Risk-based testing strategy across code, data, AI, and production.
How to validate data pipelines and migrations so a successful job run also means the business data is correct.
A hands-on start with Microsoft Playwright for a small set of critical, maintainable browser test journeys.
A layered test architecture that proves risk at the lowest effective level, from static checks to selective end-to-end tests.
A practical, risk-driven wiki for testing software, data, AI, security, performance, and production releases.
Tying performance, security, and resilience testing to realistic workloads, explicit objectives, and observable production behavior.
How to identify critical business journeys, tier risk, and drive release decisions from evidence rather than pass rate alone.
How to test a full AI/RAG system — retrieval, prompts, guardrails, and evaluation — not just the model's final answer.
Testing builds confidence by checking risks at the cheapest useful level: static checks, focused unit tests, integration and contract tests, a few critical end-to-end journeys, and production signals.