ai-testing
AI fairness is not a single number. Demographic parity, equalized odds, and calibration are distinct mathematical properties that are provably incompatible under realistic conditions. This guide explains what each metric actually measures, when to use which, how to compute them with Fairlearn and custom code, and what EU AI Act
ai-testing
AI safety evaluation is not a checkbox — it is an engineering discipline with concrete tools, measurable benchmarks, and adversarial test suites. This guide covers the NIST AI Risk Management Framework as an organizational lens, red-teaming LLMs with Garak and manual probing, adversarial robustness testing with the Adversarial Robustness Toolbox,
Playwright
Playwright v1.50+ ships three first-party AI agents — Planner, Generator, and Healer — that together automate the entire test lifecycle from exploration to repair. They are built into core Playwright, not plugins, and they change how developers write and maintain E2E tests. Key Takeaways Planner explores your app and produces
ai-testing
Self-healing tests use AI to automatically update broken selectors when your UI changes, without you touching the test code. They eliminate a real maintenance burden — but they are not magic. They fix selector failures; they cannot fix tests where the feature behavior itself has changed. Key Takeaways Self-healing
engineering-managers
Big tech senior engineers cost ~$350,000/yr total comp and ship roughly 375 PRs per year. AI-assisted code review runs $15–25 per PR. That's $7,500/yr per engineer — 2% of what you're already paying them. If the review catches one production bug