Grounded LLM generation: what it means and where it still goes wrong

Retrieval-augmented generation answers questions about indexed interview transcripts by retrieving relevant chunks and grounding the model's output in those chunks. Here is how the pipeline works and where it still fails.

Embedding-based semantic search finds passages by meaning rather than by matching words. Here is what an embedding is in plain terms, how the search works, and where it still misses things.

A documentary character profile gives directors a view of who they have across all interview hours. Here is what to include, what to leave out, and when in the production timeline it pays to write one.