Glossary · Technical
Model Alignment
The training and tuning work done to make a model's outputs match what its developers consider safe, helpful and accurate, rather than simply statistically likely.
What it is
A model trained purely to predict likely text will happily produce confident, fluent statements regardless of whether they're true. Alignment adds further training on top of that — often involving human feedback — to make the model more willing to express uncertainty, decline unsafe requests, and prefer accurate over merely plausible-sounding answers.
Why it matters for AI visibility
How aligned and cautious a model is affects how willing it is to make definitive brand recommendations, cite sources, or repeat unverified claims. A more cautious model tends to hedge more and lean on citations; a less cautious one may state things more assertively from memory, which changes how a brand mention actually reads.
See more terms in the full glossary, or read the AI Visibility 101 guide for the full picture.