The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 5,759 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 49 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Taggar: Model commoditization sets up AI app startups for fantastic year
“Gemini surge, especially over the last few months, just feels like it returns us to a world of where exactly that, like the models are all essentially commoditizing each other. And it's just like the application layer and the startups are going to set up to ha…”
Diana Hu: AI's future Google- and Facebook-scale startups have not started yet
“Startups like the future Facebook or the future Google are yet to be started because those come in in the deployment phase, because right now I think these things, things are still getting built up.”
Tan: Boom Supersonic is using jet engines to power AI data centers
“Boom supersonic, instead of making supersonic jets right now, is on this good quest to create enough power for a bunch of these
AI data centers that are being built right now.
They use jet engines and even those like are so bad, you know, the supply chain for …”
Tan: Environmental lobby abuses CEQA to halt innovation and housing
“In California we have CEQA, which is totally abused by the environmental lobby to stop all innovation and building housing, by the way.”
Hu: A YC startup's 8B model beat OpenAI on healthcare benchmarks
“There's this particular YCE startup that told me that they collected the best data set for healthcare. And they ended up performing better than OpenAI and a lot of the benchmarks for healthcare with only eight billion parameters.”
Tan: GPT-4 wiped out YC startups' RL fine-tuning lead over GPT-3.5
“You know, we've also had YC companies where, ah, they had something that beat OpenAI, ah, you know, GPT-III.V and they were doing fine-tuning with RL, but then, ah, yeah, GPT-IV and then, ah, GPT-IV came out and, ah, you know, basically blew their fine-tuning …”
Taggar: Incremental model gains make finding AI startup ideas difficult again
“The models themselves have incrementally improved this year, but there haven't been like major steps forward that have shaken everything up, which is, has a knock on effect. Many episodes ago, we talked about how it was It felt easier than ever to pivot and fi…”
Taggar: Rising AI software expectations force startups to maintain pre-AI hiring levels
“AI is going to reduce the cost of, like, producing the time to produce things, and so then the expectations from your users and customers will just go up, and you'll need to keep hiring more people to satisfy, like, the growing expectations. I feel like this y…”
B2B brands should be weird enough to polarize audiences intentionally
“Like, it needs to be so weird that it polarizes. Every day we'll get a whole bunch of people talking about that website, and we monitor all our brand mentions online, and it's going to be like either this is literally the best thing I have ever seen, and we al…”
Skates: Amplitude is building a 'Cursor for analytics' product
“We're gonna go much, much bigger in December, January, and February where we are gonna be coming out with what we call the cursor for analytics, which I'm incredibly excited about, and I think will dramatically change how people use and leverage analytics”
Skates: AI product building must be technology-first, not customer-driven
“With the capabilities of AI, because they're so jagged, you, it's a technology first understanding of what is possible. And so if you go to your customers and tell them and ask them what they want, like, they're not even going to be able to describe what's pos…”
Skates: The top filter for founders is persisting when quitting is rational
“One of the really clear takeaways from any of these journeys is there is a point that you get to a year, maybe two years in, where From a rational standpoint, you probably should quit but for whatever reason those successful ones don't, and so that is the numb…”
Skates: Most successful founder CEOs leave after a decade due to scale
“Even if you look at the successful founder CEOs, after about a decade, most of them leave. And in my mind, it's actually for this very reason, because being a large company executive is different.”
Mignano: AI will eventually generate dynamic social media feeds without human creators
“Sora, to me, feels like this third, the start of this third phase where Eventually they don't really need creators to make content, right? Yes, today people are prompting, but you could very easily imagine a world in which you're just coming into the feed, and…”
Tan: Micro-creators with 1,000 to 10,000 followers are mispriced distribution assets
“When you're paying someone else, like the reason why that's interesting for consumer products is it's a mispriced asset generally still. I mean, Mr. Beast is not a mispriced asset. He's like getting his value from it. Like he's, you know, but It does seem like…”
Mignano: Sora proves AI labs can build net-new consumer apps that threaten startups
“Sora is kind of proof that, no, these labs, like, they have the taste and capability and the horsepower and the execution to build and ship net new products that also might run you over.”
