Day 07: Why confident AI answers still need evidence
Why confident language still needs evidence, boundaries, and uncertainty paths.
Series
From LLM Demo to AI Product
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.
Posts in this series
Day 08: Why production AI needs structured outputs
How structured output turns model text into something software can safely use.
Day 09: Why a capable model is still not a product
Why strong model capability still needs workflow, product, and ownership design.
Day 10: When to use a chatbot, workflow, or agent
A practical way to choose between conversation, repeatable workflows, and bounded autonomy.
Day 11: Why RAG is an evidence design problem, not a buzzword
Why RAG is really about trusted evidence, not just letting the model search.
Day 12: Why retrieval quality starts before search
Why answer quality starts when knowledge enters the system, not when the user asks.
