Practical thinking for teams building document intelligence in production.
Why reliable RAG requires explicit, measurable pipeline decisions instead of one-off demos.
How chunking quality sets the ceiling for retrieval and answer reliability.
Why anecdotal correctness is not evaluation and cannot sustain production trust.
What changes when RAG leaves notebooks and enters real production constraints.
Most RAG hallucinations come from retrieval and context failures, not model magic.
Noesia's definition of understanding: source traceability, reasoning clarity, and uncertainty.
