Ex-Palantir Analyst On The Inner Workings Of Intelligence & Markets In A World Of Socialism

Summary

1000x Podcast Summary
Episode: Ex-Palantir Analyst on the Inner Workings of Intelligence & Markets In A World Of Socialism
Host: 1KX Media
Guest: Alex Good (Former Palantir Analyst, Trader, Entrepreneur)
Date: July 28, 2026

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Episode Overview

This episode features a wide-ranging interview with Alex Good—Wharton grad, ex-Palantir analyst, former hedge fund trader, entrepreneur, and now the founder of a crypto project called “Post Fiat.” The discussion traverses Alex’s firsthand experience at the intersection of intelligence, big data, market speculation, meme stocks, and the coming tidal wave of AI-driven disruption. The core themes center on the changing nature of market edges, the transformative yet perilous rise of AI, how communities organize in digital economies, and the looming societal implications as unemployment and political upheaval threaten the established order.

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Key Discussion Points & Insights

1. From Palantir and Markets to Meme Coins and AI (00:00–13:00)

• Alex’s Palantir Roots:
  • Originally, Palantir was about “killing the right terrorist” by mapping ontologies—how data points connect to solve real-world ambiguity.
  • Notable Quote: “If you try to go to Afghanistan and kill all the people with beards driving a Jeep, then you're going to kill everyone, and you don't know who's who.” (Alex Good, 00:00)
• Trading Evolution:
  • Alex’s edge as a trader initially came from direct, actionable data—especially in digital advertising—using it to arbitrage in capital markets (e.g., seeing undervalued Amazon from ad ROI).
  • The move from “real economy” trading to attention and memes (“The alpha I'm measuring with Tesla is not how cheap it is to sell a car, it's how cheap it is to sell the stock.” —Alex Good, 09:22).
• Crypto & Digital Identity:
  • Alex critiques shallow meme token communities, arguing for deeper digital cultures with real architectures and collective incentives.

2. Understanding Attention, Reflexivity, and Market Edges (13:00–17:00)

• Goldfish Theory and Predictability:
  • Alex develops a model where, once a person or product becomes the “vortex of attention,” future behaviors (like purchase rates) become highly predictable.
  • He applies “reflexivity” from Soros: “if people believe something is valuable, then it actually becomes valuable.” (Host, 11:39)
• Where the Model Breaks:
  • Attention and liquidity fragment when too many similar alternatives emerge (e.g., competing tokens, products, or influencers), diluting the edge.

3. The Palantir Inside Story: Data, Ontologies, and AI Competition (16:16–24:27)

• Palantir Finance Product:
  • Alex was an early user and builder, employing credit card and SWIFT transaction data to predict macroeconomic trends and provide compliance analytics.
• From Consulting to Product:
  • Palantir evolved from bespoke consulting projects (e.g., anomaly detection for oil trades) to scalable enterprise products (Gotham, Foundry).
• AI Revolution & New Competition:
  • The market for AI in finance and intelligence is now crowded; behemoths like OpenAI and Anthropic directly compete and fragment Palantir’s attention/market share: “What Palantir used to be special because it was the only person on the block with like an intelligence product and now they're three.” (Alex Good, 23:32)
• The Ontology Argument & Its Weakness:
  • Palantir claims AI can’t work on raw data without human-labeled ontologies. Alex disagrees, arguing modern AI’s need for ontologies is diminishing as LLMs grow more capable.

4. The Data Gold Rush & How to Monetize It (24:27–26:04)

• Data as the New Drop-Shipping:
  • The business of selling, not just collecting, data for AI labs has exploded. However, Alex’s philosophy is to internalize/mobilize rich behavior data rather than simply selling it: “If you actually think a data source is valuable, you shouldn't sell it, you should monetize it.” (Alex Good, 25:13)

5. AI Leverage, "Permanent Underclass," and Looming Unemployment (26:04–33:47)

• AI’s Uneven Impact:
  • While high-agency actors can leverage AI for immense advantage, the average person remains on the sideline, using AI as a chatbot or assistant.
• Unemployment Lag & The Accenture Indicator:
  • Despite market turmoil (e.g., software stocks crashing), corporate layoffs have lagged. Alex forecasts significant unemployment will begin to show up in three months as financial pressure (e.g., Accenture losing 60% market cap while keeping headcount) forces downsizing.
• Trading Opportunities:
  • Look for bottoming in software companies post-layoffs, IP-rich companies (Nintendo, Disney) benefitting from AI, and companies with unique, undervalued assets.

6. AI, Political Response, and The Rise of Socialism (33:47–39:33)

• Black Print Thesis:
  • Alex posits the current U.S. political system is not built for hyper-acceleration. As AI massively shifts wealth to a minority (e.g., Nvidia vs Russell 2000 in value vs employment), middle-class workers will respond by organizing politically.
  • Prediction: A populist-left (socialist) surge facilitated by newly unemployed, highly competent workers.
• Regulation Is Inevitable:
  • Both political right and left are now prepared to regulate AI, with job protection likely prioritized over global competition with China.

7. Automation, Robotics, and AI Bubble Timing (39:33–47:36)

• Robotics Skepticism:
  • Alex is bearish on large-scale humanoid robotics/automation, citing public/political unpopularity and strict regulatory precedents (e.g., port & self-driving automation restrictions).
• AI Entertainment & The Attention Economy:
  • AI hasn’t delivered paradigm shifts in content/entertainment yet, but the coming wave is personalized digital content, smarter NPCs in games, and richer online experiences.
• Productivity vs. Speculation:
  • Despite AI hype, actual productivity growth remains anemic. Most benefit accrues as increased speculation and further immersion in a digital “attention economy.”
• Sovereign Margin Call Scenario:
  • If the productivity boom fails to materialize, the U.S. faces a “sovereign margin call” as debt/political risk mounts. Crypto (Bitcoin) as a hedge and escape from sovereign risk is a central motivation.

