The subject this post names, from the same vocabulary
the directory files beliefs under, and the words it uses that this site has seen
least often elsewhere. Posts are matched on those words alone —
nothing here is a summary of this one.
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.
By four years of age, girls tend to think that boys are academically inferior to them. Teachers often see their female students as academically superior, even when aptitude tests show the opposite pattern for their classes.
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
Artificial intelligence has unleashed a torrent of cheating on campus and created chaos in the job application process, as both students and employers use large language models: the former, to write hundreds of AI-assisted applications; the latter, to screen those AI-written applications with AI-written filters, thus removing from the process of finding a first job those procedural frictions sometimes known as "people."
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?
The deeper lesson is that education has to be research-based and proven to work measurably, not just based on positive emotions or customer satisfaction.
The level of academics that those students know is very low because the parents have basically abandoned that and said, "I care all about the life skills." For parents who really care about academics, those kids crush it.
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.
what what is the current thing that models are not very good at doing? Alpha is going to decay in some way with every model release or every series of model releases. So, it's going to change over time.
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.
I guess you can’t go wrong with Charles Petzold. This book is excellent and highly recommended to anyone interested in computing. Must read for computer science students and software developers.
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.
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.
The other kind of danger is in the name of agency and and uh and motivation the tools are denied to our students because we're worried you cheat or worry you only got your answer from Chad GBT. That is very bad as well
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.
I mean I think like if you look at uh my colleagues work on say alpha fold that was a very specific model for uh protein folding and it was highly successful um and was able to really handle that domain quite well so that all of a sudden you now have this amazing tool and model that can give you answers to questions about proteins and their structure um really effectively um but it's not a general model it's a very specific one and there are other I domains where that kind of approach can work really well. Uh maybe in material science or chip design or things like that that uh will enable you to leverage the capabilities of a very accurate but but niche model uh to do things that are hard today.
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.
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.
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
I think a lot of people, especially students, are unfortunately learning everything through LLMs. So a lot of that isn't really learning, they're just kind of cheating and they're just doing everything like that. And then they lose a lot of their skills
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.
although students' personal statements seem more creative because they use more varied words, they actually feature less original ideas. AI writing produces an illusion of creativity.
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 truly believe that following this kind of approach to AI in the classroom would, in the aggregate, produce better learning outcomes than the research and writing workflows available to students pre-AI.
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.
Gamified learning is a bit like wrapping medicine in candy. Yes, it may help some students swallow some instruction they otherwise find bitter, but in practice it’s easy to pull off the candy, consume it, and throw the medicine away.
General problem solving abilities are neither learned nor taught. While some problem-solving methods have broader applicability than others (such as the scientific process of hypothesis testing), students learn these methods better when they’re explicitly taught rather than simply giving students projects and hoping they’ll reinvent them on their own.
Summary: Shipping damage. Residue on some of the components. Loud pings and pops from the assembled weight rack. A design that looked great and saved space but was painfully unusable. Restocking fee. Non-refunded shipping fees. Ghosted me about the refund.
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.
We don't ask the students to write essays because we love reading their amazing essays. We ask them to write essays because they we want them to go through a thought process, which helps them learn something.
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.
You can staff a school with the best teachers on earth, give them unlimited resources, and wrap the place in every evidence-based intervention imaginable, and it still won’t work if students are resistant, disengaged, or actively hostile to the enterprise.
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.
But if you know anything about my obsession with selection bias, you can predict the outcome: when you expand access from a population that excludes more students to one that excludes fewer, you’re very likely to see declining performance.
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
So many of us in the education world have seen this precise change in our students over the past decade: They have more difficulty reading books, sitting through a 75-minute class, or doing their homework.
The Alpha Ball solves a few different problems at the same time: (1) It's precise. Foam rollers are big amorphous objects. It can be hard to get them to certain spots (e.g., hips—TFL, glute medius, piriformis), which the Alpha Ball can easily access.
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
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.
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.
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.
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
I forget (again!) how I chanced across it, but it fills a very real need for a lot of the students in my inequality class, and I intend to make it recommended/optional reading in the future. (I'll have to see if the library can buy a digital copy.)
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.
Josh Hardman at Psychedelic Alpha provided a detailed live account of the advisory committee meeting, which I found very helpful in developing a more granular sense of how the meeting unfolded without having to watch it myself.
If you think about how we teach quantum mechanics to our students, the Copenhagen interpretation, it’s a God-awful mess. No one’s going to accuse that of being very beautiful. I’m a fan of the many-worlds interpretation of quantum mechanics, and that is very beautiful in the sense that fewer ingredients, just one equation, and it could cover everything in the world.
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.
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.
Instruction is collaborative: students want to learn, and I want them to learn, too. Evaluation is adversarial: students want the points, and I have to make sure they don’t get too many.
Evaluation forces me to flatten everything I teach into something that can be tested, and it encourages students to ignore everything that isn’t on the test.
If my class is so boring that I have to devise an additional carrot-and-stick system to get students to pay attention, the problem is my class is boring.
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.
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.
Though the book perhaps gets a little too math-ey by the end (and this is coming from someone who is literally teaching discrete mathematics to university students at the moment), Dantzig provides a compelling overview of what we mean when we talk about "numbers," and why this is a question that we must repeatedly keep re-visiting.
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.
It's an online graphing calculator that makes it very simple to whip up surprisingly complicated graphs. I found it abundantly useful for live presentations over a stream, and what's nice is that you can share the links of what you build so that students can play with them.
This might seem like a bizarrely specific question to write a whole book about, but that's actually the charm. It covers deep and general ideas, such as class field theory and elliptic functions, which are usually only taught to graduate students, but Cox approaches it all from an extremely concrete question which Fermat thought about.
Scott Galloway, The Algebra of Happiness: Notes on the Pursuit of Success, Love, and Meaning: Galloway should be familiar to readers as both the brand strategy professor at NYU Stern School of Business, a regular guest on Masters in Business, and as the author of The Four. He usually writes about technology and business, but concern with his students’ life issues led to this 10 minute YouTube video that garnered nearly 2 million views. That became this lovely short book which is likely to be a graduation and holiday gift for years to come.
A korrent is a belief a person has stated in their own words: one
sentence stating the claim, backed by a quote and a source, kept at
korrents.com.
Under a name here, the quoted block is what they actually said.
The korrent beneath it is the claim those words support, in
korrents' wording — tap it to see the record, its source, and who
else holds it.
Nobody here wrote their own korrents. They are compiled from public
statements, and a person can change their mind, which is recorded too.
About the English under a post
Some people here publish in a language other than English. Where they
do, this site shows a machine translation beneath the post, in
this typeface — the site's own, not theirs.
The post itself is never changed, moved or hidden: what is set in the
serif above is exactly what the person published, and it is what to
quote them on. A translation can be wrong in ways that matter,
especially about tone.
Only the post's own words are translated. A quoted post, a linked
article and a belief on korrents.com
are left in their original language.