Cognitive Drag is the UX-facing name for the slowdown that bad context creates. Where Reasoning Tax talks about cost and Reasoning Load talks about work, Cognitive Drag talks about the feeling: the model responding sluggishly, producing meandering answers, asking unnecessary clarification questions, or generating verbose output that circles around the answer before landing on it. Users experience Cognitive Drag as the model "not getting it" — but the root cause is usually that the context made it hard for the model to get it.
More in Reasoning Cost
Reasoning Tax
Extra model cost paid to compensate for context debt.
Token Bleed
Silent budget drain from re-onboarding — tokens spent re-explaining context the system should already hold.
Token Burn
Token waste caused by a client sending the entire session history to the LLM on every call.
Context Compensation
The model using additional reasoning to make sense of poor, bloated, or unstructured context.
Reasoning Inflation
More reasoning is required to extract the same signal from worse context.
Reasoning Load
The amount of interpretive work a model must perform before useful task execution begins.
Reasoning Efficiency
The model producing correct output with minimal interpretive overhead — the reward for clean context.
Token Leverage
Getting more useful output per token spent. The inverse of Token Bleed.