GenAI & LLM Mentorship Concepts, RAG & Python

Large Language Models are reshaping how software is built and most learning resources either stay too shallow or go too deep too fast.

In this 30-minute session, we cut through the noise. We can cover how LLMs actually work under the hood, how to design and build RAG pipelines from scratch, how vector embeddings and semantic search tie into real applications, how to write clean Python code for AI workflows, or how to position yourself for an AI/ML career when you are just starting out.

I have hands-on experience building GenAI systems on enterprise platforms and working with retrieval-augmented architectures in production contexts. I bring that practical depth into every conversation, not just theory.

Come with a problem, a concept you are stuck on, or a career question. We will make the 30 minutes count.