Software engineer based in Wellington, New Zealand, focused on production debugging, backend systems, developer tooling, CI/CD reliability, and AI-assisted systems engineering.

I am most useful when a failure is ambiguous, intermittent, crosses multiple layers, or needs stronger evidence than "the patch seems to work". My engineering process is built around reproducibility, root-cause isolation, bounded fixes, and regression verification.

• Java / JVM backend and infrastructure debugging
• TypeScript and Python runtime failures
• concurrency, lifecycle, cache, transport, and resource-ownership bugs
• GitHub Actions, Docker, AWS, Gradle, Playwright, Vitest, and API integrations
• production-style incident reproduction and regression testing
• AI-assisted engineering workflows with explicit evidence gates

copley/paid-debugging-lab is my public debugging storefront and case-study archive. It documents investigations across CI lifecycle failures, concurrency, authentication propagation, serialization, runtime compatibility, browser automation, AWS/CDK, Docker/Buildx, GitHub Actions, pytest/Pydantic, Vitest, Wrangler/Miniflare, and related systems work.

vitest-dev/vitest#11155 fixes a Vitest 5 benchmark project-filter identity regression. The contribution includes reproduction, a bounded TypeScript change, regression coverage for selection/exclusion behaviour, and broad verification. It is currently in review, not presented as merged work.

Last reviewed: 2026-09-16. These are active investigations, not claims of contribution:

• vitest-dev/vitest#11276 — browser mode intentionally constructs interceptorPlugin({ registerWebSocketEvents: false }), but the plugin still exposes a configureServer hook whose body merely returns. Vite 8 detects the forbidden environment hook from the plugin shape before that guard can help; omitting the hook entirely in the disabled case is a small, regression-testable fix.
• vitest-dev/vitest#11281 — project-specific defineCacheKeyGenerator callbacks are registered into one workspace-global generator set, then every generator runs for every environment. Two projects can therefore contribute the same combined cache-key material to a shared module even though their transforms differ.
• actions/runner#4723 — the runner's workflow-permissions model is stale beyond the JSON schema: code-quality and copilot-requests are absent from the schema, the Permissions data model/comparison map, and conversion switch, so synchronization with the GitHub-owned language-services schema needs to cover parsing and policy semantics rather than a one-line schema edit.

The queue is deliberately source-inspected before any public diagnosis is posted. The next useful artifact should be a reproducer, regression test, or bounded patch—not an ownership-only comment.

copley/copley-ai-engineering-harness is a model-independent control plane for directing AI systems through a deterministic engineering lifecycle:

DISCOVERY
→ REPRODUCTION
→ EVIDENCE
→ ROOT CAUSE
→ DESIGN
→ IMPLEMENTATION
→ REGRESSION TESTING
→ STRESS / INTEGRATION TESTING
→ REVIEW
→ VERIFIED RESULT

The objective is not code generation by itself. It is reliable AI-assisted systems engineering with reproducible evidence, adversarial review, and human approval.

netty/netty#17391 investigates bounded TLS wrapping and backpressure behaviour in SslHandler under slow-consumer conditions. The work focuses on queue ownership, writability semantics, direct-memory pressure, and regression coverage rather than a broad behavioural rewrite.

Issue discovery
→ repository and environment setup
→ codebase mapping
→ deterministic reproduction
→ instrumentation and evidence capture
→ hypothesis testing
→ root-cause isolation
→ smallest safe patch
→ regression / stress / integration tests
→ adversarial review
→ upstream PR or production-ready incident package

A useful debugging engagement should leave behind a result another engineer can independently verify: the reproduction, the failure boundary, the root cause, the patch, and the test that prevents recurrence.

For a focused repository failure, CI breakage, runtime bug, or difficult integration problem, start at paid-debugging-lab. Good requests have one repository, one concrete failing behaviour, logs or a reproduction, and a clear expected outcome.