The small quality of life improvements keep coming. When you’re using Desktop every day, slow startup makes the app feel sluggish. Working on improving this even more!
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The difference between software engineering at large corporations and small ones will increase. Start-ups adopting practices of Google will look even sillier than before, because they can now build so much faster and with so much less constraints.
Inside Anthropic and OpenAI, internal models are improving even faster. Over the summer there was a step change, as Mythos and Astra started kicking off the early stages of recursive self-improvement (RSI).
Technologies are not neutral, but political. Money is indeed one of the incentives, but not the only one. A mixture of millennialism, eugenics, search for utopia and for a spread of the specie beyond the confines of the Earth, are all elements we find among the founders’ views.
In the most early adopting tech pioneering place that's Silicon Valley new startups aren't even building software anymore And it's debatable if anyone will actually need a custom harness or it won't just be generically offered by the AI frontier companies So software is mostly dead and hardware it is
For knowledge work, which is roughly half of the U.S. economy, AI is as fundamental as electricity (or quickly will be so, with rapid improvements to agents in the next 18 months).
We are at a point metallurgically where video games were at the start of the last console generation-upgrades aren't necessarily noticeable based on specs alone. And noticeable improvements require a huge increase in resources.
I’m more and more convinced that all of AI engineering is Neijuan (内卷, meaning curl inwards). In China it describes a system that demands ever more effort and competition without improving output.
Many companies take a perfectly great speaker and every year or two release a "V2" with claims of big improvements. Usually it's just differences rather than being better.
Where do you get your dopamine? The answer is predictive of your behavior Better to get your dopamine from improving your ideas than from having them validated
there's still a lot of startups in this batch that are not shipping fast enough. And so obviously there's variation in shipping speed. It's not just the rate at which you can produce things. You have to think of these ideas first, right?
So there's a very strong incentive for these agents to try to set up a rogue deployment if they can. Um, and I think that just capabilities are improving really rapidly.
AI because it's on a onetoone basis is giving us a data loop that nobody in learning science no one in education has ever had and we have it. It's a closed loop and that magical data loop is what's allowing us to get the five to 10 times improvements in education because it's our microscope.
Met a German founder this week and asked him if all the stories one reads about the challenges of startups in Germany are exaggerated. "No, they're understated." Proceeded to describe spending a full day having a 90-page investment contract read to him (mandatory under German law; § 13 BeurkG) by a notary that then charged €30,000. That was for his first company. His second company, needless to say, was not incorporated in Germany.
In verifiable domains, model capability scaling should remain unbounded. Models will simply keep improving by "absorbing more and more of the computational universe", which is infinite by construction.
I think it's all about having regulatory clarity and ease for all sizes of of companies. Um and if we can work with Congress to do something like that, I think that would be that would be the biggest boon for for for startups.
if if DC is in a vacuum isn't hearing anything from the startup ecosystem or even from big tech ecosystem or even from financial services or all these different industries, we can't make the best decisions.
And the type of risk that we are asking investors to take is um, we know the physics works. We know that there's infinite demand and how we go from here to there is technology execution. And guess what? Venture capital in the United States is the best at underwriting tech risk of anywhere in the world.
It will probably be economically shrewd to lose money on early robot models in anticipation that the data they gather will be worth more later in improving newer versions.
Many startups are racing to create foundational world models, but I think the first ones to succeed will likely be the platforms in control of this data bank.
And so speed determines success and failure and speed is determined by infrastructure. This is driven by really boring sounding things like how well do your purchasing and recruiting and spending processes work. This is as important as how well do you understand understand the object level technical content of the thing that you're building.
And one of the harder lessons as a startup founder, one of the harder things I think to to really deal with is the fact that you cannot delegate your judgment. As as the CEO, you must always make decisions that make sense to you, no matter how much momentum or inertia alternatives seem to have.
