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 2,573 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 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
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: Software companies must shift from building apps to directly solving problems
“And for Replit, and I'm sure a lot of other businesses to survive, at some point Replit needs to stop being focused on making applications and start being focused on solving problems with software.”
Masad: AI model training has reliability limits without fast environment feedback loops
“I think there's a limit on how much the training can increase reliability, but I think the environment feedback and the ability to try things really fast is the way to get to the upper echelon of reliability.”
McGrew: FDE-led product discovery beats traditional sales-led discovery
“Sales-led product discovery, you're talking to people from the outside. And again, this is important very early on, but it's not as effective as the FDE-led product discovery, where you're solving these problems from the inside.”
McGrew: Building what customers ask for turns startups into consulting firms
“I think one of the other failures, by the way, that's even prior to that, and more, the easier failure to become a consulting firm, it's where you build the product in the field that the customers are asking for, rather than the one that's actually valuable to…”
McGrew: Startups should avoid FDE strategy unless no alternative works
“My first, second, and third pieces of advice to people who are thinking about trying an FDU strategy is like, don't,
Don't do this at home.
If you can avoid it, like it's probably bad for you.
Probably you're going to end up doing services.
And then only if yo…”
McGrew: FDE strategy succeeds by growing contract sizes rather than cutting customization
“In the product market fit strategy, you want to be doing less work for every customer, you want to be driving down costs, you want to keep the contract size the same. In the FTE strategy, you want to drive the contract size up. So you're doing more and more va…”
Legal AI innovation is scaling parallel queries, not prompt engineering
“And the big innovation there does not really come from, you know, how do you prompt and work with the model, but it's how do you make this run at scale? You know, how do you run a 100,000 queries in parallel at the same time and make sure nothing breaks.”
Blomfield: Discussing pricing early almost never scares off enterprise prospects
“Founders are often very afraid to have a willingness to pay conversation. They feel like if they bring a dollar amount up, it might scare the customer off. But honestly, that's almost always not true.”
Blomfield: Early startups should accept customer contract terms unless company-ending
“So I'd be pretty flexible on signing, frankly, whatever your early customers want, as long as it's not going to expose you to like unlimited liability or container clause that's going to transfer all the IP in your product to your customer or something company…”
Field: Design and craft are the primary differentiators in the AI era
“If you really believe that development gets easier and it's more simple to create software, it's faster to create software, then like, what is your differentiator? It's design. It's craft. It's attention to detail. It's point of view.”
Field: Designers and PMs, not just researchers, should build AI evals
“As you're, you know, doing developing a model or you're developing research ideas, You have to have good evals, and usually the researchers are the ones building those, and I think that's kind of just the wrong model. For us, at least, designers, my point of v…”
Kaplan: AI scaling trends are as precise as laws of physics
“We found that there's actually something very, very, very precise and surprising underlying AI training. This really blew us away that there are these nice trends that are as precise as anything that you see in physics or astronomy.”
Kaplan: Compute scaling drives AI progress more than researcher cleverness
“Basically you can Scale up the compute in both pre-training and RL and get better and better performance. And I think that's sort of the fundamental thing that is driving AI progress. It's not that AI researchers are really smart or they suddenly got smart. It…”
Kaplan: Founders should build products that current AI cannot quite support
“One is I think it's really a good idea to build things that don't quite work yet.
This is probably always a good idea.
We always want to have ambition, but I think specifically AI models right now are getting better very, very quickly.
And I think that's going…”
Kaplan: Broken scaling laws usually signal flawed training setups, not fundamental limits
“If scaling laws are failing, it's because we've screwed up AI training in some way. Maybe we got, ah, we got the architecture of the neural network wrong, or there's some bottleneck in training that we don't see, or there's some problem with Precision and the …”
Finn: Scale is necessary but not sufficient for open-world robotics models
“And so I think the lesson here is that scale is necessary for developing these models that can generalize in open world conditions, but they're subordinate to actually solving the problem. So you need scale, but it's not sufficient for the entire problem.”
