Insights

What if showing up was enough, because the rest is already built for you?

Learn how to evaluate LLM quality and limitations using a range of testing techniques, from unit and regression testing to bias, adversarial and explainability testing.

Identify the subtle signs of "implementation-driven design" and discover practical strategies for testers and tech leads to actively defend and restore user-centric product intent.

Understand why test data management is a more complex and impactful challenge than test automation itself, and how to address it through better ownership, tooling, and data practices.

What would change if the work you are proudest of was actually seen?

A one-word shift that opens up quality thinking

Every question you ask during testing is the seed of the next one.

Could borrowing a concept from cognitive science change the way we think about quality engineering?

AI amplifies the good and the bad, so where should your team start?

Why does mentorship work best human to human, even in an age of AI?

When has chasing automation coverage cost you more in maintenance than it gave back?

There's a skill in spotting which of your activities are genuinely high value

The whole team can interactively explore the vulnerabilities worth probing. Before an attacker does.

The whole team can interactively explore the numbers worth testing

Most teams think they've handled dates. Most teams are wrong.

A Claude Skill to copy or spark inspiration

The tool that makes your testing easier might be the same one cutting you off from the team that builds the product.

What if the tools we use to stay on top of things are quietly making us worse at our jobs?

The five risk categories to navigate before, during, and after an AI migration.

When the implementation of AI leads to lower quality