I had the same experience and kept wondering if I was missing something important. I'm not a fan of Python, so I was anxious about not using the thing everybody recommended, but for my project I ultimately went with what I know well (C#). I've happily had zero issues.
LangChain docs and tutorials were useful for understanding the popular practices for approaching AI-driven development, but the biggest challenge by far has been getting a baseline prompt and measuring performance of alternative implementations against that in a sensible way that doesn't break the bank. Mitchell Hashimotos's Prompt Engineering article [1] was way more helpful in this regard than anything I saw in LangChain.
To that end I've also been working on a tool to save me money by caching requests and responses, blocking unexpectedly expensive requests, keeping a granular history of requests for prompt cost analysis, etc. Maybe I should open source it and get some VC bux too?
LangChain docs and tutorials were useful for understanding the popular practices for approaching AI-driven development, but the biggest challenge by far has been getting a baseline prompt and measuring performance of alternative implementations against that in a sensible way that doesn't break the bank. Mitchell Hashimotos's Prompt Engineering article [1] was way more helpful in this regard than anything I saw in LangChain.
To that end I've also been working on a tool to save me money by caching requests and responses, blocking unexpectedly expensive requests, keeping a granular history of requests for prompt cost analysis, etc. Maybe I should open source it and get some VC bux too?
[1] https://mitchellh.com/writing/prompt-engineering-vs-blind-pr...