Architecture is the product decision layer
AI app architecture is not a folder tree or a diagram made after the fact. It names the system that must stay coherent while implementation changes: what the product is, who it serves, which records matter, and which workflow owns each important decision.
- Core objects, actors, and product surfaces
- Source of truth, authority boundaries, and state changes
- Critical workflows, invariants, and scope boundaries
- What belongs now, what can wait, and what must not silently change
Start from the project you actually have
A new build needs its first coherent product shape. A messy existing app needs its useful center separated from accumulated implementation noise. A drifting product needs competing directions brought back under one decision boundary. The starting point changes, but the need for architecture does not.
Why a generic planning chat eventually breaks down
A planning chat can produce good ideas without preserving the decisions it made last week. Once sessions, agents, or models change, the same product gets interpreted again. Driftbreak makes the important product decisions explicit before the next implementation task is handed off.
Architecture, blueprint, and AI-directed development have different jobs
Architecture defines what the system must be and protect. The technical blueprint defines how modules, records, interfaces, and validation implement it. AI-directed development gives a coding agent a controlled way to investigate, implement, report evidence, and ask for a decision instead of silently making one.
