Articles tagged: LLM
Generative text can sound complete while quietly inventing defaults, guarantees or citations. Build a verification pass around authoritative sources, executable examples and explicit uncertainty. The dangerous AI error in documentation is rarely broken grammar.
In three years, generative AI turned a first draft from an expensive output into a cheap operation. The important question is no longer whether a model can write, but who owns facts, structure, review, updates, and quality once text can be produced in minutes.
If a model can create or update documentation at scale, validation must scale with it. Constrain inputs, preserve provenance, validate structure and make publication a separate privileged step. A useful architecture assumes the model will sometimes be wrong.
Generated examples can accelerate documentation work, but they must never be allowed to invent product behavior and then validate themselves. A code example is a factual claim about fields, values, order and behavior.