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 61 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 2 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
Krieger: DeepSeek release had almost no impact on Anthropic's go-to-market
“I got this question a bunch with deep seek when deep seek came out, like, all right, what does deep seek mean for you? And I think there's things that we learned from on the tech side, just looking at what they were doing, but from a go to market and place in …”
Krieger: Nations Should Not Distill AI Models From Other Countries
“I think the places where this gets interesting are, one, do we want any nation to be able to be able to distill models from any other ones? Like, My personal answer is no. I think that there's value in like, even like as AI gains and capabilities being really …”
Krieger agrees with Alexandr Wang: Most future friends will be AI
“I've had so many conversations with Alex Wang about this because he has this whole thing about how in the future most friends will be AI friends. And you know, I don't think he's wrong.”
Krieger: AI foundation models will differentiate over time, not converge
“I think models over time get more different rather than more similar.”
Krieger: DeepSeek's cutting-edge AI capabilities should not surprise observers
“I think the DeepSync piece, people seem surprised that there were cutting-edge research teams there, and if you were paying attention, that part should not have been the surprising piece.”
Krieger: AI Startups Need Domain Knowledge and Proprietary Data for Long-Term Value
“My sense of where it ends up being most valuable to exist is places where you have some differentiated go to market, some differentiated knowledge of some particular industry or some special data that only you have access to ideally two or even three of those …”
Krieger: Selling pure API token access is a terminal failure mode
“I think the more you are just, like, maybe it's good inverting that all to see, like, what the failure mode looks like. I think it is resting on your laurels or not retaining your best people. Just believing that making the models incrementally better in every…”
Krieger: Creating multi-step task environments is the main AI blocker
“Figuring out how we better either break that down into component parts, which is probably part of the story, but also think about it holistically is the biggest blocker to at least one slice of progress, which is how do models go from being extremely good at e…”
Krieger: Top AI models will require both human and synthetic data
“So I think it absolutely has to be a mix. And I think the best models will come from that combination of great, like for code it's, you know, being, having good foundational understanding of code and good examples, but then also being able to explore a really …”
Krieger: Underestimating China's frontier AI capabilities is a mistake
“It was absolutely. Be a mistake to have underestimated or continue to underestimate like China's ability to both train at the frontier especially like if they get access to compute and then continue to innovate there too.”
Krieger: Anthropic will build general-purpose software, not bespoke vertical AI
“We are going to be building things that are general purpose as a rule with maybe some specialization at the, like, user level, but not at the, I don't anticipate us building a lot of verticalized experiences that are, like, fairly bespoke to a given workflow o…”
Krieger: Anthropic is focusing on agentic tools, not building an IDE
“So when I think about the coding space and where we can play and add value, it really is on the agentic side. It's not on the ID side.”
Krieger: AI coding models cannot run autonomously for hours without humans
“Recognize that they're not yet at the place where for many use cases, you can let them kind of run free for hours. You need that more human in the loop piece.”
Krieger: Software engineers will become AI delegators within three years
“How do we evolve from being mostly code writers to mostly Delegators to the models and code reviewers. That's what I think the work looks like three years from now. It's coming up with the right ideas, doing the right user interaction design, figuring out a de…”
Krieger: AI models are three-plus years from solving product strategy
“That, that's still a very human problem that I think we're at least three years away from the models being, being solving at that level of abstraction.”
Krieger: Anthropic became overly calcified by adopting a large company playbook
“We got too calcified, I think. And like, oh, well, this is on this team's plate versus this team's plate. And oh, you can't get this done this quarter because it's not on this team.”
Krieger: Anthropic's current product adoption outpaces true product-market fit
“The adoption that we've gotten of our products is ahead of their actual like true Product market fit because they are still the best ways of getting the models. And I don't think that's durable over time.”
Krieger: AI Companies Cannot Build Moats Without First-Party Products
“And I think that there's, you'll, you'll miss out and not have enough of a durable moat if you're not equally investing or maybe even investing even more on the first party side of things.”
Krieger: Application startups can iterate faster than major AI labs
“Building applications on top of these models becomes, it is a lot easier, and you can go from zero to one, and you can be more nimble than even these labs that are gonna all have, like, you know, tens or hundreds of millions of users, and you have to move slow…”
Krieger: Anthropic under-invested in first-party product iteration and API
“I think we've, if anything, under-invested a bit in two things. One is just Having a faster iteration speed on first-party products, and then on the second part on the API side.”
Krieger: AI product design must build for model capabilities 3 months out
“The very thing about AI and product design is you have to dance this very delicate dance of showing the future and dreaming up what the models are currently capable at their edges, you know, cause you want to design for where they'll be, gosh, three months fro…”
Krieger: AI startups can overpromise more than incumbents due to forgiving early adopters
“And now if you're a startup, you can do a little bit more of the over promising because people are kicking your tires, the early adopters, they have a little bit more of that. Sort of willingness to engage.”
Krieger: Current AI Product Design Suffers From Leaky Abstractions
“And the reality is the current state of most AI product design is an extraordinarily leaky abstraction.”
