Most AI coding tools today rely on a single large language model to generate everything. That approach works for small tasks, but it often produces fragmented results when projects become complex.
To explore a different direction, I designed a multi-agent AI coding architecture that mirrors how real software teams operate.
Instead of one model doing everything, the system is structured around specialized roles that collaborate through routing and orchestration.
Core Idea
The architecture simulates a development team using role-based agents:
- Leader Agent — task decomposition and coordination
- Builder Agent — implementation and code generation
- UI/UX Agent — interface structure and design decisions
- Security Agent — vulnerability review and safety checks
- Tester Agent — validation and testing logic
- Memory Keeper — persistent context and system memory
All of these agents communicate through structured LLM routing.
At the center of the system is something called a Living Feature Tree — a structured map of features and tasks that acts as the single source of truth for the project.
Why This Architecture
The goal is to move beyond fragmented outputs and explore a production-style workflow for AI development.
Real engineering teams separate responsibilities, validate outputs, and coordinate work through shared planning structures. This design attempts to replicate those patterns in an AI-driven environment.
Open Design Spec
This project is not a startup or product.
It’s an open architecture specification created as a reference for developers, researchers, or builders who want to experiment with multi-agent systems.
The full design document is available in a single Markdown repository.
Looking for Feedback
I’d especially appreciate feedback on a few points:
- Does separating responsibilities into multiple agents make sense architecturally?
- What would be the best strategy for routing tasks between LLM agents?
- Could a Living Feature Tree realistically function as the coordination backbone?
If you work on AI tooling, orchestration systems, or developer automation, your perspective would be valuable.
Thanks for reading.
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