# Avylo AI Documentation

> Avylo is an AI-native Architecture Operating System for technical founders and reviewers that helps users build, understand, review, and evolve one living software architecture model.

## Documentation Index

- [Frequently Asked Questions](https://docs.avyloai.com/docs/faq): Common questions about Avylo, the living architecture model, AI reasoning, and collaboration.
- [Getting Help & Support](https://docs.avyloai.com/docs/getting-help): How to get assistance, share feedback, and report issues during the Avylo Private Alpha.
- [Documentation Overview](https://docs.avyloai.com/docs): Welcome to the official Avylo AI public documentation.
- [Domains, Capabilities & Requirements](https://docs.avyloai.com/docs/architecture/capabilities-requirements): How Avylo decomposes high-level business blueprints into buildable functional units and explicit engineering requirements.
- [Architecture Decisions & Explainability](https://docs.avyloai.com/docs/architecture/decisions): How Avylo captures, evaluates, and documents material architecture choices with complete traceability and trade-off analysis.
- [The Canonical Architecture Model](https://docs.avyloai.com/docs/architecture/model): Understanding the authoritative source of truth for your system components, boundaries, and connections.
- [Project Knowledge & Blueprint](https://docs.avyloai.com/docs/architecture/project-knowledge-blueprint): Understanding the foundational intent layer that grounds your technical architecture in business reality.
- [Core Concepts](https://docs.avyloai.com/docs/getting-started/core-concepts): The canonical vocabulary and mental model behind the Avylo Architecture Operating System.
- [Create Your First Architecture](https://docs.avyloai.com/docs/getting-started/first-architecture): Step-by-step guide to starting a greenfield project and completing Bootstrap Discovery.
- [Introduction](https://docs.avyloai.com/docs/getting-started): Discover Avylo, the AI-native Architecture Operating System designed for technical founders, lead engineers, and reviewers.
- [Understanding Architecture V1](https://docs.avyloai.com/docs/getting-started/understanding-architecture-v1): What your generated Architecture V1 represents and how it establishes the foundation for your ongoing system evolution.
- [Reviewer Experience & Feedback](https://docs.avyloai.com/docs/review/reviewer-experience): How technical reviewers inspect architecture, explore trade-offs, and submit structured feedback.
- [Sharing an Architecture](https://docs.avyloai.com/docs/review/sharing): How to invite technical reviewers, advisors, and team members to inspect your living architecture model.
- [Working with the AI Architect](https://docs.avyloai.com/docs/workspace/ai-architect): How the AI Architect reasons about your system, evaluates trade-offs, and proposes changes while preserving creator authority.
- [Assumptions vs. Open Decisions](https://docs.avyloai.com/docs/workspace/assumptions-open-decisions): Understanding how Avylo categorizes and manages architectural uncertainty.
- [Architecture Health & Maturity](https://docs.avyloai.com/docs/workspace/health-maturity): Track evidence-based architecture coverage, confidence, drift detection, and objective lifecycle maturity stages.
- [Workspace Overview](https://docs.avyloai.com/docs/workspace): Navigating the central Avylo Architecture Workspace, interactive canvas, properties inspector, and history timeline.

## Core Concepts

- **Project Knowledge**: Private, revisioned source material and problem context provided by the creator.
- **Blueprint**: Structured synthesis of business intent and functional scope.
- **Domains & Capabilities**: Buildable functional decomposition of product requirements.
- **Architecture Decision**: Material architectural choices with recommendation, alternatives, trade-offs, evidence, and confidence.
- **Canonical Architecture Model**: The authoritative, editable model of system components, boundaries, and connections.
- **AI Architect**: Continuous reasoning partner that investigates trade-offs and prepares proposals without overriding creator authority.
- **Assumptions vs Open Decisions**: Assumptions are AI-inferred baseline values; Open Decisions represent material architectural uncertainty.
- **Architecture Health & Maturity**: Evidence-based metric coverage and stage progression (Idea → Business Defined → Capabilities Complete → Architecture Stable → Deployment Ready).