RLHF

RLHF aligns a model to human preferences using a reward model and reinforcement-style optimization.

RLHF shows up constantly when teams ship LLM features. Practically, it influences how you design prompts, evaluate quality, and reason about failure modes. Teams should document how RLHF manifests in their stack—data handling, evaluation, and runtime guardrails—and revisit assumptions as models update.