Srinivas: Google's ad model disincentivizes providing direct search answers
“If you get direct answers to these questions with booking links right there, how are you going to mint money from booking and Expedia and Kayak and like, you know, all like same, same, same thing for shopping. How are you going to take money from Amazon and li…”
Srinivas: No AI product has in-app network effects yet
“No AI product has within app network effect. Like it's not like WhatsApp where if you build a WhatsApp rival, Meta has a definitely like a questionable brand, right? Like people don't necessarily trust Meta's products. They think like these are ad products. De…”
Srinivas: Browser-native agents offer superior reliability over MCP-only approaches
“That's the key advantage of the browser that you do not have if you commit entirely to just the MCP vision. If you commit entirely to the MCP vision, you require these third-party MCP servers to work reliably. Ah, the data that they send you, ah, on, with the …”
Srinivas: Foundation model labs will copy any high-revenue AI startup idea
“You should assume that if you have a big hit, if your company is something that can make revenue on the scale of hundreds of millions of dollars, or potentially billions of dollars, you should always assume that a model company will copy it. Mainly because the…”
Ng: The biggest AI economic opportunities must be at the application layer
“And even though a lot of the PR excitement and hype has been on these technology layers, it turns out that almost by definition, the biggest opportunities have to be at the application layer. Because we actually need the applications to generate even more reve…”
Ng: Subject matter expert intuition beats slow data for startup decisions
“Getting data for a lot of startups is a slow mechanism for making decisions. And a subject matter expert with a good gut is often a much better mechanism for making a speedy decision.”
Ng: Code itself is becoming much less valuable as engineering costs drop
“One surprising thing is, we're used to thinking of code as this really valuable artifact because it's so hard to create, but because the cost of software engineering is going down, code is much less of a valuable artifact as it used to.”
Ng: AI turns software architecture decisions into reversible two-way doors
“So choosing the software architecture of your tech stack used to be a one-way door. Once you're built on top of a certain tech stack, you know, set a database schema, really hard to change it. So that used to be a one-way door. I don't want to say it's totally…”
Ng: Product management is becoming the software bottleneck as engineering accelerates
“With software engineering becoming much faster, the other interesting dynamic I'm seeing is that the product management work, getting user feedback, deciding what features to build, that is increasingly the bottleneck.”
Ng: AI safety is a function of the application, not the technology
“Safety is not a function of technology. It's a function of how we apply it. So like electric motor, you know, You can't, the maker of electric motor can't guarantee that no one will ever use it for an unsafe downstream task. Like using electric, electric motor…”
Taggar: College students often extract better AI model performance than PhDs
“The technical expertise is now actually really like the missing piece for a lot of these things. And we consistently see, at least in YC, that college students are actually at the forefront of this stuff, like actually understanding how to use the models and h…”
Chollet: Displaying skill across tasks does not demonstrate intelligence
“Intelligence is a process, and skill is the output of that process. The skill itself is not intelligence, and displaying skill at any number of tasks does not show intelligence.”
Fei-Fei Li: World models require structured priors beyond brute-force scaling
“Constructing world model might be a little more nuanced. The world is more structured. There might be signals that we need to use to guide it. You can call it in the shape of prior. You can call it supervision in your data, whatever it is.”