Krieger: AI products differentiate on model personality, scaffolding, and vibes
“I don't know what that fake formula is for AI products yet, but I think it's some version of that where there's like model model personality is probably one of them. There's likely something around the scaffolding prescriptiveness of the product that you're wo…”
Krieger: Distillation Is Unnecessary for Frontier Open-Source AI Progress
“I think the open source models, Like take Llama, for example, like they've been able to do that from their own research and perspective and data ingestion and training. And so I guess I would say distillation does not feel essential in order to unlock those th…”
Krieger: AI labs will increasingly obscure model chain-of-thought outputs
“More labs either choose to not show or otherwise obscure the chain of thought down the line.”
Krieger: Anthropic trained Claude 3 with a much smaller team than competitors
“The Claude three, we were training a model at the frontier that was state of the art with a team that was much, much, much smaller. Than any other lab.”
Krieger: OpenAI ships initial products faster than Anthropic
“They've moved faster at shipping V-ones, even ahead of where the model is sometimes.”
Krieger: OpenAI lags Anthropic in product personality and cohesion
“Probably personality and having the features they build be cohesive.”
Krieger: Claude and ChatGPT were initially built only as model showcases
“Claude AI and probably ChatGPT.com were, like, very much, like, initially just built to be sort of showcases of the models and not really built in a lot of ways to be the right, like, The sort of foundational for like a much more complex sort of multi product …”
Krieger: Anthropic is actively rebuilding Claude's core user experience
“We have an active effort right now around tearing down some of that and rebuilding the core UX to just feel good. It doesn't feel great right now.”
Krieger: Being late to first-party products hurt Anthropic's narrative
“I think significantly if you take a deep seek moment, right? Like ideally that the, like the story of, oh, there's more than one sort of front or leading edge API, sorry, AI product to be used is some, a narrative that we should have captured. I think it hurt …”
Krieger: AI is not yet indispensable for most workers
“I still think we are in, like, day one around, is AI an indispensable part of most people's work? And I think the answer is no.”
Krieger: AI breakthroughs benefit pre-existing builders over new entrants
“Often the companies that do benefit from those model generation shifts are not the ones that suddenly start that day. Like, gosh, you know, it sounds like cloud three, seven Sonic can do that. It's the ones that have been beating against the wall.”
Krieger: AI product development is the most complex work of his career
“It's in many ways the most complex product development work I'll ever do.”
Krieger: AI customers won't switch models overnight due to custom integrations
“Over time, you start learning that, people don't just deploy models. They're doing like fine tunes or they're deploying models. Plus they've done a lot of really bespoke work to make that model be great for that use case. It's not a thing that's going to switc…”
Krieger: Social networks succeed through format, audience, and vibes
“Social networks are made of format, or formats that you have in your product, audience, and vibes.”
Krieger: AI Labs Use Internal Distillation to Reduce Latency and Costs
“Even, like, let's take within the labs, like, I assume every single one of the labs is using, like, even within themselves, like, it is very valuable to be able to take, you know, the knowledge of your highest-end model and then be able to make it higher, you …”
Krieger: Google Gemini benefits significantly from training on YouTube video data
“It's actually clear to me that Gemini benefits from that. Like whenever they have like a good, like video understanding demo, for example, I'm like, well, I, Somebody has like probably the largest repository of video in the world and can likely train on a lot …”
Krieger: AI benchmark evals do not indicate real-world model performance
“Evals are really useful for hill climbing and for internal research, but they don't tell the story of like, is the model going to be excellent at what it needs to be excellent or deployed for, or even if it is excellent at that thing, is it only excellent at t…”
Krieger: WeChat solved technical challenges on par with Facebook's scale
“People love talking about the, like the super app and we chat, and there was some technical challenges solved by those at scale that were of the same scale of challenges that Facebook was challenged was doing.”
Krieger: Descript features some of the best product design in AI
“Descript, I think Descript is some of the best product design in AI, and, like, they've clearly put so much time into the workflow.”
Krieger: Startups have an AI alignment advantage over large incumbents
“It's why I'm really bullish on at least startups being able to explore the space because, you know, I remember this from my, both Instagram and artifact days, like when it's just a couple of you, like alignment is a coffee conversation in an afternoon rather t…”
Krieger: Internal dogfooding of Claude Code directly improved Claude 3.7 Sonnet
“As a really, you know, specific example with cloud code within, you know, a week of it being deployed internally, we had found a way in which one of the sort of tools that it has access to the model wasn't using as well as it could have, and that made its way …”
Krieger: OpenAI effectively balances consumer product with API platform
“I think that they've balanced first party product development and an API that like people, people use at scale as well. And I think that they we had an Instagram principle that was do the simple thing first. And I think they often do the simple thing first.”
Mike Krieger: AI Model Privacy Discernment Is Underappreciated and Under-Researched
“And I think models, this is very underappreciated and probably under-researched as well from like a model capabilities perspective because models fundamentally want to be helpful. And that is not always what you want them to be. And there's a safety case for t…”