Heller: AI application TAM is 1,000x larger when capturing labor budgets
“Today, the actual amount of money that we already know people and companies are willing to spend is the combined salaries of all the people they're currently paying to do the job. And that number is like a thousand X bigger. You pay 20 dollars a month to solve…”
Heller: Casetext built CoCounsel with plain Python, dismissing frameworks like LangChain
“And to be honest, a lot of the stuff that we built while building co-council was exactly like this. Every time you do this task, you're basically gonna take the same six or seven steps. And you don't need to have, frankly, like fucking Langchain or whatever. J…”
Fisher: Large enterprises are replacing SaaS purchases with AI-assisted internal builds
“Large enterprises sometimes aren't even going out and buying software from SAS providers anymore. They're like, I can just like Throw two people at cloud code and they'll build it and it'll be dedicated to the capabilities that I need for my organization.”
Fisher: Retrofitting Existing Products With Distribution May Beat AI-Native Startups
“It's natural to think it's better to build it a new product from the ground up that's AI native. Like that's like my startup mentality, like new technology revolution. You need to start from scratch if you want to build this right. But that might not be true. …”
Semi-automated companies allow single bad actors to act without human whistleblowers
“In a semi-automated world, that's no longer true. And it could be the fact that a single person could make a decision that changes the entire impact of a product. And there's no single person that might be aware of that except themselves. It gets extremely eas…”
Fisher: Post-AGI capital won't need labor buy-in, worsening wealth concentration
“But once AGI arrives, you don't need labor buy-in anymore. Right. Like you don't need folks like me to approve of the thing that you're building or of your morals or whatever. Right. Like capital begets capital in that world. And that can easily spiral out of …”
Fisher: Users choose honest AI over sycophancy when asked at principle level
“But I think if you take a step back, and you say, hey, hold on a second, here's two principles, and you can choose the AI that follows this principle or this principle, The first principle is that we're never gonna blow smoke up your ass. We're only gonna tell…”
Anthropic's Joseph: Compute matters far more than pre-training objective details
“I think that, like, the one sort of general intuition I have is, like, compute is the thing that matters. So, like, I think if you throw enough compute at any of these objectives, you're gonna get something that's probably pretty good, and can kind of be fine …”
Joseph: LLM training requires collaborative infrastructure work over publishable research papers
“And to do a project like training a large language model requires a lot of people to collaborate on like a really complicated piece of infrastructure that isn't going to be a paper, right? Like you're not going to publish like, oh, I got a slightly, I got five…”
Joseph: Sparsely linked long-tail data may be most valuable for frontier AI
“And it might be that like, that data ends up more valuable because you, everything that's linked to a lot, you've already got. Like at some point, you're maybe like going for the tails, or you're going for the stuff that no one's ever, like, you know, it's onl…”
Joseph: Training purely on raw LLM generations cannot produce a better model
“Theoretically, I shouldn't be able to train a better model than that. Like, I'm just going to get the same thing out. So I think that's-”
Nick Joseph: Third parties can steer frontier AI labs by publishing evals
“Like, it is the case that, like, the labs right now are really driven by getting good eval scores. And it's hard to make them, and anyone can do it. There's no comparative advantage to having the model to making an eval. So I do think it's actually, like, an i…”
Anthropic's Joseph: Certain AI Alignment Pieces Will Move to Pre-Training
“I do think at some point there will be, like, some pieces of alignment that, like, you do want to export back into pre-training because that might be a way to, like, Put them in with more strength, like, more robustness, kind of, or more core to the intelligen…”
Anthropic's Joseph: Scaling alone likely will not achieve AGI without further paradigm shifts
“Like I think the sort of shift towards more RL is like one paradigm shift in the field, and I think it's, I think there will probably be more. I think a lot of people sort of argue about like, oh, it's like, you know, current paradigm's enough to get us to EGI…”
Anthropic's Nick Joseph: Frontier pre-training teams primarily need engineers, not researchers
“The thing we, like, most need is engineers. Almost always, like, throughout, like, the entire history of this field. It's, like, the case that you throw more compute, the thing kind of works. The challenge is, like, actually doing that.”
