In this paper, we investigate LLM-assisted code generation using architectural documentation as a first-class input. Building on prior work that guides LLMs through Attribute-Driven Design (ADD), we propose a workflow in which the LLM synthesizes an implementation plan from requirements and an architecture document, and then generates code with human oversight. Using a ReAct-style agent as a case study, we perform three experiments and evaluate architectural conformance and functional correctness of a primary use case. In addition we capture size and modularity metrics using the DV8 tool. Our results show that incorporating architectural documentation substantially improves conformance and that adding an explicit implementation plan further enhances functional correctness and modularity.