The core idea
A language-model stage needs a defined input, a limited task, and an output that can be checked. Keep extraction, topic assignment, summary writing, and approval separate. That makes it possible to locate a failure instead of attributing every problem to one undifferentiated “AI” step.
A workable starting pattern
Provide a controlled vocabulary and representative examples. Allow uncertain or empty results where evidence is insufficient. Keep source version, instruction version, and model identifier in the internal record. Compare changes using a retained evaluation set rather than judging only a few attractive outputs.
A test set can include a tutorial, a mixed interview, and a news item with quoted claims. The workflow should preserve which statement belongs to the author and which belongs to a source being discussed.
What this page does—and does not—offer
This topic is architectural guidance. TagsFeed does not host a language model, expose inference endpoints, or provide model credentials.
