I posted the short courses just as answer to how to address quality control. I'm not selling anything, and those courses are free anyway. deeplearning.ai was cofounded by Andrew Ng, who is probably the most well known for his work on teaching machine learning through deeplearning.ai, Coursera, Stanford, etc. He has taught and influenced millions.

https://en.wikipedia.org/wiki/Andrew_Ng

In regards to "evaluation", I think these is what those short courses will cover:

Self-Evaluation with the LLM: The idea is to use the language model to generate an answer and then use the same or a different model to evaluate that answer. The evaluation could involve asking the model to rate the answer's accuracy, coherence, relevance, or any other desired metric. This self-evaluation process can be automated and scaled, although it's important to be aware of the limitations, as the model might inherit biases or blind spots from its training data.

LangChain for Structured Evaluation: LangChain can be used to structure this self-evaluation process. It can orchestrate the flow where the LLM first generates an answer and then follows a series of steps to evaluate it. This might include breaking down the evaluation into specific questions or tasks that the LLM must perform to assess its initial response.