Fei-Fei Li: Modern AGI fundamentally mirrors the original 1950s AI goal
“The founding fathers of AI who came together in 1956 in Dartmouth, you know, the John McCarthy and Marvin Minsky of them, they wanted to solve the problem of machines that can think, and that's a problem that Turing, Alan Turing, also put forward a few years e…”
Green: AI shifts tech paradigm from attention to relationships and affection
“The way I kind of like simply think about it is, is that for the last two cycles, let's call it the internet and mobile, we've moved from outcomes and attention into an area of relationships and affection. And I think that's much more dynamic and it's much mor…”
Nadella: AI energy consumption requires social permission and real economic surplus
“If there's one lesson history has taught us is that if you're going to use energy, you better have social permission to use energy. So that means you've got to make sure that the output of this AI is socially useful. In other words, if we really are not creati…”
Nadella: Change management is the real rate limiter for AI deployment
“So that change management is the real rate remitter, right? Because you're now taking the means of production in an insurance company, in a financial services company, in a healthcare company, in a software company. And saying, we are going to change everythin…”
Altman: AI companion value lies in background persistence, not hardware
“I think the key of her is not the little piece of hardware. It's that this thing got to a point where it could run in the background and feel like a sort of AI companion.”
Altman: Startups almost always win when industry clock cycles shift dramatically
“When the clock cycle of the industry changes this much, startups almost always win, and we've probably never seen it change this much.”
Altman: Energy will eventually be the fundamental limiter on intelligence scaling
“I cannot recall ever thinking until like after starting OpenAI that they were going to be so obviously related. That, you know, the, that energy would be the eventually the fundamental limiter on how much intelligence we could have.”
LLMs invert historical tech diffusion by reaching consumers before enterprise
“LLMs, like, flip, they flip the direction of technology diffusion, ah, that is usually, ah, present in technology. So, for example, with electricity, cryptography, computing, flight, internet, GPS, lots of new transformative technologies that have not been aro…”
Developers should build Iron Man suits, not fully autonomous robots
“Working with valuable LLMs and so on, I would say, you know, it's less Iron Man robots and more Iron Man suits that you want to build. It's less like building flashy demos of autonomous agents and more building partial autonomy products”
Truell: Chat text boxes are fundamentally too imprecise for controlling coding AI
“And then, you know, one thing I will note kind of harkening back to a last response is that even if you had something you could talk to that was human level at coding, Or faster and better, better than a human at coding, you know, sort of the skill of an entir…”
Truell: AI coding tools mirror web search's product-improving distribution flywheel
“One of the things that characterize search, and I think also characterize our market, is distribution is really helpful for making the product better. And so if you have lots of people using your thing, you have an at scale business, you get a sense of where t…”
Koomen: Developer AI tools lead by avoiding defensive corporate restrictions
“Developer tools are power tools, right? Developer tools by definition allow you to get to the bare metal, right? To get under the hood of what it, whatever it is you're working with. And so the teams that built these tools allowed me Full access to have this a…”
Palicha: 10-Minute Delivery Has Better Economics Than 2-to-4-Hour Models
“The insight was, yes, let's do 10 minute delivery, but also let's build out the full stack of commerce where we're able to run the logistics, we're able to Have a much better sense and selection on quality control and sort of that audacious thinking Put us in …”
Palicha: 10-minute delivery in India is a necessity, not just convenience
“Now, obviously at scale, the insight is that it's not just important because people are used to it, but it's just, it's a necessity because you've got a lot smaller household sizes in India. You've got a low penetration of four wheelers. You've got much more p…”
Thompson: 1970s Environmental Laws Now Block Clean Energy and Dense Housing
“The medicine of the 19 sixties and 19 seventies has become the disease of the 20 twenties. The very same policies that we used to stop the despoliation of the world 60 years ago now stop us from building dense housing, which is good for the environment, solar …”
Thompson: Modern Failures Stem from Refusing to Update 1960s Institutions
“Institutional renewal is the charge of every new generation. And when we fail to update on the systems that we built 60 years ago, it's not their fault. It's ours. We're the ones deciding to live inside a building. That was built half a century ago that we ref…”
Xu: Suburban delivery economics beat cities due to family basket sizes
“Where in the places outside of city centers, the suburbs, you tended to have a greater percentage of families, which have more mouths to feed. As a result, you tended to have higher baskets. Higher baskets meant larger revenues. You also tended to have easier …”