Day 07: Why confident AI answers still need evidence
Why confident language still needs evidence, boundaries, and uncertainty paths.

Search for a command to run...

Series
A practical bridge from language-model demos to usable AI products. This series covers hallucination, structured outputs, product boundaries, chatbot versus workflow versus agent choices, and the first RAG and ingestion decisions that make answers more trustworthy.
Why confident language still needs evidence, boundaries, and uncertainty paths.

How structured output turns model text into something software can safely use.

Why strong model capability still needs workflow, product, and ownership design.

A practical way to choose between conversation, repeatable workflows, and bounded autonomy.

Why RAG is really about trusted evidence, not just letting the model search.

Why answer quality starts when knowledge enters the system, not when the user asks.
