Code Agents are bad at Software Architecture – for now (blog.cohix.network)

The recent decision by a lead developer on the amux project to overhaul its architecture highlights the current limitations of AI code agents in software design. Despite their proficiency in generating code and executing specific tasks, even advanced foundation models like Opus struggle with high-level architectural reasoning and long-term codebase health. The developer noted that while AI agents can produce effective Rust code given clear specifications, they lack the ability to conceptualize how various components of a system integrate over time, leading to inefficient and error-prone coding practices. To address these challenges, the developer implemented a "grand architecture" which organizes the amux code into four distinct layers, ensuring that lower layers do not call upon higher ones. This structured approach aims to eliminate cross-contamination of business logic across the three frontends (TUI, CLI, and API) while promoting the use of typed objects instead of free functions. This careful architectural redesign not only seeks to rectify existing deficiencies but also prepares the foundation for future features and integrations, such as a desktop application and Kubernetes capabilities. The ongoing multi-agent refactor underscores a significant evolution in software development, stressing the need for human oversight in maintaining the integrity of complex systems while leveraging AI tools.