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This is a great question! I think we now know, collectively, a lot more about what’s annoying/hard about building LLM features than we did when LangChain was b
by lordofmoria 3y ago
This is a great question!
I think we now know, collectively, a lot more about what’s annoying/hard about building LLM features than we did when LangChain was being furiously developed.
And some things we thought would be important and not-easy, turned out to be very easy: like getting GPT to give back well-formed JSON.
So I think there’s lots of room.
One thing LangChain is doing now that solves something that IS very hard/annoying is testing. I spent 30 minutes yesterday re-running a slow prompt because 1 in 5 runs would produce weird output. Each tweak to the prompt, I had to run at least 10 times to be reasonably sure it was an improvement.
- codewithcheese 3y agoIt can be faster and more effective to fallback to a smaller model (gpt3.5 or haiku), the weakness of the prompt will be more obvious on a smaller model and your iteration time will be faster
- JeremyHerrman 3y agogreat insight!
- sroussey 3y agoHow would testing work out ideally?