Start here¶
This portfolio is a small, public set of samples showing how I approach documentation as a product: clear information architecture, consistent patterns, developer-first content, docs-as-code workflows, and AI-assisted documentation governance.
Suggested project path¶
For the clearest picture, review the portfolio in this order:
- docs-portfolio - baseline documentation samples and working style
- docs-ai-operating-model - flagship AI DocsOps operating model for quality gates, PromptOps, governance, and evaluation
- openapi-to-human-reference - API documentation transformation from OpenAPI source to readable Markdown reference
- docsops-quality-gate - reusable documentation quality gate for PR workflows
Suggested reading order for this site¶
A quick path through the materials in this site:
-
How I structure information: Mental model
The framing and boundaries: what belongs where, and why. -
How I guide users through a task: Send your first event
A practical flow with prerequisites, success criteria, and clear steps. -
How I document an API: Event Intake API reference
Reference patterns, examples, and what developers need at integration time. -
How I handle failure modes: Event Intake API issues
Symptom -> likely cause -> fix, written to reduce back-and-forth.
Conventions used across the docs¶
- Topic-based writing: concept, how-to, reference, and troubleshooting
- Task-first structure: prerequisites, steps, expected results, and pitfalls
- Consistency: terminology and style are treated as part of quality, not an afterthought
- Maintainability: content is designed to be reviewed, versioned, and iterated
What I would extend next¶
- Findability: tune labels and navigation to match common entry points and search terms
- Reference depth: add auth, error model consistency, pagination, and idempotency patterns
- Operational model: define ownership, review cadence, and definition of done per doc type
- Feedback loop: add lightweight signals such as page feedback and support patterns to guide iteration