Cohere Fundamentals: Models, Prompts, Embeddings and Grounding
How does a prompt become a response,and what happens when an AI system needs reliable information beyond what a language model already knows?
This opening workshop introduces the foundations behind applications built with Cohere. We will move beyond the idea of AI as a simple chatbot and examine how generation, embeddings, retrieval, reranking, and grounding work together.
What we will cover
How language models process prompts and generate responses
Tokens, context windows, instructions, and generation settings
The different roles of Cohere Command, Embed, and Rerank
How embeddings represent semantic meaning
The difference between keyword search and semantic retrieval
How reranking improves the order of retrieved results
Why grounding matters for reducing unsupported answers
Common failure modes, including hallucinations and stale context
Where agents fit within a grounded AI system
The session will use clear visual explanations and short interactive knowledge checks throughout. It is designed to establish the vocabulary and mental models needed for the more technical workshops that follow.
No live coding is required for this first session. Participants will be encouraged to explore the Cohere Playground independently afterward and arrive at the next workshop ready to work with Python and the Cohere API.
This is the first session in Dunia Hub’s four-part series, From Fundamentals to Version-Grounded AI, which will progressively build toward an open-source, version-aware code agent and accompanying research study.
Who should attend
Developers, students, researchers, technical founders, and curious builders who want to understand how modern AI systems retrieve, evaluate, and ground information.
Supported by Cohere Labs.