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Notable Quotes & Memorable Moments

• On Market Edges & Meme Stocks:
  • “The alpha I'm measuring with Tesla is not how cheap it is to sell a car, it's how cheap it is to sell the stock.” (Alex, 09:22)
• Palantir’s Real Origin:
  • “How do I know that Osama bin Laden is Osama bin Laden? ...these things that comprise Osama bin Laden are a quote unquote ontology.” (Alex, 21:24)
• On Fragmented Attention:
  • “If their product review went from 4, 5 stars to 3.8 stars, like if you start to lose trust in Michael Saylor, it's like his star rating going down and then the conversion rate drops.” (Alex, 15:03)
• Predicting the Underclass:
  • “We tried to escape the permanent underclass. We didn't. We're all in the permanent underclass together. Like, what are we going to do about it?” (Alex, 27:26)
• Sovereign Margin Call:
  • “If we have a massive productivity increase, then we're not going to have to worry about our World War II level of spending. And it's like, okay, like if that doesn't happen, then it's basically a sovereign margin call. And that's sort of like why I'm in crypto.” (Alex, 47:06)

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Important Timestamps

• 00:00 – 03:17: Intro to Alex’s worldview, Palantir background, community critique
• 07:01 – 11:22: Trading edge evolution, meme stock insight
• 16:16 – 24:27: Palantir’s finance/ontology innovation, why Alex is bearish on corporate AI claims
• 25:17 – 26:04: Data monetization philosophy in crypto/AI
• 29:09 – 29:19: Alex’s prediction: “Unemployment should start kicking within three months.”
• 34:10 – 39:33: Black Print: Political response, rise of socialism, historical parallels
• 41:00 – 42:36: Automation/Robotics skepticism, regulatory response
• 46:52 – 47:36: Productivity disappointment, AI’s limits, crypto as sovereign hedge

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Tone & Language

Alex is sharp, analytical, and unsparingly candid—often skeptical, always systems-minded. The hosts maintain a tone that’s both awed by Alex’s depth and eager to challenge and clarify. There are frequent references to “edge,” necessity-driven pivots, and an explicit focus on how systems—market, technological, political—evolve together. The entire conversation is brisk, incisive, and mixes street-level trading realism with macro-social theory.

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Summary Takeaway

Alex Good paints a complex world where the convergence of AI, big data, and digital capital is rapidly changing market dynamics and societal structures. The future is not just technological, but intensely political—with looming unemployment, the fragmentation of attention, and a renewed contest over who benefits from acceleration. While hype cycles may crest and capital may flee to “digital corners” (like Bitcoin), Alex contends that reflexivity, community design, and adaptability remain the trader’s (and citizen’s) best tools—until, and unless, the sovereign “margin call” finally arrives.

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(This summary omits non-content segments such as ads, intros, and disclaimers.)

Transcript

[Alex Good]

The first use of Palantir was like, how do I know that I'm killing the right terrorist? Because if you try to go to Afghanistan and kill all the people with beards driving a Jeep, then you're going to kill everyone, and you don't know who's who.

[Podcast Host]

Honestly, I have no idea how to introduce this next guy, but his name is Alex Good, and he is one of the most interesting people that I've ever had the pleasure of interviewing. Our conversation spans a ton of different topics, ranging from what's going to happen in the age of AI to the rise of socialism to how to benefit and put money in your pocket based on what's to come.

[Alex Good]

Okay, So, I mean, like, I'm in the popcat Telegram group, and Murad is in there too, but he's the main event. You know, it's like, Murad in the popcat group, and people are kind of glomming onto him, and I'm like, this is the community that you build. That's not the community that I want to build. I want to build something that's like, my bar is like, would I use this product every day? You know, like. Like, would I show up every day and do what the AI told me to do publicly? That was the bar. And. And just the popcat group wasn't the bar. So I'm like, okay, like, what would it take to actually make, like, a system where a large group of people voluntarily opted into the system and had a real command and control architecture with an AI at the center of it?

[Podcast Host]

What was the issue with the popcat

[Alex Good]

group that you saw? So, I mean, the. The issue with the Popcat group is 100% about the price of Popcat. And then it was about the promotion of Popcat. And it wasn't like there was. There was no. It wasn't funny. It, like, you know, the theme was like, oh, we're part of a community. I didn't see elements of a community forming. There were not people helping each other out. They were not people colluding usefully. Like, it's. It's not like I'm in the popcat group. Hey, do you want to get into this venture deal with me? Right? It's like, no, we're all going to kind of just like, post the popcat chart and maybe engage with some tweets that Murad posted. Right? That was the extent of the popcat Telegram group. And I was like, that's interesting. From, like, a very. You know, the. The thesis that Murad had was more profound. Than that, right? So it was kind of like he's like, look, in the age of AI, the only real identity is that we have these new digital cultures. And like, it's very relatable because we're on like, X and we're, we're there. And to some extent, I would have never met you if it weren't for X. So we kind of natively understand that this is true. But the, the community on X is quite rich, right? There's DMs, there's like meetups, there's in person events, there's deal flow. And it, it just, it wasn't there for the memes. Like, the meme coins were not useful social identity layers. But like, I kind of was like, okay, like, I like the idea, I think it's true. But you didn't take it far enough, right? You didn't have a real architecture. So, so that's like part of why I started a token. I'm like, what would it take to create? What would it take that I joined the group and I didn't feel silly joining it.

[Podcast Host]

Right. And before we get into that, because you've created something kind of insane. You were telling me before, the only point of it is to basically increase its own value. And we'll get into it, we'll name it, we'll talk about it, we'll dive in. But first I want to ask you, who the are you?

[Alex Good]

Who the am I?

[Podcast Host]

Like, who the are you, man? I, I'm Alex. I've known you for four years, five years now. Yeah, we've met a few times in person. I'm a huge consumer of your content and tweets. I think that they're brilliant. But you've lived a lot of lives. You're a Wharton grad. You are former Palantir, former Valley Asney. You started a company called Perpetua that sold, that got acquired. Then you became an independent trader. And then you started, I mean, you started tweeting, really actively started being an essayist. You have all these thoughts on the world. Like, and now you've built this thing called post Fiat, which is a layer one cryptocurrency. I mean, you've done more in a life than most people, even more in, whatever, 10 years, 15 years than most people do in life. Like, what are you doing? Like, who, like, who are you?

[Alex Good]

Yeah, I mean, I, I was always really, really interested in trading in capital markets. You know, I, I was very normal for a long time. Like, you know, I, I, I worked at City.

[Podcast Host]

Do you Consider yourself not normal.