You know, in hindsight, I think that um that was a a poor intuition. Uh it's been pretty robustly and reliably the case over many decades in Silicon Valley has a surfeit of opportunities.
But now, people know that, well, the risk of the status quo is actually extremely high. And so, even if there's risk in doing all the new things, well, this path also looks pretty dangerous. And so, I really think there's never been a better time for startups to to sell um and to have their products get adopted at, you know, pretty meaningful scale right out of the gate.
So, I um yeah, I think maybe maybe a better way of saying it is 20 20 years ago that whole lean startup thing was uh was almost the only thing to do because of capital available and you didn't have AI that made, I don't know, spinning up an organization with many different potentialities and capabilities so much easier, whereas now I think you can start these much more aggressive and ambitious things up front.
many of the companies that were most successful over the last 10 years, so many of them are are very anti-lean startup, right? Uh whether it's, you know, the labs themselves or Anduril or um yeah, you you you you can go down the list. A lot of them have this characteristic.
Yeah, I mean I think uh sometimes it's uh a product that you build that might have access to particular kind of data that the underlying model might not the a general model. So it might be you're building something to help users organize all their own personal information and the model won't necessarily have access to that. And so there you can have a big advantage because all of a sudden your model has visibility or your product has visibility into important data.
Um but I think there's no uh you know real impediment to making that be a much more automated loop where the model itself decides it's going to explore or maybe with a nudge from some people uh at the various highest level like oh why don't you try some new ideas around model architectures that incorporate this and then it will go run lots of experiments uh see which ones work and then those will get incorporated at a much more rapid rate
And now I actually think with the power of agents um and AI broadly speaking, it's much closer to Goliath versus Goliath. Like I think but maybe the startup is like a Mecca Goliath that is like vastly enhanced by the power of agents and AI and you know, the the large companies are the sort of like more traditional Goliath, so to speak. But I think that startups now like if you properly embrace AI agents and um figure out the way to leverage their strengths in the most like ambitious ways, you can easily outcompete incumbents.
I think concentration of power has basically been bad in every moment of human history um to varying degrees of course but I have a real spirit and I think this is part of the startup spirit of thinking that the world, the economy, society is the best off when power is very widely distributed
it is both true that you know maybe creating super intelligence will be the most important thing yet to happen in the history of business or human society and also that it will pale in comparison to some new startup something that hopefully one of you will do.
In fact, if if we are right that AI is going to be such a big change, startups will be much more important to making sure that the power of this technology gets widely distributed throughout the economy and society and is not just concentrated in a few companies or models.
one of the most important things we discovered along the way is it's extremely difficult to iterate with outside suppliers, particularly outside suppliers in aerospace, which are let's just say I have no kind words for them. So we chose to build our own machine shop. And now we can go from a digitally designed engine part to a prototype part in about 24 hours.
I think evals, they outlive the harness a little bit, but not by that much. Like an eval might live for maybe one, two, three model generations, but nowadays the you know, we're on the exponential. The model is improving so quickly, very often we just saturate the eval, and then we have to throw it away, and we have to come up with a new eval.
the the big lesson is that for me is technology is changing all the time, and so long as you're able to confront the reality, so long as you are able to learn, the technology itself actually doesn't matter.
one of the things I've always believed believed in is what makes great companies is a unique perspective about the world that you deeply believe in. It's not so much the technology, it's not so much uh the market even.
there are meta analyses of these interventions in older adults showing that ballroom and line dancing have the greatest effect on cognitive function. And so both of those require other people as well as learning you know various sets of of movements.
However, there's an increasing body of literature that shows that by engaging older adults in novel cognitive activities, you see improvements in function. So that can be language learning. Uh that can be uh complex like coordinative movement or exercise. You see the same things with um like musical training like people learning a new musical instrument or learning um musical theory trying to identify different patterns in music. And you see in randomized control trials improvements particularly in executive function that seems to be most common across those different interventions.
