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Ask HN: Do startups building on OpenAI have a defensible moat?

jtwaleson 2y ago
As you were submitting this question I was finishing this on-topic blog post. https://blog.waleson.com/2024/05/the-long-long-tail-of-ai-applications.html https://blog.waleson.com/2024/05/the-long-long-tail-of-ai-ap... Short answer: Yes I think so.
- sabrina_ramonov 2y ago
  to summarize: prompt engineering is hard, niche use cases often involve private data and specialized knowledge, and LLM ops is a heavy lift. Did i miss anything?
  - jtwaleson 2y ago
    Prompt engineering is hard, and not a one size fits all solution.
  - anonzzzies 2y ago
    Prompt engineering is not engineering and it’s not hard, LLM ops is not ops if you are using OpenAI (which the question states you are using). If your solution has code for rag & prompts + a saas boiler plate, you have no moat. Whatever you have is already or will be eaten by openai itself (Altman keeps saying that as well). (Still assuming you are using OpenAI) if your solution implementation has 2% prompts and AI specific stuff and 98% other functionality while AI is still central to your solution then you have possibly a moat. Seems existing systems adding AI are long term AI money makers.
    - ano88888 2y ago
      why does any software company have a moeat then, since everyone else can copy it with your logic.
      - anonzzzies 2y ago
        The technical moat for software companies is the effort to implement the logic; for instance, many companies have moats because they implement functionality that is hard to reproduce without having access to documentation needed to implement that functionality. It is also possible that there is so much functionality implemented over the years that copying it, while 'just work' is just too much work for most companies to really compete; SAP is an example. Then there is the example of OpenAI etc; too costly to reproduce simply by not having enough compute. Besides technical moats, you have client base moats; for instance, a trivial to implement application, like say, Resend (where you can find tons of open and paid alternatives for) did their marketing well (until they got hacked a few times that is) which gave them a moat and they still have some of it. Here is where large incubators give you some advantage; they use circlejerk to give you a lot of clients (their other companies and their clients) from the start. Then there is a regulatory moat which is common in banking, healthcare etc; you need certificates in distinct regions etc. That makes it harder to compete without having a lot of money. IP moats; maybe there are patents which competitors would need to work around. I'm against software patents however, they do exist and can hinder competitors to compete directly. These are all moats which hinder competitors coming up. If a large company wants to compete with your software solution, they can copy it and go after your market. Usually they will look at your moat and just buy you out giving them the moat. But yes, it is why VCs want you to grow as fast as possible at any cost; to 'take the market' so you have a moat in one or more of the above so in the end it's too much work to catch up and you'll be bought (exit). Solely on technical merit, it is expected that AI will remove this moat completely over time, but we are not there yet. We don't know what software will look like at that time anyway; probably not really recognisable vs now.
    - sabrina_ramonov 2y ago
      "LLM ops is not ops if you are using OpenAI" Even if you've plugged in OpenAI, there's a lot of ops work that goes into monitoring and managing output quality, reliability, and continuous improvements at scale.
blueboo 2y ago
They’re a PM’s whim away from being steamrolled by their foundation model vendor. And these startups are doing the product market fit for them The bigger the opportunity, the more general the audience, the juicier the B2B market, the greater the risk. Time was when Jasper was valued more highly than OpenAI. Now it’s flagging and OpenAI is headed for 12 digits…
yumraj 2y ago
Depends on whether the startup is building a feature or a product. A lot of AI startups that are building on top of OpenAI are effectively building a feature, a small very specific solution for a small use-case. Most of those are going to fail when OpenAI or some other entity with a product will add that feature to their product. But, if you solve a real large pain point that has value and use LLMs via OpenAI to add 1 or more features to your offering which allows it to solve that pain point more effectively and differentiate from competitors, then you have a moat.
- sabrina_ramonov 2y ago
  Not sure I understand the differentiation you're making between feature vs product. Perhaps startups start out as a "feature" but then build a full product around it. This path seems common and reasonable, given the very limited resources of a typical startup.
ano88888 2y ago
does people build using javascrapt or python or java programming language have a defensible moat since everyone can use that launage and immiate your ui/ux ideas.
- anonzzzies 2y ago
  Your technical moat is the complexity, quality and breadth of your solution; everything can be copied but the question is the effort. It is often just simpler to just buy you out vs building; especially if it's not only complex, good quality and has a client base. See also my other reply to you; https://news.ycombinator.com/item?id=40283601 https://news.ycombinator.com/item?id=40283601 The OP question was about LLM based companies using OpenAI api's. Most (almost all) of these are thin wrappers with some prompting; most of the ones introduced here on HN or Reddit, I can outperform in minutes. I try them all to see if someone is doing something interesting, but 99% are not, they just took some SaaS starter and added AI in there and threw it on social media. Even the ones that went somewhat further are still just doing straight forward things that can be replaced trivially inside the OpenAI playground. That's no moat at all. It looks flashy but...
muzani 2y ago
OpenAI and Anthropic builds extremely fast, even more so than most startups. There's little point building things like langchain, because OpenAI will build a better product a few months later. But you can build a product connected to OpenAI fine. Anthropic uses a similar API. Most of the smaller LLMs will also copy the same design so switching is cheap. It's probably not a smart idea to be completely dependent on OpenAI either. They're down all the time, can ban you on a whim, and their customer service is inaccessible.
deleted 2y ago
[deleted]
w3bperson 2y ago
Maybe not in the traditional sense of a moat, but maybe that's OK. It's difficult to create a deep moat with the commoditisation of technology and higher barriers to entry. Soon enough every company will be an AI company. So to create a moat it could be a case of creating a company that wasn't possible before AI that has the characteristics to create a moat - imagine something like a personal cooking assistant that links up with your health apps and buys your groceries for you, optimised for your health - add a yearly subscription for next-day delivery and you have your moat.
_akhe 2y ago
The moat could have nothing to do with the AI part. Examples: - e-commerce app is a thin ChatGPT wrapper for the shopping experience but their moat is their products and supply chain details - video game using LLM NPCs and other dynamic experiences but their moat is something else like incredible graphics or being based on some known IP - any business based on curation or archival of past LLM responses or interactions, moat could be some quality of that particular data, like other data businesses