[Alex Good]

Now, I. I think I got weird eventually. And I can tell you exactly what happened. Right. You know, I was always looking for an edge trading. I did fx and then I did big data stuff at Palantir. And we found a lot of interesting stuff with big data at Palantir. And then I worked on Swift Data in Singapore. And then, like, basically when I showed up to Balasni, I. I got hired at Bally Asni because I had access to a data set that got cut off because of the Swift problems at Stan Chart and hsbc. And I had to invent a new trading strategy. And that trading strategy was based on advertising. And so I traded, you know, Google and Facebook and Twitter, and then I had to advertise things. So next thing you know, I'm advertising video Games. I'm advertising OTA booking.com and Expedia, and I'm trading those stocks. And then when I started Perpetua, it was just a very simple observation that I knew that. That I knew because of the advertising that I was running, that Amazon was incredibly undervalued. Right. So I bally as me. They were like, Risk was constantly calling me, you have like, a 15% of your book in Amazon, which is way too big. And like, like, why do you own all this Amazon? I'm like, because everyone is saying the retail business is worth zero. I know it's worth a gajillion dollars because I'm running all these ads and they're breaking even on ads. So it took a long time for this to just date. But what ended up happening was that I just got really in the weeds on what it took to acquire a buyer of a thing. Right. Like an advertisement. Right. And. And eventually we got so big at Perpetua that, you know, we started booking, like, Crocs and Kimberly Clark. And we were selling. We were still selling data to. To funds. But then at that point, when we started booking these. These big companies, it was no longer viable to trade. And that's how I got into crypto, because I was like, okay, like, what. What can I advertise that has an edge, that has a direct feedback loop? And by this time, I'd already started seeing stuff like Tesla. Like, way before meme stocks became, in our common parlance, we'd be running ads for, like, Tesla cars. And all of the clicks were coming from, like, the search Elon Musk or like, can we take a step back

[Podcast Host]

for a second and talk about the strategy?

[Alex Good]

Yeah.

[Podcast Host]

And how you found it and generated that edge. I Mean, I think one of the most important things that you do as a trader is figure out what your edge actually is. And half of the time, it's searching for edge, and then it's monetizing the edge. So what were you doing and how did you find it?

[Alex Good]

Yeah, I mean, it was like, actually a pretty funny, funny thing. I showed up to work. I had been hired because I had this data set or was supposed to have this data set that I didn't have. And they're like, you have to come up with a strategy. So they moved me from Singapore to San Francisco because I started the strategy. I talked to a guy who owned like, $200 million of Facebook stock, and I asked him point blank. I'm just like, have you ever run a Facebook ad? He's like, no, I'm just in it because Zuck is a chad, basically, right? Like, that was like this. I mean, he was right. Actually, in hindsight, he's right. But I was like, this is a huge opportunity because people are trading these advertising stocks, and you can get real time data about how well their stock, like, you know, their ads are performing and. And. And then. But they're into, like, what do I actually advertise? Right? Like, you have to advertise video games, or you have to advertise stuff on Amazon, or you have to advertise travel booking sites or like Groupons, and all of a sudden you're advertising airlines, and. And suddenly you have a view. You're like, you know, a very, very simplified version of the strategy is, like, at the time, you know, it. It cost you. About 70% of your margin of booking.com was spent on ads. So if you talk to, like, the CFO of booking.com, they'd be like, yeah, we're like, very, very actively managing our advertising budget. You talk to the CEO of Electronic Arts, you know, you say, look, dude, like, you can sell a $50 video game for $4, right? Why aren't you spending all of your money? Why are you spending any TV ads? Like, why are you doing any TV ads? He's like, well, we're know the digital ads work, but we like the margin story. We can progressively increase our digital ads. And you're like, holy crap. Like, at the time, Electronic Arts was cheaper on an EVDA multiple than booking. And you're like, okay, company A can acquire customers for a 50 video game for $4, and then company B is spending 5 out of their $6 of profits, and they're trading at a way higher multiple. So you know, you go long, electronic arts, shortbooking.com, you've got a pair trade, you've got the valuation on your side, you've got the data on your side. And if those dynamics change in your quarter, like let's say you say like, oh, Call of Duty ads are like way more expensive this quarter. Then you're like, okay, EA is not cheap anymore because their product is hard to acquire. So, so it, at the, at the time it was very, very normal. And then I guess to your question is like it only got non linear once you started getting into meme stocks, right? Because at some point you're like, wait a second. The alpha I'm measuring with Tesla is not how cheap it is to sell a car, it's how cheap it is to sell the stock, right? And that's how I got into xrp, that's how I got into Cardano. That's how I got into like Binance affiliate programs. That's how I got into X. Because you know, I was running affiliate ads and they were like, yeah, we're, we're getting rid of our affiliate programs. If you don't have 10,000 Twitter followers, I'm like, how am I going to get 10,000 Twitter followers? I need to start saying things on the Internet. And so that's, that's how I ended up starting like I, I, everything that I became was a sort of result of just sort of economic necessity.

[Podcast Host]

And I think it's crazy because you've actually witnessed the degradation of our markets and society in real time from the inside just based on that framework. It's, I used to use this data set to figure out if things were expensive or cheap and I used to use them to express real views on the real world and now I just use them or I use them to express views on attention.

[Alex Good]

Yeah.

[Podcast Host]

Do you think that's right?

[Alex Good]

Yeah, I, and I think you realize like over time you're like, at first you think that and then you're like, okay, well how, how much has Tesla gone up in terms of its real cash flow generation since that time? Enormously. So it's like at the time Tesla is a meme stock, but they gave Elon Capital and he did useful stuff with it. And, and so it's hard to really, you know, even GameStop now they're, they have enough money where they're like going to acquire ebay and like now people are really trading Pokemon car. Like when GameStop was a meme stock, it had no fundamentals, zero fundamentals. Now it actually has fundamentals, right? Like, actually, Michael Burry was like a gamestop investor because he saw, like, the trading card turnaround. Like, these things aren't that simple. I think in crypto, we see it too. It's like, okay, at some point, ethereum was worth $7, and it was ridiculous. And then eventually, now you have, like, tether and circle trading on Ethereum.

[Podcast Producer/Moderator]

And.

[Alex Good]

And so I think memes aren't necessarily just degradation. I think sometimes these memes are like hallucinations of our society, or hyperstitions, if you will, where capital flows into ideas and people that society wants to advance.

