Steering Vectors: Changing What an LLM Wants Without Touching Its Weights

LLMs encode concepts as geometric directions in activation space. You can find those directions, add them at inference time, and shift model behavior - without touching a single weight. This is called steering vectors , and it works. The core idea A language model's residual stream is a high-dimensional vector that accumulates information as it passes through layers. The linear representation hypothesis says that concepts like "pessimism," "formality," or "Python expertise" correspond to…