Two directions considered in this paper: (i) the philosophy and formalization of pragmatic aspects of information application in activity–efficiency, effectiveness, and potential with regard of information application–through explicit causal sequences of states-actions-transitions; and (ii) the Info-Activity Method (IAM), an architectural approach to solving human activity problems by representing questions as problems and answers as obtaining information within unified information–activity (“infact”) states. Classes of pragmatic characteristics (A–E) defined, the relation between efficiency and potential discussed through these characteristics. Next, it is shown how IAM’s data, modeling, application, and adaptation layers enable predictive, causal, and adaptive problem solving. An illustrative software sprint-planning scenario demonstrates how information quality and causal modeling improve risk-adjusted value. The approach supports predictive evaluation, synthesis, and optimization of activity under changing conditions.