Inside the Scaffold: A Source-Code Taxonomy of Coding Agent Architectures

1. 1Identify key components of coding agent architectures, such as control loops and state management
2. 2Analyze existing surveys and trajectory studies to understand limitations in current classification methods
3. 3Develop a taxonomy based on source-code analysis to distinguish between architecturally distinct systems
4. 4Apply the taxonomy to real-world coding agents to validate its effectiveness

AI engineers and researchers benefit from this study as it provides a deeper understanding of coding agent architectures, enabling them to design and develop more efficient systems

💡 Understanding the scaffolding code surrounding language models is crucial for developing efficient coding agents

🤖 New taxonomy for coding agent architectures! 📈