Thanks for the spotlight :) We've spent quite a lot of time working on the Agents lately, and it's definitely a big focus. Couple of extra points to reflect on some of the comments here. It's quite straightforward to build a hybrid NLP backend with Haystack combining either hosted LLM (e.g., OpenAI or Cohere), or local, smaller Transformer models, or both. Agents add another level of control on top of that, as described in the article and in the comments. This provides more flexibility wrt bridging it to the relevant data and extract/generate accurate non-hallucinatory answers. Join our Discord too :) https://haystack.deepset.ai/community