Quantum signal processing (QSP) has emerged as a unifying subroutine in quantum algorithms. In QSP, we are given a function (f) and a unitary black-box (U), and the goal is to construct a quantum circuit for implementing (f(U)) to a given precision. The existing approaches to performing QSP require a classical preprocessing step to compute rotation angle parameters for quantum circuits that implement (f) approximately. However, this classical computation often becomes a bottleneck, limiting the scalability and practicality of QSP. In this work, we propose a novel approach to QSP that bypasses the computationally intensive angle-finding step. Our method leverages a quantum circuit for implementing a diagonal operator that encodes (f), which can be constructed from a classical circuit for evaluating (f). This approach to QSP simplifies the circuit design significantly while enabling nearly optimal implementation of functions of block-encoded Hermitian matrices for black-box functions. Our circuit closely resembles the phase estimation-based circuit for function implementation, challenging conventional skepticism about its efficiency. By reducing classical overhead, our work significantly broadens the applicability of QSP in quantum computing.