Platform & Systems
These systems show how I structure knowledge, documentation infrastructure, workflows, and automation models for complex technical environments.
Each system focuses on structure, flow, execution, and scalability.
Systems & Operating Models
The systems behind how documentation gets built, reviewed, and kept accountable — including where AI fits, and where it doesn't. Full build status for every system →
Release Documentation Traceability Checker
Status: Built and running
Catches a coverage gap most checks miss — a doc page that tags a ticket but was written before the sprint even started.
See the model →AI Governance & Review Operating Model
Status: Compliance checker built; operating model designed, not yet run with a team
What AI owns, what the team owns, and what I own as manager — the operating model that keeps AI-assisted documentation auditable as a team scales.
See the operating model →End-to-End AI-Assisted Publication Pipeline
Status: Built; one AI-drafted page merged through the PR gate on this site. Not yet run as a team workflow
Spec in, AI-assisted draft out, mandatory human review gate before anything publishes — and the planned link into ongoing health monitoring.
See the pipeline →Documentation Health Operating Cycle
Status: Checker built and running weekly against this site's own content; the team operating cycle is designed, not yet run with a team
A weekly cadence — flag, triage, assign, re-check — that runs a team against documentation health data instead of a quarterly manual audit.
See the operating cycle →AI-Driven Documentation Workflow — Release Notes Automation
Status: One sub-workflow (release notes) built and running; wider model designed, not built
The narrowest real slice of a broader vision — a batch of release tickets synthesized into structured, PM-ready release notes, using the same PR-gated review pattern as the Publication Pipeline.
See the workflow →Core Architecture
The information models and platform structures I'd apply to connect documentation across product, knowledge, and engineering systems. Designed during the sabbatical — not yet implemented in production.
End-to-End Product Documentation System
Status: Designed, not built
Product documentation works best when it is treated as an operating system, not a collection of files.
See the model →Knowledge Architecture Model
Status: Designed, not built
Technical knowledge can become fragmented across teams unless it is structured into clear domains, flows, and reusable system models.
Explore the model →Documentation Infrastructure
Status: Designed, not built
Documentation needs reliable infrastructure for authoring, version control, review, publishing, and distribution as products evolve.
See the design →Developer & Release Systems
How documentation integrates with API delivery, release cycles, and in-product user experience.
API Documentation & Developer Experience
Status: See the Impact Stories case study — built and led at Zeta, not a sabbatical concept
Improving developer onboarding and API adoption through structured documentation systems, workflow design, and integration-focused content.
See the case study →Release Documentation Workflow
Status: Designed, not built
A structured workflow for managing documentation across product releases, ensuring accuracy, consistency, and readiness at launch.
See the workflow →In-App Help & User Onboarding Experience
Status: Designed, not built
Designing contextual help and onboarding flows to improve product usability, reduce friction, and support user adoption.
See the design →Measurement
How documentation impact is tracked and reported as a measurable system.
Documentation Metrics & Impact System
Status: Designed, not built
A measurement framework for evaluating documentation effectiveness, user outcomes, and self-service success in enterprise products.
See the framework →