Where I’m coming from.

Professional summary

I’m a software testing and automation engineer. Most of my career has lived at the intersection of test architecture, API testing, and CI/CD reliability. The work I’m drawn to now sits at the boundary between human judgment and AI: where agents help write, maintain, or explore tests, but a person still owns the quality decision.

My testing philosophy

Tests exist to communicate quality, not to satisfy a coverage number. The best test strategy is the one a team can actually maintain: API-first where possible, UI where necessary, deterministic when running in CI, expressive when read by a future engineer. Flakiness is a design problem, not a configuration problem.

Why AI plus QA matters

AI is not a replacement for judgment about what to test. It is a force multiplier for the parts of testing that are easy to describe and tedious to do: generating candidate cases, maintaining selectors, summarizing failures, suggesting risk areas. The win is using agents to surface signal faster while the engineer stays accountable for the decision.

What I’m building toward

A practical body of evidence that AI-assisted testing can be both useful and honest about its limits: a universal testing language to bridge frameworks, agentic workflows that help with the slog of test maintenance, and quality dashboards that translate test signals into something a product team can act on.

Current focus areas

• Agentic workflows in software testing, with explicit guardrails and observability.
• API-first automation strategy that scales beyond a few hundred tests.
• Quality signal design for engineering leaders and product owners.
• Tool evaluation for AI coding agents applied to test maintenance.