. So what happens in practice is like if you look at what happened with Rockefeller. So Rockefeller took... his focus was refining. You look at the early people in the oil industry, the different producers. What would happen is oil prices are decent. Then you get a flood of new oil on the market and people just get wasted. They get ruined. And so what does that do? That disincentivizes people from investing over time because the volatility is so high. So what Rockefeller was basically able to do is he said, 'Okay, I'm going to buy you up. You're exposing yourself to way too much risk. I'm going to buy you up. I can run everything much more efficiently.' And so in the long term, we can have something that is a profitable and b has much lower prices on average than the very volatile situation. And in fact, he dramatically lowered prices. So the interesting thing, so you could think of Rockefeller, they call it... it's in a sense a cartel, but it's a free-market cartel, which I think should be able to exist, but you can call it...
Yeah. And I believe that's in part... that's in the Sherman Antitrust Act in some ways like you have to prove consumer harm and this is why...