As you were submitting this question I was finishing this on-topic blog post. https://blog.waleson.com/2024/05/the-long-long-tail-of-ai-applications.html https://blog.waleson.com/2024/05/the-long-long-tail-of-ai-ap... Short answer: Yes I think so.

sabrina_ramonov 2y ago
to summarize: prompt engineering is hard, niche use cases often involve private data and specialized knowledge, and LLM ops is a heavy lift. Did i miss anything?
- jtwaleson 2y ago
  Prompt engineering is hard, and not a one size fits all solution.
- anonzzzies 2y ago
  Prompt engineering is not engineering and it’s not hard, LLM ops is not ops if you are using OpenAI (which the question states you are using). If your solution has code for rag & prompts + a saas boiler plate, you have no moat. Whatever you have is already or will be eaten by openai itself (Altman keeps saying that as well). (Still assuming you are using OpenAI) if your solution implementation has 2% prompts and AI specific stuff and 98% other functionality while AI is still central to your solution then you have possibly a moat. Seems existing systems adding AI are long term AI money makers.
  - ano88888 2y ago
    why does any software company have a moeat then, since everyone else can copy it with your logic.
    - anonzzzies 2y ago
      The technical moat for software companies is the effort to implement the logic; for instance, many companies have moats because they implement functionality that is hard to reproduce without having access to documentation needed to implement that functionality. It is also possible that there is so much functionality implemented over the years that copying it, while 'just work' is just too much work for most companies to really compete; SAP is an example. Then there is the example of OpenAI etc; too costly to reproduce simply by not having enough compute. Besides technical moats, you have client base moats; for instance, a trivial to implement application, like say, Resend (where you can find tons of open and paid alternatives for) did their marketing well (until they got hacked a few times that is) which gave them a moat and they still have some of it. Here is where large incubators give you some advantage; they use circlejerk to give you a lot of clients (their other companies and their clients) from the start. Then there is a regulatory moat which is common in banking, healthcare etc; you need certificates in distinct regions etc. That makes it harder to compete without having a lot of money. IP moats; maybe there are patents which competitors would need to work around. I'm against software patents however, they do exist and can hinder competitors to compete directly. These are all moats which hinder competitors coming up. If a large company wants to compete with your software solution, they can copy it and go after your market. Usually they will look at your moat and just buy you out giving them the moat. But yes, it is why VCs want you to grow as fast as possible at any cost; to 'take the market' so you have a moat in one or more of the above so in the end it's too much work to catch up and you'll be bought (exit). Solely on technical merit, it is expected that AI will remove this moat completely over time, but we are not there yet. We don't know what software will look like at that time anyway; probably not really recognisable vs now.
  - sabrina_ramonov 2y ago
    "LLM ops is not ops if you are using OpenAI" Even if you've plugged in OpenAI, there's a lot of ops work that goes into monitoring and managing output quality, reliability, and continuous improvements at scale.

