Mobile did not go to startups. It remained with the incumbents from pre-mobile (Google, Meta, Apple). It appears only the Internet was a truly game changing event if you are thinking of brand new gigantic companies go from startup phase to trillion dollars.
Mobile _phones_ did not go to startups. Making money off mobile -- whether apps that were impossible before, or features which advantaged certain companies who were able to be mobile-early or mobile-first, advantaged startups.
A bit. There was enough space that the incumbents failed to notice a niche here or there. And in particular, Google left a relatively big portion of the ad market open for grabs.
But the incumbents succeeded in capturing most of the money involved with mobile. And only became more powerful after it.
Only Apple had the phone, Google's phone is mostly for pushing innovation (not sales) and Meta doesn't have a phone or OS. In the final analysis, most of the value went to these guys not the hundreds/thousands of startups that got started on mobile. Whatever these startups did, these guys copied or bought and drove most of the value post-acquisition (ex. Insta/Meta). Uber is probably the biggest and it only just crossed $150B recently.
Three different people are telling you that the majority of value accrued to the ones listed. Insta and Lyft are both under $10B while the other three got into trillions of dollars post mobile.
Delving into new strategies wouldn't make sense given the thesis of the article—what your strategy is must depend entirely on the specific market you're targeting. There is no generally applicable advice because each market is completely different.
In past disruptions the startups could all have similar playbooks because one strategy was applicable everywhere: "do X, but on {web,mobile}". Now there's no common strategy that applies to all markets because the incumbents are already integrating AI more rapidly than you'll be able to bootstrap a whole product. This means that each startup needs a strategy that is tailored to the specific incumbent they're trying to unseat.
You need to look at second order effects and how AI might intersect with other emerging technologies. There will be fundamental shifts that change market dynamics, we just don’t know how they will happen yet. Incumbents have a strong belief in AI being transformational but since no one truly knows how those changes will be realized, so they are mostly all hedging their bets, investing in institutional knowledge and low-hanging fruit. They cannot generally afford to make a “big bet”. If you can develop a strong hypothesis about a non-obvious shift you can get ahead of the curve in a significant way on an emerging, or transforming market. Look for things that are valuable and/or expensive that might become a commodity. Look for technologies, business models and approaches that might be considered inferior or non-viable by incumbents, but that might experience synergies with an ai-powered future that changes the base assumptions.
I would argue that they do in some ways. For example, with AI it's not about adopting vs. not adopting AI, but rather degree of adoption.
It's easy to superficially integrate AI, but creating a competitive product predicated on post-AI assumptions requires rebuilding it from the ground up, which is not in the rational self-interest of incumbents.
In fact, this is even harder than the decision whether or not to adopt new technologies because with AI you can fool yourself into thinking you've gone far enough.
AI is such a game-changer that we have no idea what 'far enough' means yet. So the best we can do is run in that direction as fast as possible, which is hard to do with the baggage of an existing business. Startups are uniquely suited to this because they arebets on a different future.
That said, it is a fantastic article -- Jason always puts out insightful, high quality writing.
And I agree with your push-back on that. Indeed, perhaps when a startup is able to say "ahh, but HERE Disruption CAN work because...", that's where a good strategy can emerge.
An interesting article, with many good points (I particularly like the reminder that unless you're competing with OpenAI, AI is in the solution space) but despite the repetition that this time is different to the Internet, I do feel that if you replaced "AI" with "Internet" you'd get something that could have been written in 1996.
The core difference is that the internet was about distribution while AI is about intelligence, which includes the ability to create things.
The internet is probably the closest the comparison, which is why I get your point, but far off in terms of the scale of the implications.
The hardest thing about AI is that we don't have intuitions for it. It will make the exponential growth that the internet brought look linear by comparison.
I think the closest comparison to AI is the assembly line. None of the current AI offerings make sense without scale. AI also helps enhance some work, but it's not the product itself that the end user wants.
I'd say AI is more like a 3D printer than an assembly line, and not just because both sound futuristic.
Assembly lines make one thing efficiently, by breaking down the complete task into small units such that no single person needs much training. This is basically what UNIX has been doing since at least the command line pipe operator was invented.
3D printers are general purpose and can kinda make anything in principle, but in practice the cheap ones are very limited while the one for building a rocket engine is priced at "hire a team of full-time engineers to build and maintain it", and in any case these are not a good choice for reliable mass production. This seems like a better, though still flawed, pattern match to AI.
These are some good points, but it doesn't seem to mention a big way in which startups disrupt incumbents, which is that they frame the problem a different way, and they don't need to protect existing revenue streams.
So, the Shirky principle: incumbent companies are dedicated to keeping around the problems that they solve. Startups get to define the problem differently, and can solve a problem that an incumbent is dependent on.
Or put another way, this wave may not be technology-based disruption but business-model based disruption. For example, if LLMs enable subscription or service-based models that deliver more value than ad-based/aggregator based ones, a nimble enough disruptor may surface. Probably too early to tell.
>> AI is in the solution-space, not the problem-space,
this feels like an oversimplification. Its like saying the internet was in the solution space, companies were still selling things and now they needed to use the internet as well.
I think there's a ton of new scenarios that open up some are already underway like self driving cars and others further down like home robots that function like butlers.