[Podcast Host]

And so maybe we can talk about this hyperitional vortex as, as. As an example of, of what you're, what you're getting at. But I think at the core, to me as a trader, it just reminds me of that simple graphic from the alchemy of finance, the George Soros graphic of reflexivity, where perception actually does influence reality. And then you can get a flywheel effect of if people believe something is valuable, then it actually becomes valuable. But there are, There are two different outcomes here. It's like a meme. No matter how high it goes, it's not generating any value for anybody, right? It's generating value in the sense that you can sell it at a higher price point. But Tesla, as it, as it trades higher, you sell the stock, you get the cash, and then you can actually invest and grow the company. So the perception of it as more valuable actually does make it more valuable. Or do you think that applies to memes as well?

[Alex Good]

Well, I think. I think the frame that I learned to take originally was that average, like, I call it the Goldfish theory. Um, and it's the idea that I noticed this pattern with Amazon sellers where, like, there was a guy selling dandelion tea, and every day 8% of people who went to the page bought it. Like, it was always 8%. It didn't ever go to 6%. It didn't ever go to 10%. It was always 8. And it was like this for literally years, right? And I'm like, why do all. Why do 8% of people always buy this? Like, like, you know, they're different groups of people. And it turns out that certain things, like attention vortexes, like Elon Musk being Elon Musk, is actually very predictable, right? So, so in a way, predicting people's affinity to buy assets is far more predictable than predicting the future. So, so that was sort of like the frame that I, I took was that, like, you don't know in advance who is going to be the vortex of attention. But once you know that they are, it's very predictable that they're going to continue to be that. And so that allows you to create like a more predictive mental model of, of the world than like a lot of people in macro trading. They're like, I think this is going to happen. This is where the puck is moving. I would rather be like, yeah, I think like 40% of people who see GameStop GameStop come up with a Pokemon card release are gonna buy the stock and that's gonna drive the price up. That's, that, that's something I can wrap my head around. I don't like predicting the future when it comes to trading. So I think that's like how I got into it. And I don't know if that answers your question.

[Podcast Host]

It, it does, but it's, I mean there's just so much to cover here. But I also want to understand where that model breaks, right? Because at some point that model falls apart. You can't say people like 40% of people that come across Cardano are going to buy it at Infin at some point they, they stop buying it.

[Alex Good]

Right?

[Podcast Host]

And so like how do you assess, how do you assess that risk?

[Alex Good]

Actually Michael Sailor is a great real time example of where the model breaks.

[Podcast Host]

Okay.

[Alex Good]

Fragmenting liquidity. Like so, so for example, the Dandelion Te example, if you launched another Dandelion T that was very, very similar to that Dandelion T, it would break the model. Um, if you launch STRC in addition to mstr, you break the model because you fragment liquidity, you fragment attention into two different things which suddenly become comparable, which previously weren't. And also trust matters a lot. So that the other thing about the Dandelion example is it was like entirely based on product reviews. So if their product review went from 4, 5 stars to 3.8 stars, like if you start to lose trust in Michael Saylor, it's like his star rating going down and then the conversion rate drops. And so like there are things in real life that affect these conversion rates. And the most direct way to drop your conversion rate is to drop a competing product. So like Elon, dropping SpaceX is unambiguously bearish for Tesla stock, right? Because it's, it's like an attention of fragmentation. Enduro launching an IPO will be bad for Palantir stock because it's, it's the same E Commerce dynamic with competition and that's the most predictable fragmentation. And, and generally what you Want to do like. Actually, this is why altcoins have such a hard time, is because they are playing for the same pie. Bitcoin is, doesn't have any competitors, right? Bitcoin doesn't. There's not, there's not another store of value asset that has successfully argued that like, you know, we just have like a fixed supply and that's just what we do. Ethereum and Salana are fighting and then all these other L1s are fighting for their pie and it's very competitive. And so. So I think that's like how the story breaks down.

[Podcast Host]

That makes sense. So you actually worked at Paler?

[Alex Good]

I did.

[Podcast Host]

Was that out of college?

[Alex Good]

I worked at City fx, Equity drives and then got picked up at Paler.

[Podcast Host]

Right. And so when you were, when you were at Paler, what were you, what were you doing for them? Did this, was it data analysis?

[Alex Good]

Yeah. So I was like, you know, Peter Thiel and Bridgewater, they built a product called Palantir Finance and I was one of the first users of the product. And so I was very fortunate to have like a group of people train me at a young age to like do all these quant trading strategies. I had no idea to do like. And, and then eventually I realized because I was such an early user that I had a lot of leverage actually. So I was like, you have to hire me because I'm the only person who knows how to use this product. And so I worked on capital market stuff. So we worked like the biggest project. I did two big projects. One was the application of credit card data to predicting large scale purchase decisions at the CIO office level of a bank. So trying to like basically predict macro slowdowns. And then I also worked on Swift Data and processing both like, you know, compliance for Swift Data and also converting Swift data into once again macro signal. So it was always kind of like the two business lines are always. There's like a revenue side where you're like, how can I take this data to make more money for the CIO office? That's the fun stuff. And then the bread and butter is like, you know, this guy is selling barrels of oil at $130 and the price is $80 and it's probably transfer pricing and like, you should do something about that. So that's always like the two sides of a Palantir deployment is like, help the business lower its future fines on one side and then the other side is like, once we've lowered your fines, here's the cherry on top, here's the

[Podcast Host]

revenue boost So, I mean, so you actually. I didn't actually realize that Palantir had a finance side to it that you were. That you were working on. And where is that today? I mean, you look at what's happening in the world of AI and as AI applies to finance, is that sort of what Palantir was doing back then? Was it just aggregating data or were they building models to actively trade?

[Alex Good]

They were really early on machine learning. You know, they would work with really big oil companies early on to kind of make these, like, lead lag signals where it's like, okay, you have this many shipping assets, like, load this into the Palantir ontology and predict, you know, if there's going to be a blowout in a spread of oil. And that would go to their capital markets desk, but then it would also go to their shipping groups. And so eventually that be. That was like.

[Podcast Host]

In our.

[Alex Good]

In the early days of Palantir, people hated the stock, people hate the company because there's like, it's just a bunch of guys coming up with these insights and like. Like pro, like pseudo productizing it and giving it to the CIOs. And eventually what Palantir evolved into was a much more elaborate product. Right. So they eventually productize all of this and it stopped being consulting and it started being delivering this via Foundry and other products. So, like, there's different products. One of them is Gotham, which is a security product. And then Foundry and other Ontology products are more revenue generating. And I think their business is split kind of like 50, 50 between this sort of commercial business and government.

