The Waterfall Parallel
Why Spec-Driven Development recreates the same structural dissociation that made waterfall fail in teams.
Architecture Driven Development
ArDD
A methodology for coherent AI-assisted software development
This site is built around the white paper itself: a reading-first publication that argues Spec-Driven Development is necessary, but not sufficient, for team-scale AI-assisted software development.
Abstract
ArDD replaces the spec as the primary artefact with the living architecture model, giving AI agents the full system context they need before implementation begins.
“The paper on your desk was always the architecture. ArDD is just where the paper lives now.”
Abstract
Architecture Driven Development
ArDD — a methodology for coherent AI-assisted software development, replacing specs as the primary artefact with the living architecture model.
Contents
The white paper structure
The site is organized around one primary paper and its chapters, rather than around a conventional blog homepage.
- Abstract
- 1. Introduction
- 2. The Historical Parallel: Waterfall and the BA Problem
- 3. How Good Engineers Actually Work
- 4. Architecture Driven Development: Definition and Principles
- 5. ArDD in Practice: A Concrete Comparison
- 6. ArDD and AI Agents: Why Architectural Context Produces Better Code
- 7. Maintaining Perspective at AI Velocity
- 8. Scaling Teams and Agent Fleets with ArDD
- 9. Team Dynamics and Agile Compatibility
- 10. SDD and ArDD: A Structured Comparison
- 11. Implementing Architecture Driven Development
- 12. Reference Implementation: uxxu.io
- 13. Conclusion
- References
Key arguments
What the paper is trying to prove
ArDD as the Primary Artefact
How the living architecture model becomes the design, constraint set, and implementation contract for humans and AI agents.
Perspective at AI Velocity
Why code generation speed is not enough, and how architecture becomes the control plane that preserves coherence.
Position
Do not stop at specifying your AI. Architect the context around it.
The white paper frames ArDD as the formalisation of how good engineers already work: understand the system first, then code within its structure. AI makes that discipline more important, not less.