Also companies that leverage AI in the best possible way for a domain will differentiate and that does open up the possibility of disrupting incumbents. It may get to be that to set up a business you pay for Data and the Model until you have critical mass to generate your own data.
I agree with the arguments except for the core innovators dilemma’s incumbent. Here the incumbent is Google and the startup is OpenAI. Google did not want to cannibalise its market share and OpenAI swooped in to fill the gap.
> ...all new startups probably do need to include AI
A more logical conclusion would be that significant market disruption is more likely to occur outside of the world of AI.
I know its heresy to suggest that AI isn't the be-all and end-all of technical innovation but imagine for a moment that the incumbent's bet on AI actually ends up harming the long-term value proposition of their products. What if people get increasingly annoyed with impersonal and inauthentic interactions/content. What if the mass-adoption of generative AI pollutes consumer trust.
It stands to reason that there's a huge potential in startups not focusing on AI. There's an increasing segment of users who would happily opt for "low-tech" options that solve a problem well. If the rules for disruption don't hold with AI tech, then the high-ground startups should be searching for is perhaps on a different hill.
A perfect storm is possible since incumbents have gone all in on the same technology and strategy. When everyone's following the same playbook, strategic disruption could upend multiple incumbents at the same time. I think that's a much more exciting prospect than trying to go toe-to-toe with giants.
I think the real question here is identifying a problem are you trying to solve for the world and figuring out if it’s actually a real problem that needs solving, past that it’s finding the right foundation and tools, whether it’s building on top of open ai or some other llm - that’s fine. if it requires a more tailored ai, then one could delve more into the research in R&D. why compete with another solution that already exists? just build on top or find another problem to solve?
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[ 2.8 ms ] story [ 68.6 ms ] threadBut the incumbents succeeded in capturing most of the money involved with mobile. And only became more powerful after it.
I think the social media startups like instagram are a good example of the startups from the mobile era.
It’s unfortunate that he doesn’t actually delve into new strategies.
Anyone know of any actually good articles on plausible AI startup strategies?
In past disruptions the startups could all have similar playbooks because one strategy was applicable everywhere: "do X, but on {web,mobile}". Now there's no common strategy that applies to all markets because the incumbents are already integrating AI more rapidly than you'll be able to bootstrap a whole product. This means that each startup needs a strategy that is tailored to the specific incumbent they're trying to unseat.
I would argue that they do in some ways. For example, with AI it's not about adopting vs. not adopting AI, but rather degree of adoption.
It's easy to superficially integrate AI, but creating a competitive product predicated on post-AI assumptions requires rebuilding it from the ground up, which is not in the rational self-interest of incumbents.
In fact, this is even harder than the decision whether or not to adopt new technologies because with AI you can fool yourself into thinking you've gone far enough.
AI is such a game-changer that we have no idea what 'far enough' means yet. So the best we can do is run in that direction as fast as possible, which is hard to do with the baggage of an existing business. Startups are uniquely suited to this because they arebets on a different future.
That said, it is a fantastic article -- Jason always puts out insightful, high quality writing.
And I agree with your push-back on that. Indeed, perhaps when a startup is able to say "ahh, but HERE Disruption CAN work because...", that's where a good strategy can emerge.
The internet is probably the closest the comparison, which is why I get your point, but far off in terms of the scale of the implications.
The hardest thing about AI is that we don't have intuitions for it. It will make the exponential growth that the internet brought look linear by comparison.
Assembly lines make one thing efficiently, by breaking down the complete task into small units such that no single person needs much training. This is basically what UNIX has been doing since at least the command line pipe operator was invented.
3D printers are general purpose and can kinda make anything in principle, but in practice the cheap ones are very limited while the one for building a rocket engine is priced at "hire a team of full-time engineers to build and maintain it", and in any case these are not a good choice for reliable mass production. This seems like a better, though still flawed, pattern match to AI.
So, the Shirky principle: incumbent companies are dedicated to keeping around the problems that they solve. Startups get to define the problem differently, and can solve a problem that an incumbent is dependent on.
this feels like an oversimplification. Its like saying the internet was in the solution space, companies were still selling things and now they needed to use the internet as well.
I think there's a ton of new scenarios that open up some are already underway like self driving cars and others further down like home robots that function like butlers.
Also companies that leverage AI in the best possible way for a domain will differentiate and that does open up the possibility of disrupting incumbents. It may get to be that to set up a business you pay for Data and the Model until you have critical mass to generate your own data.
I'm sure it was just on Google images or something, just funny how instantly recognizable that shape is, I don't think I've seen it for years.
A more logical conclusion would be that significant market disruption is more likely to occur outside of the world of AI.
I know its heresy to suggest that AI isn't the be-all and end-all of technical innovation but imagine for a moment that the incumbent's bet on AI actually ends up harming the long-term value proposition of their products. What if people get increasingly annoyed with impersonal and inauthentic interactions/content. What if the mass-adoption of generative AI pollutes consumer trust.
It stands to reason that there's a huge potential in startups not focusing on AI. There's an increasing segment of users who would happily opt for "low-tech" options that solve a problem well. If the rules for disruption don't hold with AI tech, then the high-ground startups should be searching for is perhaps on a different hill.
A perfect storm is possible since incumbents have gone all in on the same technology and strategy. When everyone's following the same playbook, strategic disruption could upend multiple incumbents at the same time. I think that's a much more exciting prospect than trying to go toe-to-toe with giants.