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LLM Systems
Building production systems on top of foundation models: retrieval, agents, fine-tuning, and evaluation.
Subject: Machine Learning · Roles: AI Engineer
Concepts
Retrieval-Augmented Generation (RAG)
Grounding an LLM's output in retrieved external documents instead of relying purely on its trained-in knowledge.
LLM Agents & Tool Use
Letting an LLM decide which actions to take — calling tools, APIs, or other models — rather than just generating text.
Fine-Tuning & Adaptation
Adapting a pretrained LLM's behavior via further training, and how that differs from prompting or RAG.
LLM Evaluation
Measuring whether an LLM-based system actually works, given that outputs are open-ended and hard to score automatically.