[Podcast Host]

But you're kind of bearish on Palantir now, is what I'm hearing from you. You're tweeting a little bit about the fact that they're in a fight with Anthropic and OpenAI. And so what's your. I think a little bit of the framework is it almost seems like everybody is in a fight with Anthropic and OpenAI. Every week you see a new release from these frontier labs that could take out companies in this world. Like, what. What's your view on what's happening in the world of AI? Like, are we seeing a. Are we seeing just a brawl out. Out in public between all these companies?

[Alex Good]

Well, I think you're seeing a really specific brawl because Alex Karp called out Dario Amode, like, basically called him publicly

[Podcast Host]

in an interview, and then I somehow missed that part.

[Alex Good]

Yeah, he. Well, basically he. It was kind of like a quote tweet, you know, because Dario is saying like, oh, we're going to have 10% unemployment. And then CARP is like, if you think you're going to have 10% unemployment, well, guess what, news flash, you might have a high eq, but you're actually, you know, it's sort of like they're starting bigger and bigger fights. And yeah, I am bearish on Palantir right now. And the reason is just because the assertion of palantir is that LLMs don't work out of the box. And they say you need Palantir for LLMs to work. And I'm just like, is that because

[Podcast Host]

of the underlying data or.

[Alex Good]

Well, yeah, they say like, in order for your business to like, properly use LLMs and avoid hallucination with your large data sets, you need to have an ontology baked in so the agents know what to interact with. And I'm like, I just know that's not true, right? Because like, I use LLMs all the time without any palleter.

[Podcast Host]

Can you, can you clarify that? When you say need to have an ontology baked in?

[Podcast Producer/Moderator]

Yeah.

[Podcast Host]

What do you mean when you use the word ontology?

[Alex Good]

So in Palantir world, there is a model. So, so the, the origin of Palantir is actually interesting. So the, the first use of Palantir was like, how do I know that I'm killing the right terrorist? Because if you try to go to Afghanistan and kill all the people with beards driving a Jeep, then you're going to kill everyone and you don't know who's who, right? And it's like, okay, like, how do you even know that Osama bin Laden is Osama bin Laden? You know, it's like, well, for the Toyota Hilux, what's like, you need his license plate number, you need his known associates, you need his interactions with other people, you need his bank accounts. And this idea of like, these things that comprise Osama bin Laden are a quote unquote ontology. And they say in order to target the right things, whether they be financial assets, whether they be military personnel, you need to have a higher level ontology to map onto it so that you know that you're working with the right stuff. Now, in the world of AI, they're using the same argument. They're saying, in order for your AI agent to know that it's interacting with the right data sets, you need to label the data sets effectively. You need to have a model for when they've been acted on by a certain employee at a certain time. In order for this all to work, that's the argument. But like if you work with AI in real life, you know that that's not true. Like you can point an AI at your code base and just be like, yo, figure this out and it will. Right? And, and, and actually as AI models have become more capable, the need for ontologies has decreased linearly. Right? So, so there's all these like studies of prompting and how effective they are and like all the major labs are basically saying prompting is less important than it's ever been. You don't need to paste a two page prompt into your model for it to do the right thing anymore. Now you can just be like, build me a great website and it'll do it. So, so that's like kind of real time evidence that, that the use of ontologies is like a hack to make AI models more performant. And then you know, the other thing is like there's a lot of fragmented attention. You know, like OpenAI is launching FD there everyone uses the word forward deployed engineer.

[Podcast Host]

Right?

[Alex Good]

So OpenAI has forward deployed engineers. Anthropic has four deployed engineers with Golden Sachs. So it's like what Palantir used to be special because it was the only person on the block with like a intelligence product and now they're three. So it goes back to what we were talking about, about fragmenting attention. Like when there are three things in the store and instead of one, guess what if you're trading at a hundred times sales, like you're going to face investor headwinds.

[Podcast Host]

Would you agree with the statement that structured data is less important but raw data is still as important as it was before?

[Alex Good]

Well, the ability to turn raw data into structured data has never been cheaper.

[Podcast Producer/Moderator]

Right?

[Podcast Host]

That's what I'm getting.

[Alex Good]

And, and so you could argue that the, the value of raw data is definitely going up a lot. And that's something you're, you're seeing in the market, right? It's like the new drop shipping is data acquisition. Right? Like, like everyone is starting a data firm to sell data labs because you, it's much, much easier to do it.

[Podcast Host]

And, and what, like what, maybe you can talk about some opportunities in that, right? Like what are you seeing anything there? Are, are you working on anything in that?

[Alex Good]

Yeah, I mean my, my sort of view is that, you know, we've seen a crypto protocol do this right Grass and they sell data to labs. I am not interested. Like my premise is that most people in crypto are here to speculate and the, the information that they generate is very rich and Very valuable. And like if you actually think a data source is valuable, you shouldn't sell it, you should monetize it. And so that's sort of like what I'm working on is like, how do I generate the richest possible data set with a group of pseudonymous actors? Monetize that information instead of selling it to an AI research lab. Like just monetize it internally.

[Podcast Host]

Right. And, but that's, I think for, for most people, most def. Pretty difficult. I think one thing that I always come back to is that AI, I think for high agency people that really want to get things done is this massive tool of leverage. But your average person isn't taking advantage of it. Right, in any, in any meaningful way. I think most people are using it as just another chatbot or an assistant and people don't really go past that or beyond that. But what does that, what, what does that mean if you can start to build? Oh, you can start to have individual people build. Billion dollar companies do this by themselves. Like where does that leave us? When do you agree with the statement that AI is making the vast majority of people useless?

[Alex Good]

I don't think, I think it changes the use case or like we are not at yet at the point like we're still at full employment. Actually like a lot of these AI unemployment things have yet to kick in. One yet to kick in.

[Podcast Host]

Do you think they will?

