3 ms·

It seems like Shopify has fallen into a trap thinking that more complexity costs nothing because of AI. In the age of AI we have to embrace the same principle a

It seems like Shopify has fallen into a trap thinking that more complexity costs nothing because of AI. In the age of AI we have to embrace the same principle as before that complexity needs to be tamed, not multiplied. Even as humans struggled with complexity, from what I see now AI struggles very much the same. Hence I don't think this will age well.

tonyhart7 24d ago
Yeah the problem is AI would improve exponentially and can do work 24/7 any engineering problem is just 'when' and 'how much' at that point
- ernsheong 24d ago
  Yeah but engineering is still subject to failure modes, AI can't circumvent that short of formal proofing (which nobody really wants to get into)
meowtimemania 24d ago
Another scary thing is with AI it's easy to let complexity get out of hand to the point where a human manually writing code is basically impossible. Even though AI might seem capable of handling the complexity, you'll start noticing all these weird bugs pop up all over your codebase.
- gib444 23d ago
  I'd say that was even a goal of the AI companies. It's not in their interest to generate human-maintainable code
  - bcjdjsndon 23d ago
    Aren't there open models you can get for free? What are their intentions?
    - gib444 23d ago
      Are enterprises using those free models for app development? With any kind of market share figure that isn't a rounding error, compared to eg Codex, Claude et al? You tell me - what are their intentions? I wasn't really thinking of open models tbh
    - written-beyond 23d ago
      Those models can never be capable enough to compare to the level of output generated by frontier labs. Where would you even host these models? Maybe a company like Shopify could manage self managing an few instances but that's it's own headache. Unless Shopify can show significant productivity gains by using ChatGPT or Anthropic's API pricing models there is no way they'll be able to justify using those services at those prices in the long term while maintaining their employee pool. The other option is to just stay with ChatGPT and Anthropic and fire almost all of their employees, but then they're running the risk of having a significantly worse customer experience in case your development cycle gets out of hand. They'd have lost most of their internal knowledge in the layoffs so they'd be stuck. If they don't do anything and just let their employees continue to work like they've always been but with LLMs to enhance productivity. Not to the point of implementing software factories, but as most people are using them in the industry. They lose nothing, gain productivity but their shareholders, investors and managers have been gaslit into believing if they're not 200x-ing their AI spending they're probably going to be left behind by competitors who are doing that. Also some of their larger investors may have investments in other AI companies and they probably strong arm them into contracts with those companies to benefit their portfolio.
  - pezo1919 22d ago
    Jeez, I did not even realize that! That’s a very good point (in general)!
N_Lens 24d ago
Always relevant - https://grugbrain.dev/ https://grugbrain.dev/
- sacul 23d ago
  That was great! But here is one place, at least, that needs to be updated for the AI era: > working demo especially good trick: force big brain make something to actually work to talk about and code to look at that do thing, will help big brain see reality on ground more quickly One of the best things about AI is that you can have a working prototype almost instantly, which is great for iterating quickly over ideas. But it means this trick simply doesn’t work anymore.
jbs789 23d ago
We should understand the complexity we are adding but having LLMs as a tool does also make managing the complexity easier.
Cthulhu_ 23d ago
Armchair / gut feeling opinion: using AI makes a developer feel like they can manage more code than they normally would. But it's a risk, if an agent can no longer make sense of the code, or the developer can no longer make sense of what the AI is saying, you're in trouble. Not a new problem, of course - developers wrangling large amounts of code (more than they should or can) is a recurring challenge in the industry.

tonyhart7 24d ago

Yeah the problem is AI would improve exponentially and can do work 24/7 any engineering problem is just 'when' and 'how much' at that point

ernsheong 24d ago
Yeah but engineering is still subject to failure modes, AI can't circumvent that short of formal proofing (which nobody really wants to get into)

meowtimemania 24d ago

Another scary thing is with AI it's easy to let complexity get out of hand to the point where a human manually writing code is basically impossible. Even though AI might seem capable of handling the complexity, you'll start noticing all these weird bugs pop up all over your codebase.

gib444 23d ago
I'd say that was even a goal of the AI companies. It's not in their interest to generate human-maintainable code
- bcjdjsndon 23d ago
  Aren't there open models you can get for free? What are their intentions?
  - gib444 23d ago
    Are enterprises using those free models for app development? With any kind of market share figure that isn't a rounding error, compared to eg Codex, Claude et al? You tell me - what are their intentions? I wasn't really thinking of open models tbh
  - written-beyond 23d ago
    Those models can never be capable enough to compare to the level of output generated by frontier labs. Where would you even host these models? Maybe a company like Shopify could manage self managing an few instances but that's it's own headache. Unless Shopify can show significant productivity gains by using ChatGPT or Anthropic's API pricing models there is no way they'll be able to justify using those services at those prices in the long term while maintaining their employee pool. The other option is to just stay with ChatGPT and Anthropic and fire almost all of their employees, but then they're running the risk of having a significantly worse customer experience in case your development cycle gets out of hand. They'd have lost most of their internal knowledge in the layoffs so they'd be stuck. If they don't do anything and just let their employees continue to work like they've always been but with LLMs to enhance productivity. Not to the point of implementing software factories, but as most people are using them in the industry. They lose nothing, gain productivity but their shareholders, investors and managers have been gaslit into believing if they're not 200x-ing their AI spending they're probably going to be left behind by competitors who are doing that. Also some of their larger investors may have investments in other AI companies and they probably strong arm them into contracts with those companies to benefit their portfolio.
- pezo1919 22d ago
  Jeez, I did not even realize that! That’s a very good point (in general)!

N_Lens 24d ago

Always relevant - https://grugbrain.dev/ https://grugbrain.dev/

sacul 23d ago
That was great! But here is one place, at least, that needs to be updated for the AI era: > working demo especially good trick: force big brain make something to actually work to talk about and code to look at that do thing, will help big brain see reality on ground more quickly One of the best things about AI is that you can have a working prototype almost instantly, which is great for iterating quickly over ideas. But it means this trick simply doesn’t work anymore.

jbs789 23d ago

We should understand the complexity we are adding but having LLMs as a tool does also make managing the complexity easier.

Cthulhu_ 23d ago

Armchair / gut feeling opinion: using AI makes a developer feel like they can manage more code than they normally would. But it's a risk, if an agent can no longer make sense of the code, or the developer can no longer make sense of what the AI is saying, you're in trouble. Not a new problem, of course - developers wrangling large amounts of code (more than they should or can) is a recurring challenge in the industry.