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No, AI isn't. Any new tech, or version upgrade, or whatever, takes time for people to become familiar with it. You might as well say "Stack Overflow is stiflin

No, AI isn't. Any new tech, or version upgrade, or whatever, takes time for people to become familiar with it. You might as well say "Stack Overflow is stifling new tech adoption" because brand-new stuff doesn't have many Q's and A's yet. But that would be a silly thing to say. I'm not going to adopt a brand-new database regardless of LLM training data cutoff, just because enough people haven't had enough experience with it. And LLM's have a commercial incentive to retrain every so often anyways. It's not like we're going to confront a situation where an LLM doesn't know anything about tech that come out 5 or 10 years ago. Early adopters will be early adopters. And early adopters aren't the kind of people relying on an LLM to tell them what to try out.

deleted 2y ago
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TheTaytay 2y ago
I feel myself taking AI’s base knowledge of a tech stack into account when I work. Otherwise it feels like I am swimming upstream. I can’t be the only one, and this article resonated for me.
- crazygringo 2y ago
  Sure, but what I'm saying is that's not where the knowledge bottleneck is. The knowledge bottleneck is in the human population, which is then reflected in Stack Overflow and blogs, which is then reflected in LLM's. LLM's aren't doing anything special to stifle new tech adoption. New tech is harder to adopt because it's new tech, because people in general are less familiar with it. (And there's a little bit of a training delay in LLM's updating, but that's a minor aspect here compared to the years it takes for a new Python package to become popular, for example.)
  - hinkley 2y ago
    It’s generally true that the people who come up with the first interesting idioms in a new space get an outsized influence on the community. It takes a while for people to borrow or steal their ideas and run with them. On the plus side while the AI can’t write in that language there’s money to be made doing the work organically.
  - mst 2y ago
    Yes, but I think it's also true that LLMs are acting as a force multiplier to the underlying effect you describe. Something like (my apologies to maths for the abuse) LLMs are adding one to the exponent of the adoption feedback cycle.
milesvp 2y ago
Strong disagree here. I've been trying to learn Zig, and I'm thwarted enough by chatgpt giving me outdated information on Zig's unstable API that if I didn't have a strong incentive to learn it for it's cross compiler, I'd likely turn my efforts towards another language. This effect can greatly alter the adoption curve of a new tech, which can leave it dying on the vine. You're not wrong though, in that Stack Overflow has the exact same problem. The main difference is that with Stack Overflow, there was a bonus in becoming the first expert on the platform, so while it does stifle new tech adoption, it at least encourages new tech content creation, which in turn encourages new tech. Though, I don't know if it's a net positive or negative in aggregate. I think this problem will likely lessen as training becomes cheaper and faster. But right now, there is really strong incentives to avoid any tech that has had breaking changes in the last 3 years.
- throwup238 2y ago
  Have you tried Cursor instead of a chatbot? I don’t trust it to do much coding for me but it has this feature where you give it the URL of the documentation, and it indexes it for you. Then you can reference that documentation in the chat with the @ symbol and Cursor applies RAG to the indexed content to include relevant documentation. I usually index autogenerated API docs and any website docs the library has like guides and tutorials. The experience is night and day and it’s the only reason I pay for Cursor on top of OpenAI/Anthropic. The answers it gives are much more accurate when including documentation and it helps a lot with exploring APIs. Probably helps a lot with the code generation too, but I don’t use Composer as much.
  - giovannibonetti 2y ago
    Yeah, RAG is a great way to handle outdated docs
- hinkley 2y ago
  Someone recently put it that it’s the first 10% of adoption that sets the future for a product. There are people online calling it the “tech adoption cycle” but this is a concept I encountered in a literal Business 101 class. 2.5% of the population are Innovators. 12.5 are early adopters. Then there’s 70% in the middle where most of your cash comes in, and by the time the laggards hit you’re optimizing for cost per unit because you’ve had to drop the price so much due to competition from copycats and from the next new thing. So by the time 60% of your early adopters are onboard it’s already been decided if you’re on a rocket ship or this is just a burp. Early adopters have a high tolerance for inconveniences but it’s not infinite. If they bleed enough they will find something else, and then you are DOA.
WhyOhWhyQ 2y ago
"Early adopters will be early adopters. And early adopters aren't the kind of people relying on an LLM to tell them what to try out." Why is this? 'Early adopter' is a pretty arbitrary category of people.