[Alex Good]

I do. And, and I think, I think a good example is like Figma Stock, it dropped 85% and their headcount went up or like Accenture dropped 60% and their head counts up. They have 800,000 employees. Right. So, so, so we know that Accenture hasn't fired anyone and the market has crushed their stock 60%. So it's, it's somewhat safe to say that the, the, the, the employee reduction is yet to come because it just hasn't happened and the employment statistics don't reflect it. And actually like, so there's like this huge disconnect between like what Amode and, and Altman are saying about this existential crisis and we need mmt and then the employment report comes out and you're like, we're like full employment. You can't hire people. And do I think that people are going to lose their jobs? Yes, I do. Have they lost their jobs yet? No, definitely not. And like I think the most interesting primitive is not that we're going to have these solo shippers, it's more that there are a lot of people in the same boat. There are a lot of Accenture employees who are about to get, you know, laid off. And then the question is like, how can you use collective action to extract economic advantage? I, I think that's like the interesting question because, you know, there are different ways to, to approach it. Some people are like MMT Maxis, right? They're like, the way that we use collective bargaining is that we all vote to give ourselves money. And you're like, okay, well what would that look like? It's like, well, MMT is actually quite hard to distribute. The taxation would. That would be required because, you know, we're seeing like global interest rate markets are not in a happy spot in terms of like government spending. So the idea of like doing MMT on top of the current, like JDBs blowing up is hard. And so you're like, okay, well you need taxation. And like, what does that look like? And, and that probably is like central bank digital currencies. And so, so I think the, the thing that's going to happen is that more and more people are going to be focused on saying, okay, we tried to escape the permanent underclass. We didn't. We're all in the permanent underclass together. Like, what are we going to do about it? You know, and that, that, that's like a more interesting question. And that's something that hasn't kicked yet because people haven't really. It's like a meme right now.

[Podcast Host]

Right. I mean, but people really do take it seriously. And I think that's actually a premise of why a lot of people listen to this podcast in particular and, and other financial based media news is that people are trying to figure out how to like one, how much time do I have left? Right. You're kind of saying it might actually be more elongated, I think, than what people are claiming right now or what people, you know, what Dario and Sam are saying. And then, you know, how do I. Where do I put my money to escape the permanent underclass? And is it possible even to escape? Right. And so I think I kind of want to start with, with one and then you can walk me down what you think is going to happen. Like, how long is it going to take before we start to see these unemployment numbers kick in and we start to see this permanent underclass actually form.

[Alex Good]

I think the next. I think what's going to happen, Like, I literally think it's like the unemployment should start kicking with within three months. And it's just because of the Accenture.

[Podcast Host]

Within three months.

[Alex Good]

Yeah, because the Accenture situation was so extreme. Like the stock dropped 26% a day. Like, like it's, it's one of those moments where the, the management, it's like if they weren't awake before they, they woke up real fast. Like the, the software indexes are not bouncing back. Like the, the really egregious over hiring firms like Salesforce, the market is just crushing their stocks. And so the market is being very, very clear with companies like you need to do R S and people didn't want to do it and they're going to be forced to now because their stocks are down so much.

[Podcast Host]

Do you think there's a trade in that, that once they start laying people off, maybe these stocks bottom for a little bit?

[Alex Good]

I think so. I, I think, I think some companies that have credible AI turnaround plans where they could genuinely deliver their software for much less. Like, yeah, they could have like crazy terminal EBITDA margins. And these things are trading at like, you know, actually the, the joke is that, you know, commodity companies right now are oftentimes twice as expensive as software companies. And the big dis used to be that, oh, you're trading like a commodity. It's like, well, dude, now commodities are twice as expensive as software. So, so software is, is kind of bottom of the barrel multiples. So, so the bar for them to start firing people and delivering a product is like really appealing. You know, the like stuff like Nintendo, it's not just like software, it's like people who were competing with enterprise for stuff like memory. Like Nintendo just couldn't launch consoles because they couldn't afford memory. And so their stock is down, you know, 60% year on year and you're like, okay, well what if memory breaks and then, then it can rebound? So, so yeah, I think there's going to be a lot of opportunities. You know, especially like one of the interesting AI developments is that, you know, you saw all this like really, really hype stuff with etching. Like all the, the VCs were like saying, oh, there's a new fundamental chip breakthrough that essentially is like what happened in crypto with ASICs where you're like, okay, rather than serving a model that's massively memory intensive with inference, what if you just literally put a model directly into an asic? Like then you could run physical model like it. Rather than having a generic gpu, you have a specialized GPU with a specific model running on it, which would drastically cut memory usage. And so I think like the, the interesting thing is like if you remove the, the overhang of a lot of these quote unquote, Bottleneck trades. A lot of companies that have been just destroyed by the bottlenecks are going to like bounce. Right? So, so I think yeah, there's, there's going to be a ton of trading opportunity.

[Podcast Host]

Like, like maybe, maybe you can talk about some specific companies and how they're gonna. If you have.

[Alex Good]

Yeah, Nintendo.

[Podcast Host]

Yeah, like Nintendo's big. Okay. Yeah.

[Alex Good]

I mean I think the other thing is like we saw the lib gen settlement with Anthropic. Right. And essentially it's like Anthropic scraped. Well, I mean Lib gen scraped all the books in the world and then Anthropic train on Libgen and then there's a big copyright settlement. People have proven for example that you can like get 97% of Harry Potter I of chat GPT. So you can just like prompt chat GPT to get Harry Potter and

[Podcast Host]

that's

[Alex Good]

a problem from a copyright perspective.

[Podcast Host]

Right.

[Alex Good]

And so like there are all these companies that have like Nintendo has a great IP franchise. So if you're like, if you're kind of bullish on non enterprise or more consumer type stuff, there's a world where like all future AI Marios pay Nintendo. Right. Um, so Games Workshop would be another one like you know, Warhammer 40,000. That stock has done a lot better than Nintendo.

[Podcast Host]

That would actually be a huge value unlock. Yeah. For, for Nintendo if they actually allowed that to happen.

[Podcast Producer/Moderator]

Yeah.

[Alex Good]

Right.

[Podcast Host]

If they allowed people to just create games with their own IP using AI, I mean that would be massive.

[Alex Good]

Yes.

[Podcast Host]

And I assume that you, you're thinking that this could apply to other areas as well.

[Alex Good]

Yeah, Anyone with like core canonical ip, Lindy ip. Right. Disney, Nintendo Games Workshop I in, in many of the like Hasbro like D and D ip, a lot of these things are very, very popular. Star wars and they all have really radically different valuations. Right. Like you know, some, some of these charts are up to the right, some of them are not. Right. So, so there are different opportunities.

[Podcast Host]

And I want to go back to the, the point about you think that there could be mass unemployment coming in three months or the beginning, the beginnings of unemployment.

[Alex Good]

Yes.

[Podcast Host]

Take that a step further and talk about, let's say you go 6 months, 9 months, 12 months, 24 months down the line. I mean you've written about sort of the black print and maybe get, get into that and talk about how you think the world is going to change because of these new tools that we have.