blueboo 2y ago

They’re a PM’s whim away from being steamrolled by their foundation model vendor. And these startups are doing the product market fit for them The bigger the opportunity, the more general the audience, the juicier the B2B market, the greater the risk. Time was when Jasper was valued more highly than OpenAI. Now it’s flagging and OpenAI is headed for 12 digits…

yumraj 2y ago

Depends on whether the startup is building a feature or a product. A lot of AI startups that are building on top of OpenAI are effectively building a feature, a small very specific solution for a small use-case. Most of those are going to fail when OpenAI or some other entity with a product will add that feature to their product. But, if you solve a real large pain point that has value and use LLMs via OpenAI to add 1 or more features to your offering which allows it to solve that pain point more effectively and differentiate from competitors, then you have a moat.

sabrina_ramonov 2y ago
Not sure I understand the differentiation you're making between feature vs product. Perhaps startups start out as a "feature" but then build a full product around it. This path seems common and reasonable, given the very limited resources of a typical startup.

ano88888 2y ago

does people build using javascrapt or python or java programming language have a defensible moat since everyone can use that launage and immiate your ui/ux ideas.

anonzzzies 2y ago
Your technical moat is the complexity, quality and breadth of your solution; everything can be copied but the question is the effort. It is often just simpler to just buy you out vs building; especially if it's not only complex, good quality and has a client base. See also my other reply to you; https://news.ycombinator.com/item?id=40283601 https://news.ycombinator.com/item?id=40283601 The OP question was about LLM based companies using OpenAI api's. Most (almost all) of these are thin wrappers with some prompting; most of the ones introduced here on HN or Reddit, I can outperform in minutes. I try them all to see if someone is doing something interesting, but 99% are not, they just took some SaaS starter and added AI in there and threw it on social media. Even the ones that went somewhat further are still just doing straight forward things that can be replaced trivially inside the OpenAI playground. That's no moat at all. It looks flashy but...

muzani 2y ago

OpenAI and Anthropic builds extremely fast, even more so than most startups. There's little point building things like langchain, because OpenAI will build a better product a few months later. But you can build a product connected to OpenAI fine. Anthropic uses a similar API. Most of the smaller LLMs will also copy the same design so switching is cheap. It's probably not a smart idea to be completely dependent on OpenAI either. They're down all the time, can ban you on a whim, and their customer service is inaccessible.

deleted 2y ago

[deleted]

w3bperson 2y ago

Maybe not in the traditional sense of a moat, but maybe that's OK. It's difficult to create a deep moat with the commoditisation of technology and higher barriers to entry. Soon enough every company will be an AI company. So to create a moat it could be a case of creating a company that wasn't possible before AI that has the characteristics to create a moat - imagine something like a personal cooking assistant that links up with your health apps and buys your groceries for you, optimised for your health - add a yearly subscription for next-day delivery and you have your moat.

_akhe 2y ago

The moat could have nothing to do with the AI part. Examples: - e-commerce app is a thin ChatGPT wrapper for the shopping experience but their moat is their products and supply chain details - video game using LLM NPCs and other dynamic experiences but their moat is something else like incredible graphics or being based on some known IP - any business based on curation or archival of past LLM responses or interactions, moat could be some quality of that particular data, like other data businesses