Episode 230: Kat Obring is Back

The conversation between host Alan Page and returning guest Kat Obring centers on how testers and quality practitioners can make sound decisions when integrating AI tools into their work. Obring, who runs Keto Coaching and focuses on workshops for teams, describes a shift from earlier topics like whole-team quality ownership to current pressures created by generative AI. Both speakers stress that AI amplifies the need for careful judgment rather than replacing it, and they examine the psychological patterns that either help or hinder effective use.

Decision-making patterns under AI pressure
Obring draws on Daniel Kahneman’s distinction between system 1 (fast, automatic responses) and system 2 (slow, deliberate analysis) to explain common reactions to AI. Many teams default to system 1 impulses: either declaring that AI can handle all testing or insisting it cannot be trusted for any task. These reactions bypass the step of defining a desired outcome first. Obring recommends simple reflective sequences—ask, reflect, respond—that move thinking into system 2 territory. The same approach applies when prompting models: stating a narrow goal, specifying acceptable levels of hallucination or rework, and checking results against that goal reduces impulsive acceptance or dismissal of output.