Nick Joseph: Scaling standard models is easier and more reliable than inventing novel architectures
“It's just that scale is easier, and it's more reliable, and I think you, we're still seeing really big gains to that.”
Pollak: Four maturing unlocks have created crypto's golden building era
“Those, you know, four things
Chain scaling, regulatory clarity, stablecoins emerging as a really powerful tool, and then wallets getting simpler and simpler, I think have matured to the point where we've entered the golden age of crypto building, the golden ag…”
Pollak: Content and creator capital markets will become a major asset class
“I think one of the biggest asset classes that we believe is about to emerge is content and creators and Creator capital markets where for the first time you're going to have creators that start to say, Hey, I want to use this new platform to raise capital for …”
Levie: In 10 years, most enterprise work will be previously uneconomic tasks
“If we go 10 years into the future, The vast majority of work that gets done in 10 years from now will be work that today is in that category. It's the work that like right now we can't even attack because we're like, I'm not going to hire somebody, pay them a …”
Levie: 100 Startups Created Between 2024-2028 Will Reach $5B to $20B Valuations
“There will be 100 startups that get created between last year and in three years from now that all become five, 10, twenty billion dollar companies because they're able to find the next set of nouns and verbs”
Levie: Customers will pay for workflow software rather than raw tokens
“So eventually we're going to get to a point where customers are no longer going to just be paying for the intelligence tokens. They're going to be paying for the workflow software that goes on top of the tokens themselves.”
Levie: AI tool makers will maintain flat pricing despite falling compute costs
“It's like, it's 20 bucks a month, it's 50 bucks a month, but we know that in 10 years from now, they'll probably be able to drive down their raw materials lower, but we won't be able to command lower prices for those things, because it's just like within a rea…”
Levie: Incumbents will only sell AI agents to existing install bases
“Because I think incumbents are only going to be the agent providers for their existing install base, which means that there's going to be tons of opportunity for so many more agents that those incumbents aren't already selling into.”
Masad: Build imperfect agent products now; improving models will validate them
“I keep telling my team, we need to be okay with building crappy products today, ah, because two months down the line, the models will get better, and your business, your product will suddenly become viable.”
Masad: Execution infrastructure, not code generation, is the bottleneck for AI agents
“Agents that can write code, ah, is actually the easy part. The hard part Is the infrastructure around it. Sometimes I call it the habitat for which the agent lives in.”
Masad: Replit has solved AI agent challenges Andrej Karpathy considers unsolved
“He talked about all the different things that are really unsolved, but in reality, we actually solved a lot of them.”
Masad: Anthropic's Model Context Protocol won't solve autonomous agent-to-agent coordination
“I know a lot of people think of MCP as such an agent to agent tool, but actually MCP is a more traditional RPC protocol. So it's not really going to solve this.”
Masad: Developers will reliably run 1,000 concurrent AI agents within two years
“Or plus, which I assume we're going to get to in the next couple of years, you can really spin up a thousand agents, give them a lot, thousand problems, and reliably be confident that like, 95% of them is going to work.”
Masad: Computer-use AI models will start automating real jobs within six months
“Right now, the edge of what's possible is like computer use, in my opinion, is really at the frontier of what these models could do, and I think over the next three to six months, they're going to get a lot better, and it's going to enable an entire new market…”
Masad: Tech-empowered sovereign individuals creating immense wealth will become the norm
“And this idea of like a sovereign individual, someone so empowered by technology, so empowered by these agents. That is able to create enormous amount of wealth individually is, is is, is going to be the norm.”