Sonnet 3.6 (the 2022-10-22 release of Sonnet 3.5) is head and shoulders above GPT-4 and anyone who has been using both regularly can attest to this fact.
Reasoning models do reason quite well but you need the right problems to ask them. Don't throw open-ended problems at them. They perform well on problems with one (or many) correct solution(s). Code is a great example - o1 has fixed tricky code bugs for me where Sonnet and other GPT-4 class models have failed.
LLMs are leaky abstractions still - as the user, you need to know when and how to use them. This, I think, will get fixed in the 1-2 years. For now, there's no substitute for hands on time using these weird tools. But the effort is well worth it.
I’d argue that most coding problems have one truly correct solution and many many many half correct solutions.
I personally have not found AI coding assistance very helpful, but from blog posts by people who do much of the code I see from Claude is very barebones html templates and small scripts which call out to existing npm packages. Not really reasoning or problem solving per se.
I’m honestly curious to hear what tricky code bugs sonnet has helped you solve.
It’s led me down several incorrect paths, one of which actually burned me at work.
Sonnet 3.6 (the 2022-10-22 release of Sonnet 3.5) is head and shoulders above GPT-4 and anyone who has been using both regularly can attest to this fact.
Reasoning models do reason quite well but you need the right problems to ask them. Don't throw open-ended problems at them. They perform well on problems with one (or many) correct solution(s). Code is a great example - o1 has fixed tricky code bugs for me where Sonnet and other GPT-4 class models have failed.
LLMs are leaky abstractions still - as the user, you need to know when and how to use them. This, I think, will get fixed in the 1-2 years. For now, there's no substitute for hands on time using these weird tools. But the effort is well worth it.