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The dawn of a new startup era (giansegato.com)
17 points by giansegato 13 days ago | hide | past | favorite | 7 comments





Pretty long piece, but seems like the overall point is:

> I expect the true market crushers of the next two decades to be companies that are willing to venture into doing something that few would bet their professional lives on: applying the data flywheel to the world of atoms. That can range from defense tech, to biotech, from space tech, to robotics, from consumer hardware, to anything in between.

and also

> There are not many success cases I can mention to support my argument: these companies are being built right now. It will take many years to see them flourish and thrive. I don’t think it’s a coincidence, for instance, that some pure software companies like Midjourney seem to be getting ready to make a consumer hardware play.[16] Conceptually, the archetypical company that I think will win the biggest will look like Waymo. Hardware-first, ultra-high capex, more than a decade of R&D and deep technical work before seeing the light at the end of the tunnel, but an incredibly defensible position that will be very hard to attack. And the moat is not simply technical. It’s a data advantage too, as they are not a car company, they’re an AI company that is constantly harvesting data and improving their models. Physical companies applying AI to their verticals will be a marvel to witness, and at the risk of being proven completely wrong, I don’t think they run the risk of being disrupted in a hypothetical post-AGI world.

I guess it's cohesive: we're about to enter a compute/programming-as-commodity world. So your next moat is something physical that can't be replicated/made irrelevant overnight.

I personally think this is a little overblown, do we really think the era of SaaS is over? Maybe those companies are not getting the price premiums they used to, and I think thats partially the market itself maturing. But the article says:

> The more obviously good an idea is, the more competition there will be, the more an entrepreneur's likelihood of succeeding will eventually regress to the mean — in this case, average market returns.

This has always been true, and perhaps you could argue that until the early 2000s there wasn't much competition in some given arenas online, but that surely isn't true anymore. I can't think of a single emerging major startup that I can't also think of a few major competitors for, often huge companies.


> I expect the true market crushers of the next two decades to be companies that are willing to venture into doing something that few would bet their professional lives on: applying the data flywheel to the world of atoms. That can range from defense tech, to biotech, from space tech, to robotics, from consumer hardware, to anything in between.

The real world is cruel in a way that the virtual world of software isn't. A lot of people have tried to solve physical problems with "more data" but reality requires orders of magnitude more data than we are able to process today. That's why we don't have robots with fine motor skills. We would need a revolution in computing to be able to tackle that problem. And sometimes, like in the case of Theranos, there just isn't sufficient information in the input the size of a drop of blood to get the kind of outputs we wished we could.

For now, we're relegated to automating processes between physical things, because that is something that can be mapped to our current computing abilities. You can automate a warehouse to some degree, you can automate assembly lines, but you can't automate the final organic touches.

Not to mention all the materials science breakthroughs that we also need for a variety of so-called revolutionary applications we can imagine today.


They make the point that there will be SaaS but it's likely to be more mom & pop SaaS and not significantly large players because the cost of producing software has been lowered significantly. The SaaS to emerge will live in their own specific niches.

I don't trust people who don't know the difference between a flywheel and a positive feedback loop.

Help me out here because I'm having trouble understanding this blog post.

>By definition, if everybody agrees that something is worth investing in, the return on that investment will correspond to the market average. Formally, “market” is simply “consensus on correct pricing”. It’s the average, the norm, the wisdom of the crowd. Generational companies are outliers, happening several deviations away from that norm. If we accept this definition to be true, it must follow that consensus and successful startups are antithetical.

Um, but then who is investing that makes a company "Generational company"? If you're hugely successful and your market value huge ... someone will be investing and there will be demand for more investment, so it's not like you're entirely disconnected from the market...

Or are we talking about everything BEFORE the market invests a lot of money?

The later section on AI and wrappers and competition made more sense to me (not to say I agree, I think I got it), but the whole idea that you should be heavily concerned with potential competition in the context of a start up is interesting to me as I think most start ups fail ... because nobody wants their product, not because of direct competition.

Generally the post felt like a blob of "start up speak" to me, and I couldn't really pick out what the big insight here was overall other than maybe something like 'bet big / weird'. But maybe that's just me.


Yeah, I think this piece gets the narrative exactly backwards. Its main point is that- the bet matters, that is what is so unusual about those exemplars- and that is completely wrong.

Execution matters/mattered in those example cases, not the bet/founding hypothesis, of which in all cases there were dime a dozen. If the bet matters, why didn't those identical bets win?

Anyway.


The "willing to bet asymmetrically big on their defiance" framing is bs and completely the wrong takeaway/narrative. I stopped reading at that point.



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