[Alex Good]

Well, yeah, I think, I think there's a point and I think we've already crossed the point where this is like, this has stopped being a technological phenomenon, has started becoming a political phenomenon and it's already showing, it's going to show up in the midterm elections. Right. Like the next big checkpoint that I think would validate my worldview and I guess like to, to succinctly summarize it, it's that people won't vote for a right wing accelerationist system which doesn't benefit them economically. How. And you know, the, the, the math is actually crazy, right. Because like, you know, they're 50,000 Nvidia employees and the Nvidia is worth single handedly more than the entire Russell 2000. And the Russell 2000 employs millions of people. Right. So, so, so there is like this extreme imbalance between like the number of voters at Nvidia and the number of voters in the Russell 2000. And right now the market kind of assumes that like this will go on forever, that there's no Democratic outlet that is kind of like Trump the Stan all the way and that like, you know, the right wing will keep winning. For some reason I'm like, no, I don't think so. I think what's going to happen is that people are like actually the people like the typical Accenture employee who loses their job is going to be quite effective at coordinating like ground, like grassroots Bernie Sanders votes. Right. Like those are competent people.

[Podcast Host]

Yeah. And you're sort of seeing that, I think with the dsa. The DSA is extremely effective.

[Alex Good]

Yeah.

[Podcast Host]

In what they've done right now. And they're installing socialist candidates sort of across the board and the, the competency levels are going up among these socialist politicians. But it's kind of true that on the right you also see the rise of populism. It's a little bit of the horseshoe theory here where it's just different constituencies that are getting the benefits. I think for on the, on the right and on the left, I think both are appealing to, I mean, whether it's giving subsidies to farmers or giving subsidies to like people, people in the cities. So it, it almost seems like that's where our politics is headed.

[Alex Good]

It's also like Trump, like, you know, Trump went in and regulated anthropic. You know, he already kind of started the process of the political system blocking major model releases. And so that's a big deal because now that the gloves are off, it becomes acceptable to, to regulate and sequester AI in the name of the quote unquote public good. It's normalized now on the right and on the left, previously that would have been a Biden policy. Like, that would be a Biden move of like, oh, we're going to stop this AI model from launching. Now it's a Trump move. And so I think you're going to see, you know, that the core thesis of the black print is that the political system in the United States is not designed for hyper acceleration. Like the, the, the fantasy that people have that we're going to allow like genetic, like peptides are a good example, right. Like the FDA is like, it's definitely not, it's not very clear that peptides are even going to be legal. Right. Like everyone's shooting these things up, but it's like, okay, what about human test? Like, what about human trials? What about the process of how we approve drugs in the United States? Like if you look at the history of US medicine, it's never been like, yeah, let's yolo this vaccine. Except for like the one time we

[Podcast Host]

yolo one time ever.

[Alex Good]

And then it like did not go that well, right? Like the one time we yoloed a vaccine, like, you know, there's myocarditis. It's like a problem, right? So the backdrop of like actually right now the consensus trade is biotech, right? Everyone is like long biotech because they're like, okay, like what the AI companies have to do in order to prove themselves is to launch a, like, who doesn't want to cure cancer? What if anthropic cures cancer?

[Podcast Host]

Do you think that trade is, it's truly baked in already?

[Alex Good]

Well, I think it's gone the wrong, like I'm bearish on like the application of biotech and AI. I mean, okay, and the reason is just national security. Like the tail risk is so high after, after we saw like Wuhan, you know, it's basically like all it takes is one guy running a unsanctioned experiment on a bat. Like, like there's a guy like doing like stuff in his garage with an AI model. And I just don't think that type of stuff is like gonna be tolerated in the medium term. I think you'll probably have like the, the second you have one event, just one event, it'll be banned. Right?

[Podcast Host]

But don't, but don't you think that, I mean, the, these pharmaceutical companies are at this point quite highly regulated and so wouldn't, wouldn't you assume that they would be able to figure out how to integrate AI for drug discovery? That is in the lane of safety and that would just accelerate their drug discovery process. But it would be overseen by the same regulators that we have now?

[Alex Good]

Well, it depends on what they're doing and who has access to the AI models. And then it's also like, okay, what's the uncapped risk of this behavior? And if the uncapped risk is something like Covid developing or, or some sort of virus or unintended consequences, it'll be really hard. I. I think people are overly optimistic about, like, deregulated AI acceleration. Like, actually, like, the reason is just because of Fable. It's like, if people are already worried about Fable debugging your code base, which is, like, why they pulled Fable. Like, imagine if Fable is creating a

[Podcast Host]

new peptide, Wouldn't that argument also apply to the development or the deployment of AI in, I mean, consulting firms and law firms sort of across the board? Like, if the government saw that it was actually going to cause tremendous job loss, wouldn't they try to step in and stop that before? At least we have social programs in place to deal with that follow. Because our government's not stupid. I mean, they're, they're incompetent, but they're not necessarily. They can see that this is going to happen. So wouldn't you expect them to act?

[Alex Good]

Yeah, you, you would. And you think they already would have, but they haven't. And that, and that's why I think the job loss is actually going to kick. Because, like, the figma, like, it's like, it's like, it's kind of like FIGMA is already down 80%. And it's because of a good reason. And it's because the current models like Fable and GLM 5.2 can actually deliver a good experience. So the AI that we already have is kind of going to, I think, go after the laptop jobs. Right? Like, and I don't know if AI is going to be able to, like, for example, like, the Andrew King, like, we're going to have humanoid robotics. Like, I'm on. I'm totally on the other side of that.

[Podcast Host]

You don't think human robotics. I mean, this is, this is good. Let's dive into that.

[Podcast Producer/Moderator]

Yeah.

[Alex Good]

What?

[Podcast Host]

Like, everyone is talking about human under robotics. I had Andrew Kang on this podcast. He gave me the whole spiel that specialized robotics are not nearly as useful as generalized robots. And so therefore, we're going to see robots in the next five years doing construction. We're going to see them in assembly lines, we're going to see them in people's homes as cleaners, we're going to see them as personal assistants and you,

[Alex Good]

you disagree with that? Yeah, I mean Trump banned port automation, right? So, so even, even port automation was a no, no.

[Podcast Host]

Right.

[Alex Good]

And on the right, now imagine it on the left, right? The idea of the government on either side of, of the current political spectrum rugging blue collar workers by allowing humanoid robotics, like given the history of self driving is like laughable.

