TOPIC
LLMs
5 entries across the knowledge base
Prompt engineeringDesigning the input is designing the behaviour: instructions, context, examples and output contracts that make LLMs reliable.concept · 3 min · foundationGuardrails & safetyThe layers around a model that keep it in-scope, grounded and resistant to manipulation — engineering, not hope.concept · 3 min · practitionerAmbient documentationThe AI scribe: listen to the visit, draft the note — attacking healthcare's documentation burden at its source.concept · 3 min · foundationRetrieval-Augmented Generation (RAG)Ground an LLM's answer in your own documents: retrieve relevant passages first, then generate with them in context — citations included.concept · 3 min · foundationAI agents & tool useAn LLM in a loop: reason, call a tool, observe the result, repeat — turning a text generator into a system that does things.concept · 3 min · foundation