Understanding Architecture V1
What your generated Architecture V1 represents and how it establishes the foundation for your ongoing system evolution.
Understanding Architecture V1
Architecture V1 is the first canonical architecture baseline produced by Bootstrap Discovery. It represents a coherent, complete system model ready for real-world engineering.
Architecture V1 Baseline
The initial canonical architecture model rendered in the workspace upon completing Bootstrap Discovery.
What Architecture V1 Contains
When you open your Architecture V1 in the workspace, you receive a fully structured system containing:
1. The Canonical Model Graph
A complete graph of system entities, including:
- Services & Compute: Web applications, API gateways, background workers.
- Data Stores: Primary databases, caching layers, document storage.
- Messaging & Event Streams: Message queues, pub/sub topics, streaming pipelines.
- External Boundaries: Third-party APIs, auth providers, CDNs, external storage.
- Connections: Protocols (HTTP, gRPC, WebSocket), data flow directions, and coupling boundaries.
2. Traceability Grounding
Every element in Architecture V1 is connected directly back to the capability and requirement that justified its creation. You never have orphaned infrastructure with unclear ownership.
3. Baseline Health Metrics
An initial evaluation of:
- Architecture Coverage: Percentage of discovered capabilities backed by explicit components.
- Decision Confidence: Average confidence score across all generated decisions.
- Open Decision Count: Material topics flagged for your review.
Architecture V1 Is Not Carved in Stone
Architecture V1 is your starting baseline—not a rigid decree.
A Living System
Traditional architecture documents become outdated because updating them is tedious. In Avylo, Architecture V1 is the beginning of a continuous conversation between you and the AI Architect.
Recommended Next Steps After V1
- Inspect the Visual Canvas: Explore system components, zoom into specific domains, and inspect component properties.
- Review Assumptions: Confirm or adjust the baseline assumptions made by the AI Architect during discovery.
- Address Open Decisions: Prioritize high-impact open decisions that determine core technology choices.
- Evaluate Architecture Health: Check if any critical requirements remain unaddressed before starting development.