Learning AI engineering with Ruby

[u/hitthatliq]

I'm learning more about AI engineering, specifically the application/production side rather than ML research or training models.

The areas I'm interested in are things like:

• RAG, embeddings, vector search and reranking
• tool/function calling
• agentic workflows and orchestration
• MCP clients/servers
• structured outputs
• evals and observability
• persistent agent state / human approval
• building production AI features into normal web applications

I originally learned to code with Ruby, but since then all my jobs have been Python or TypeScript based, and I really miss working with Ruby.

I'm curious what Ruby libraries/tools people are using for RAG, agents, MCP, evals, tracing, etc. Are there good Ruby alternatives to frameworks like LangChain? What does your stack look like?

And if you were learning this stuff today, would you recommend doing it in Ruby, or sticking with Python because that's where most of the ecosystem and learning material is?

I'm not trying to avoid Python entirely. I'm more curious about how viable Ruby is for the application/agentic side of AI development.

Side note: I realise some of these areas aren't particularly language-specific. For example, with RAG a lot of the retrieval/storage work may ultimately be handled by pgvector, a vector database, or another service.

[u/Jaded_Cauliflower692]

Openclarcky is written by ruby