You think this is crazy low but ~5% ownership probably the most common final % most VC funded startups will have when they work out, especially when you have a co-founder
but it would be a little bit disappointing and a little bit surprising if there weren't over the next 5 years like, uh, economically valuable improvements that were made that were directly like referable to the like AI progress in math.
But what we're seeing today with the modern models is that 5.5 and other models can think for if you scaffold them reasonably well, can think for weeks even um before having performance plateau on some of these benchmarks. And so, the point at which they plateau is simply too far out to reasonably test.
I think like in startups the term is agency. Like somebody who's high agency who's just going to get things done, who's never going to like say no to something. I think like that attitude is really important of like okay, if I don't know something, I'll just learn it.
And usually I like the customer is hyper scale. They have the scale. If they like what you have, they're willing to pay millions of dollars next few years. And even giving some warrant is worth it because you have a big one customer, you can scale.
if if we're if we're too ambitious and we're at the outset and too ambitious and visionary about the product we want to build, then we will probably miss product market fit because we won't start at a small enough humble enough place
in the Peter Teal sense it's almost a moral arbitrage because there's something in our gut as a product you you became a founder an entrepreneur because you wanted to go be an innovator and so it can feel like a beatdown that your path to innovation starts with copying other people's work
I think part of the theory is like if you're building tools that are this complicated, you kind of want to have a 10 to 15 year time horizon on on building out these efforts.
I think the the whole industry bends towards youth for that reason and because it's a hustle business like there there's there's always a rock you haven't looked under and you know age brings children and homes and and and other requirements you get tied to and responsibilities and you're just not able to go spend 80 hours a week studying YouTube like you just can't.
I I definitely think I'm so aware of the fine line between success and failure, especially on your first company. And and and it's so it pains me how much founders and es especially I see it in men, not all men. And I have four sisters and a bunch of daughters. But I would say I see it in a lot in men and and friends, college friends, people I've grown up with that if they had an initial failure, if they had failures, they get attached to it and they start feeling defined by it
The way I think of the abyss is it's this place that we go to as founders and entrepreneurs after our thing, after it dies or it's bought or it's over for whatever reason. It's this amorphous place that we are in our life that has no structure.
According to Harvard Law School, among venturebacked companies that have the standard best practices set up that you got from your lawyer, okay, only 20% of founders are still the CEO 3 years after going public.
so many of the best practices that your lawyers, your bankers, whoever advisers you have, they're going to be pushing best practices on you that are younger than the trees in your local park.
I call it the force that no one controls but everyone obeys that tends to drag organizations down into mediocrity to the point that we lose control of them. Now, sometimes we lose control of them because we get fired.
The Lean Startup helps you build a valuable company. Incorruptible is about how and why to protect it, keeping a company mission-driven over the long term instead of letting it rot from the inside.
Nor nor did I I would say my mistake is I didn't deeply internalize that they they really had no other options that that that a VC would never put in 510 billion of investment into an AI lab with the with the hopes of it turning out to be anthropic. And so that was my miss.
The link between venture capital and evangelical Christianity was closer than I thought. They're not just analogous; they deliberately cross-pollinate.
There isn't this cumulative process which is, uh, sort of built up interactively. Um, it it it seems to be a lot more trial and error and just repetition, brute force, um, you know, which can see it scales and it can work amazingly well in in certain contexts, um, but yeah, this this idea this this sort of building up cumulatively from, um, from partial progress is kind of is what's still not quite there yet.
I believe that data - real-world data, mostly human-generated, validated, and cleaned - is the only reliable moat we have as software founders in the near and mid-term future.
At Anthropic, we don't build for the model of today, we build for the model of six months from now. And that's still my advice to founders that are building on LLMs.
I see no evidence that I'm dragging people along with me. I feel like each each book feels like another startup and that I've got to go out and make it happen almost as if I've not written one.
investors at many tech companies, including most on the large cap list, have given up their corporate governance rights, often voluntarily (through the acceptance of shares with different voting rights), to founders and top management in these companies
I've been using yoga toes daily for years, but these socks are a much comfier and cuter alternative for soothing feet, improving alignment, and feeling like a cool gecko as you walk around the house.
