What the Systems Architect does
Discovers your environment
Connects to your providers using read-only credentials and maps what actually exists — systems, resources, configurations, relationships, access models, and dependencies
Normalizes into an ontology
Translates provider-specific resources into a project-scoped cross-provider ontology so that AWS resources, Okta tenants, Snowflake warehouses, and Databricks workspaces can be reasoned about in the same implementation graph
Generates the implementation blueprint
Produces a complete rollout structure: phased checklist, architecture diagrams, process flows, stakeholder map, RACI assignments, goals, evidence requirements, and post-implementation plan
What it produces
| Output | Description |
|---|---|
| Systems ontology | Hierarchical map of discovered systems with mapping states (confirmed, inferred, flagged) and critical findings |
| Implementation checklist | Phased tasks with dependencies, acceptance criteria, effort estimates, owners, and evidence requirements |
| Architecture diagrams | Interactive dependency graphs showing task relationships and critical path |
| Process flows | Cross-system workflows with actors, durations, variants, and bottlenecks |
| Stakeholder map | Organizational roles, relationships, RACI assignments, and ownership matrix |
| Goals | Measurable success criteria with target values and tracking signals |
| Post-implementation plan | Support model, monitoring setup, adoption metrics, and operational continuity |
How it stays current
The Systems Architect is not a one-time generator. When you trigger a health refresh or re-run discovery:- New systems and resources are surfaced
- Checklist tasks update to reflect current state
- Risks are re-evaluated against live conditions
- Stakeholder assignments carry forward
- Evidence and approval state is preserved
AI with human authority
The Systems Architect accelerates synthesis and discovery, but humans retain control at every decision point:- Inferred mappings require human confirmation before they’re treated as fact
- Generated tasks can be edited, reordered, or removed
- Ownership suggestions are proposed, not imposed
- Approval gates require named approvers — the AI cannot bypass them
- Evidence requirements must be satisfied with actual proof
Next steps
Blueprints
Understand what a blueprint contains
Creating blueprints
Create your first blueprint