I build the invisible architecture that makes AI systems actually useful. My work sits at the intersection of context engineering, retrieval-augmented generation (RAG), and AI memory design — shaping how language models receive, retain, and reason over information. Former psychologist turned cloud data engineer, I bring an unusual lens to how humans and machines exchange knowledge.

My focus areas: designing RAG pipelines for food & nutrition intelligence, engineering context windows that reduce hallucination and improve retrieval precision, and architecting multi-layer memory systems (episodic, semantic, procedural) for AI agents. I care deeply about the unglamorous but critical work of making LLMs genuinely grounded — not just impressive in demos.