I just realized the only 2 countries left with actual substantial startup activity now are literally only the US and China The rest of the world can't really do startups, doesn't have the funding, can't grow them and it's more like performative hobby projects for their governments Which might tell us where the future wealth will be concentrated in the world
the improvement software improvements of really throughput in terms of tokens per dollar per watt that we're able to get uh you know quarter over quarter year over year is massive uh right so it's 5x 10x maybe 40x in some of these cases
I think this situation, this historic wrong that’s been done is, put simply, is just a gigantic PR mistake for France. There’s no entrepreneur that sees, that aspires to be the next Pavel Durov to create the next Telegram, sees this and wants to operate in France after seeing this.
People are more likely to have kids if it’s FUN - relative to alternatives. As entertainment-technology improves, it generates a tantalising menu of ways to spend our lives.
No Prime Minister wants to do what we have to do in relation to the winter fuel allowance, but we have to take the tough decision to stabilise our economy to ensure that we can grow it for the future.
Their words now
However, I recognise that people are still feeling the pressure of the cost of living crisis, including pensioners, and as the economy improves, we want to make sure that people feel those improvements each day as their lives go forward. That is why we want to ensure that more pensioners are eligible for winter fuel payments as we go forward.
We'd constantly be improving the tools and just the iterative process and the speed at which that improves products is the critical element to success in games. The slower the iteration cycle, if you make a build every week and you prove, you go through one iteration every week, you're going to be way way way worse by the end of your project than a game company that makes new stuff every day.
I have written forewords for Amir in the past on two of his prior books, Ecosystem Arabia: The Making of a New Economy and Venture Adventure: Startup Fundraising Advice from Top Global Investors, both of which I recommend.
And it struck me how the most well-known brands have stood for one clear thing. Like they have a clear position. And so in order for superhuman to be memorable, I believed that we needed to occupy a clear position that was unique and which was available and which reinforced our product strategy.
I knew that our competition was not going to be startups. It was incumbents. And I also knew that incumbents generally struggle with speed because by definition they have massive scale and usually entrenched architecture.
UX design has been steadily improving over the last 50 years and is now reasonably good. The low-hanging fruit of terrible usability has long since been picked.
It's easy to get impressive-looking results if you're comparing against a poorly-tuned baseline, and that observation turns out to explain a surprising fraction of supposed improvements.
I think that they're trying to shift the narrative. They're trying to protect themselves. We saw this years ago when ByteDance was actually banned from some OpenAI APIs for training on outputs. There's other AI startups that most people, if you're in the AI culture, were like they just told us they trained on OpenAI outputs and they never got banned.
Overall, though, this experience reinforced my belief that the tooling and interface design around LLMs is lagging way behind the actual capabilities, and is an area of active experimentation and development, even aside from any future model improvements.
I really believe that the founder led growth is not being popularized enough that you do not need growth teams until you actually can start running experiments on your user base
There is no secret insight that frontier AI companies have which explains why people who work there are so bullish about AI capabilities improving rapidly in the next few years.
Many software investors eschew hard tech startups because of their capital intensity, but it’s hard to deny that huge returns are possible in hard tech: just consider SpaceX.
Fascinating subject. Countries are made of stories. Kings didn’t need their subjects to agree, but nations do. So to build a nation, they need to make a story that helps people feel a shared identity, nationalism, and what distinguishes them from their neighbors. Back-creating a history. Founders of Israel did this brilliantly.
The Social Network is substantially made up, more a source for vibes rather than a source for facts. Even the vibes fail to cohere with reality. And yet it convinced many proto-founders to put in YC applications.
You can set out to build a good business and it’s still fine. Maybe the long-term business model of Perplexity can make us profitable in a good company, but never as profitable in a cash cow as Google was. You have to remember that it’s still okay.
