Quality engineering for the AI era.
Quality Engineering • Applied AI • Test Leadership
I lead quality across complex enterprise systems and build practical AI-enabled workflows, learning labs and engineering prototypes focused on governance, testability and human control.
Quality Leadership
19+ years
Applied AI
Governed workflows
19+
Years in quality engineering
AI + QE
Current engineering focus
HITL
Human-in-the-loop by design
MCP
Agent-ready architecture
How I work
Understand the business risk
Start with what can fail, who is affected and what evidence is needed.
Design for testability and control
Make system state, AI confidence, approvals, logs and interfaces observable.
Automate the right things
Use APIs, Playwright, CI/CD and reusable patterns where automation improves feedback.
Keep humans in high-impact decisions
AI can accelerate work without silently inheriting authority it should not have.
About
Leadership experience, backed by hands-on engineering.
19+ years across quality engineering, test leadership, delivery governance, automation and enterprise transformation, including complex integration and supply-chain platforms.
My current focus is the intersection of AI and quality engineering: designing AI-assisted workflows with confidence scoring, risk assessment, human approval, auditability and explicit test controls.
This site is my engineering lab. I use it to turn ideas into working demonstrations, learning modules, governance patterns and reusable test assets rather than presenting a traditional online CV.
Current focus
Where AI engineering and quality engineering meet.
The interesting problem is no longer whether AI can generate an answer. It is whether the surrounding system can make that answer useful, testable, explainable and safe enough for the business context.
Applied AI Engineering
Design AI workflows around grounding, confidence, risk, safe fallback, human approval and auditable action.
AI Quality & Governance
Evaluate behaviour, hallucination risk, prompt changes, model uncertainty and control effectiveness, not just whether the API responded.
Modern Test Automation
Build maintainable Playwright and API automation around business outcomes, deterministic state and CI feedback.
Enterprise Quality Strategy
Connect functional, integration, automation, data and release evidence across complex delivery programmes.
Observability & Release Confidence
Use test evidence and production signals together. A green pipeline is not proof that a system is healthy in production.
MCP & Agent-ready Design
Shape business capabilities as controlled tools so future agents can act through explicit permissions and auditable interfaces.
Capabilities
Engineering breadth with a quality core
Quality Leadership
- Test Strategy & Governance
- Risk-Based Testing
- Delivery Assurance
- QA Leadership
- Release Readiness
Automation & APIs
- Playwright
- Selenium
- Cypress
- Rest Assured
- TOSCA
- API & Contract Testing
Enterprise Engineering
- SAP WMS / TMS / EWM
- Integration Testing
- CI/CD Quality Gates
- Observability
- Test Data Strategy
Applied AI
- AI Workflow Design
- Prompt Governance
- Human-in-the-loop
- AI Evaluation
- RAG / Grounding Concepts
- MCP-ready Tools
Ideas from the intersection of AI, testing and engineering.
Practical observations on AI engineering, quality strategy, automation, APIs, governance and what changes when software systems become increasingly AI-assisted.
API Testing
Quality EngineeringAPI Testing Beyond Status Codes: Testing the System Contract
Why meaningful API testing goes far beyond checking 200 responses and must validate contracts, business rules, state transitions and failure behaviour.
Production Quality
ObservabilityTests Passed. Now Debug Production.
Passing tests are only one source of evidence. Production observability, telemetry and runtime behaviour are equally important to release confidence.
AI & Quality Engineering
AI EngineeringAI-Generated Code Changes the QA Trust Model
When software can be generated faster than humans can validate it, quality engineering must move from execution volume towards evidence, risk and trust.
AI Governance
AI GovernanceAI Agents, Human Control and Governance
Agentic AI becomes useful when capability is matched with permissions, risk controls, human oversight and auditability.
Learn by making the decision.
Short, practical labs that teach the judgement behind AI governance, browser automation and API quality. No passive slide deck pretending to be learning.
Interactive AI learning
AI Workflow & Governance Lab
Work through confidence, risk, grounding and human-approval decisions using realistic business AI scenarios.
Interactive automation
Playwright Test Automation Lab
Practice selectors, assertions, test design and reliability decisions without turning automation into a record-and-playback exercise.
Interactive API quality
API Testing Beyond Status Codes
Test contracts, negative paths, state transitions and business invariants instead of stopping at HTTP 200.
Small tools that solve real everyday problems.
The portfolio is not only about reading and demonstrations. These free browser-based utilities are practical tools people can actually use. More engineering and productivity utilities can be added here over time without turning the site into a collection of gimmicks.
Document Utility
Word to PDF
Convert Word documents into clean PDF files directly from the browser. A simple utility for assignments, reports, CVs, business documents and everyday document sharing.
Document Utility
PDF to Word
Turn PDF documents into editable Word files when you need to reuse, revise or work with document content instead of starting again from scratch.
AI EventOps Assistant
A practical demonstration of how AI can improve a business workflow without being allowed to silently make every decision.
Grounded AI Drafts
AI assists with customer enquiries using workflow context rather than operating as an isolated chatbot.
Human Approval
High-impact output remains reviewable before action, with confidence and risk visible to the user.
Auditability
Prompt context, AI output, decision signals and human actions can be captured as evidence.
Workflow, not Chat
AI is embedded into enquiry, approval, content and lead-management tasks with clear business state.
Build portfolio
Working ideas, patterns and engineering demonstrations
Applied AI Workflow
AI EventOps Assistant
An event-operations demonstration where AI classifies enquiries, drafts grounded responses and generates content while confidence, risk, approval and audit controls remain visible.
Learning by Doing
Interactive Engineering Learning Lab
Scenario-based learning for AI governance, Playwright automation and API testing. Each module asks the learner to make an engineering decision and explains the trade-off.
Responsible AI Engineering
AI Governance & Evaluation Patterns
Reusable patterns for confidence scoring, prompt risk, safe fallback, human approval, auditability and testing AI behaviour before an action reaches production.
Delivery & Test Leadership
Enterprise Quality Engineering
Quality strategy for integrated enterprise systems, combining risk-based testing, automation, API validation, release evidence and clear quality signals for delivery teams.
Education & development
Still learning. Deliberately.
Technical experience is strongest when it is combined with business judgement, communication and an understanding of how organisations actually make decisions.
Master of Management
In progress
Second degree focused on management, finance, project delivery, research and the wider New Zealand business environment.
Continuous AI & Engineering Learning
Ongoing
Hands-on study through working prototypes, AI governance experiments, test automation, API quality, prompt evaluation and agent-ready architecture.
Credentials
Professional certifications
ISTQB Certified Test Manager
ISTQB
AWS Certified Cloud Practitioner
Amazon Web Services
Certified ScrumMaster (CSM)
Scrum Alliance
Connect
Talk engineering, quality, AI or practical delivery.
I use this site to share working ideas, experiments and lessons from quality engineering and applied AI.