deleted 2y ago

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TheTaytay 2y ago

I feel myself taking AI’s base knowledge of a tech stack into account when I work. Otherwise it feels like I am swimming upstream. I can’t be the only one, and this article resonated for me.

crazygringo 2y ago
Sure, but what I'm saying is that's not where the knowledge bottleneck is. The knowledge bottleneck is in the human population, which is then reflected in Stack Overflow and blogs, which is then reflected in LLM's. LLM's aren't doing anything special to stifle new tech adoption. New tech is harder to adopt because it's new tech, because people in general are less familiar with it. (And there's a little bit of a training delay in LLM's updating, but that's a minor aspect here compared to the years it takes for a new Python package to become popular, for example.)
- hinkley 2y ago
  It’s generally true that the people who come up with the first interesting idioms in a new space get an outsized influence on the community. It takes a while for people to borrow or steal their ideas and run with them. On the plus side while the AI can’t write in that language there’s money to be made doing the work organically.
- mst 2y ago
  Yes, but I think it's also true that LLMs are acting as a force multiplier to the underlying effect you describe. Something like (my apologies to maths for the abuse) LLMs are adding one to the exponent of the adoption feedback cycle.

milesvp 2y ago

Strong disagree here. I've been trying to learn Zig, and I'm thwarted enough by chatgpt giving me outdated information on Zig's unstable API that if I didn't have a strong incentive to learn it for it's cross compiler, I'd likely turn my efforts towards another language. This effect can greatly alter the adoption curve of a new tech, which can leave it dying on the vine. You're not wrong though, in that Stack Overflow has the exact same problem. The main difference is that with Stack Overflow, there was a bonus in becoming the first expert on the platform, so while it does stifle new tech adoption, it at least encourages new tech content creation, which in turn encourages new tech. Though, I don't know if it's a net positive or negative in aggregate. I think this problem will likely lessen as training becomes cheaper and faster. But right now, there is really strong incentives to avoid any tech that has had breaking changes in the last 3 years.

throwup238 2y ago
Have you tried Cursor instead of a chatbot? I don’t trust it to do much coding for me but it has this feature where you give it the URL of the documentation, and it indexes it for you. Then you can reference that documentation in the chat with the @ symbol and Cursor applies RAG to the indexed content to include relevant documentation. I usually index autogenerated API docs and any website docs the library has like guides and tutorials. The experience is night and day and it’s the only reason I pay for Cursor on top of OpenAI/Anthropic. The answers it gives are much more accurate when including documentation and it helps a lot with exploring APIs. Probably helps a lot with the code generation too, but I don’t use Composer as much.
- giovannibonetti 2y ago
  Yeah, RAG is a great way to handle outdated docs
hinkley 2y ago
Someone recently put it that it’s the first 10% of adoption that sets the future for a product. There are people online calling it the “tech adoption cycle” but this is a concept I encountered in a literal Business 101 class. 2.5% of the population are Innovators. 12.5 are early adopters. Then there’s 70% in the middle where most of your cash comes in, and by the time the laggards hit you’re optimizing for cost per unit because you’ve had to drop the price so much due to competition from copycats and from the next new thing. So by the time 60% of your early adopters are onboard it’s already been decided if you’re on a rocket ship or this is just a burp. Early adopters have a high tolerance for inconveniences but it’s not infinite. If they bleed enough they will find something else, and then you are DOA.

WhyOhWhyQ 2y ago

"Early adopters will be early adopters. And early adopters aren't the kind of people relying on an LLM to tell them what to try out." Why is this? 'Early adopter' is a pretty arbitrary category of people.