# AI Workflow

This repository follows a lightweight AI-native engineering workflow.

```text
Context → Specs → Architecture → Implementation → Review → Iteration
```

---

# 1. Context Definition

Goal: create shared understanding.

Typical artifacts:

- Project vision
- Glossary
- Personas
- Architecture principles
- Tech stack

Context quality directly impacts AI output quality.

# 2. Spec Generation

Goal: break work into small incremental deliverables.

Good specs are:
- Small
- Focused
- Testable
- Independently understandable

# 3. Architecture Validation

Goal: ensure sustainable technical direction.

Architect responsibilities:
- Validate boundaries
- Identify risks
- Reduce complexity
- Support maintainability

# 4. Implementation

Goal: deliver working software incrementally.

Developer responsibilities:
- Implement clearly
- Respect architecture
- Preserve maintainability

# 5. Testing & Review

Goal: validate correctness and maintainability.

Focus on:
- Spec completion
- Workflow correctness
- Architectural consistency

# 6. Iteration

Goal: continuously improve:
- Specs
- Workflows
- Context
- Implementation

AI-native engineering is iterative by nature.