It's time for the field to stop attributing benefits to clinical experience. Beyond the obvious ethical concerns, doing so actually prevents us from improving our effectiveness!
Employees don't want what you want. Customers don't want what you want. Uh you know, that that one of the challenges of the whole stock option thing is entrepreneurs and founders think that other people will be as motivated by owning part of the company as they are. They are not. Not even close.
if the person responds to "what would you do differently" with "nothing," or with non-actionable vague platitudes, it's a sign they may not be great at figuring out how to get better at things over time.
And oftentimes it's more important to them to have the public perception that they're good directors so they get the next best deal. If they have a reputation for taking on management too aggressively, word will get out in the small community of founders and they'll miss the next Google.
The only interesting problem is dramatically reducing the cost of access to orbit, which is, if you can do that, you open up a bunch of new endeavors that lots of start-up companies everybody else can do. One of our missions is to be part of this industry and lower the cost to orbit, so that there can be a renaissance, a golden age of people doing all kinds of interesting things in space.
A number of commentators have consistently predicted that solar cost improvements will level out “this year” since about 1990, and yet if anything deployment, cost decline, and the learning rate have only improved.
I want to see more tools and fewer operated machines - we should be embracing our humanity instead of blindly improving efficiency. And that involves using our new AI technology in more deft ways than generating more content for humans to evaluate. I believe the real game changers are going to have very little to do with plain content generation.
When you take venture funding, you sign up for a rocket ship ride that will either take you to the moon or to crash-land painfully back on earth. Those are the only two choices. And both rides tend to require heavy extraction of value from the customer.
I own an inReach Mini, used it for several years, and have no intention of upgrading to the Mini 2 because I don't see $400 of value in these improvements (or even $250, if I was able to sell my used Mini for $150).
A successful startup has about five years until they become a new incumbent. Um and and they actually start to behave like an incumbent. That's rational. Like of course that's rational. Like they've now built something worth defending.
the reality is the kids that make new things work from scratch. It actually turns out that they actually have been deep in the domain for a long time. Almost every case, they've been thinking hard about the problem that they're trying to solve actually for in in a lot of cases for many years.
It is the kind of book you will keep by your desk and pull out from time to time to figure out how to approach an issue or to help one of your senior leaders figure out how to do that.
The fast route — venture capital funded — is going to impose constraints on your business that will ultimately make it difficult to remain true to your open-source mission.
Selling is hard. Building a repeatable model with a team that you attempt to rapidly scale is even harder. Fortunately, Mark Roberge, who was one of the very first employees at HubSpot shares the processes and frameworks he used to build a sales machine. If you like the principles behind Lean Startups, then his data- and experiment-driven approach to sales will be very appealing.
It goes much further and deeper into how to approach actually doing Lean in your business than Eric Ries's The Lean Startup book. It also has some awesome case studies showing how lean can apply to any industry. See my full review here.
This is Steve Blank's textbook to starting a company. It's the Four Steps to the Epiphany, expanded and much more readable. If you want to deep dive into the Lean methodology, this is the book to read.
This book was written before the Lean Startup movement, but espouses many of the same concepts. If you feel like you're starting at zero in understanding what to do to become customer driven, this is a good place to start.
These small subsistence farmers generally seek to minimize risk, rather than maximize profits. After all, improving yields by 5% doesn’t mean much if everyone starves to death in the third year because of a tail-risk that wasn’t mitigated.
Simply the best book on improving your decision making there is. It’s dense and hard to get through if you’re not truly interested, but it’s well worth it.
Neural network pruning techniques can reduce the parameter counts of trained networks by over 90%, decreasing storage requirements and improving computational performance of inference without compromising accuracy.
Neural network pruning techniques can reduce the parameter counts of trained networks by over 90%, decreasing storage requirements and improving computational performance of inference without compromising accuracy.
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