A modular approach to adaptive control of nonlinear systems introduced previously is presented in a general framework. This approach abandons the certainty equivalence principle ubiquitous in the estimation-based approach. The adaptive stabilization problem is studied in the setting of control Lyapunov functions, and is reduced to the problem of input-to-state stabilization with respect to the parameter estimation error considered as the input.