[Podcast Host]

But wouldn't that put us massively behind in our fight with China? Like if we're not willing to adapt, adopt automation, we're kind of mess, mess messing up.

[Alex Good]

No, but I mean I don't think that's like how you win elections. I think you, you win elections by telling people you're going to keep your job. I don't think that the vision of like humanoid robotics is probably exciting to a lot of people. I think it's like deeply unpopular actually. Like if you look at like societal perception of AI right now, it's already very unpopular. Like before people have started losing their jobs. Like once people like we're at like what, 4% unemployment? Second you get like a kick in unemployment and it's due to AI and people already hate it. It's going to get way worse and then there's going to be regulation on just raw AI yet alone. Humanoid robotics, like it's, it's sort of like this is the area that's going to be regulated. And we already know with self driving cars, like what that looks like it means that like they are literally not allowed on the road. And when they are allowed on the road, like periodically they get pulled. It's like okay, someone attacked a waymo and like it's, and we don't know why they did it. And now we're pulling waymos off the road for like a month, right. And, and it's going to be way. And that's with cars, like it's going to be worse with, with humanoid robotics.

[Podcast Host]

So this kind of implies maybe I'm putting words in your mouth that the AI bubble is close to an end. That what we're seeing with a boom in data centers and the massive rise of the stock prices of all these hyperscalers, it almost implies that we're close to the end of that. Because you also think that we're close to the beginning of regulation if we're three months away from.

[Alex Good]

Well, I don't think, I don't actually, I disagree with that because I think, you know, back in crypto world, like right when Truth Terminal came out, everyone thought that we'd have all this AI entertainment. Like we're starting to see it with Seed Dance, right where there are these like kind of cool videos. But I don't know about you, but I don't actually watch any of this AI stuff. Okay.

[Podcast Host]

No, I mean, I'm not really interested in fruit videos.

[Alex Good]

It's like, it's like fun. It's like funny, you know, but, but it's not, it's not that good.

[Podcast Host]

I've definitely been got by an AI video before.

[Alex Good]

Yeah, like you, I watch it and

[Podcast Host]

then I watch it again, I'm like, wait a second.

[Alex Good]

Yeah, some of the, some of them, I like the inspirational ones like where they get like kind of the, you know, the athletes or the, the automated, you know, like Mike Tysons and.

[Podcast Host]

But I get a lot of like historical AI on my. Okay. On my slot feeds.

[Alex Good]

That's pretty good.

[Podcast Host]

Well, like people are, you know, they're like recreating Napoleon's battles using AI and I'm like, okay, that's actually pretty, that's like, yeah, it's compelling.

[Alex Good]

But so, so I mean like I, I think we're pretty early on AI. You know, I, I don't think we've, we've fundamentally seen entertainment or generative worlds really kick. Like, I think, I think one thing you know for sure is that personalization delivers massively. Bet like, like if you do the math on the cost of an AI video right now, like a personalized AI video, it's something like like $55 for a reasonable video and it's not that good. Now if that goes down to $2, which is believable by in two years, basically you're going to have mass generated personalized videos for everything. Whether that's like entertainment, whether that's video games. Also the, the, the talks per second is going up exponentially, which means that you're going to have basically compelling computer game NPCs and improve social media algorithms. So, so, so like my core bet is that AI just makes society look more like it already is. Like, like we've already seen what happens. Like the government regulated nuclear technology in 1945 and they basically said you're not allowed to have a nuclear weapon. And if you do, if you do generate a nuclear weapon, we're going to bomb you and you're not allowed to do certain types of physics research and if you do, we'll probably kill you. And, and then like what happens? It's like, okay, well what is allowed? Computers are allowed, digital economies are allowed and entertainment is allowed. And it's like that the same exact thing is about to happen with AI where you're like, what will be allowed? How you, how do you pay for the data centers? Is it like you cook everyone's brains? Right? And so that's sort of like, like the, the actual thing that will happen is that we have a society which is more, more online, more digital where things get more expensive and productivity doesn't necessarily. Like I, I'm actually like right now, annualized productivity like as of the recent quarter is like 0.6% annualized. I'm like, dude, like, right, like, like Microsoft CEO said that we'd see 10 annual productivity increases. I'm like, that's a lot different from 0, 6% and 2.8 year on year, right? It's not 10. And so I just don't see the, you know, and that's why things like Robinhood and like Interactive Brokers are like King maker or like hyper liquid or like king makers, right? Because people are not actually generating more work, they're generating more capital and that capital is being recycled into an attention economy. And I think that's just going to continue. I think that's sort of like, say I'm like completely on the other side of, you know, Andrew King or a lot of these sort of like even Elon, right? Like with SpaceX, you're like, okay, it's trading at like some ungodly multiple on the premise that we start, you know, colonizing Mars or launching space data centers in 2029. Like I'm not sure that's going to happen. I think it's easier to underwrite the government cracking down on things and having more of the same things that we've had since like 1945.

[Podcast Host]

This is kind of the opposite of the Doomer thesis in a way. Well, I don't think the world's going

[Alex Good]

to end, I think, right. I, I think the world is going to get like just more distracted, more speculation and that I do think the economy is going to get crushed because I, I think that people assume the AI is going to get us out of the debt bubble. Right? Like the, like the, the assumption that people have is that, that, that if we have a massive productivity increase, then we're not going to have to worry about our World War II level of spending. And it's like, okay, like if that doesn't happen, then it's basically a sovereign margin call. And that's sort of like why I'm in crypto, you know.

[Podcast Host]

So I mean, I think that's as good a place as I need a, to wrap up sovereign margin call. That's, that's. I think this is. I've been pretty bearish on bitcoin. This has maybe actually made me a little bit more bullish on bitcoin, just this entire talk. And thank you for sitting down with the Thousand X pod. I mean, this was, this was, was awesome. And if anything, I think this was an advertisement for better, better financial planning out there for people if we're heading into. If we're heading into a collapse. So just keep up, keep on listening. We'll give you guys some good updates on what's happening. And thank you, Alex, for joining us. Yeah, thank you. Cheers. Foreign.

[Podcast Producer/Moderator]

Nothing said on the Thousand X podcast is a recommendation to buy or sell any investments or products. This podcast is for informational purposes only and the views expressed by anyone on the show are solely their opinions, not financial advice or necessarily the views of one KX Media. Our hosts, guests and the one KX team may hold positions in the company's funds or projects to see discussed.