5# Patrick Thompson (Atlassian, Iteratively, Amplitude, Clarify) on Why Clean Data Matters More in the AI Era, The Difference Between Using AI as a Tool vs a Crutch, and Building the Muscle of Data-Informed Decision Making

What happens when AI meets bad data? Patrick Thompson has been building and using data tools for over 15 years. He started in growth at Atlassian, then co-founded Iteratively-a data quality platform acquired by Amplitude in 2021-where he became Director of Product. Patrick knows what it takes to build data layers, event pipelines, semantic layers, and quality monitoring systems. He knows what breaks when instrumentation goes wrong. In this episode, we explore how AI is lowering the floor for analysis while raising the bar for what makes analysts valuable. Patrick shares why natural language queries are changing user expectations overnight, why memory and context remain the hardest problems for AI to solve, and the difference between using AI as a tool versus a crutch. We dig into why gut-checking analysis is becoming a critical skill, and what Patrick tells people who ask if their kids should still study software engineering. All episodes on our website: www.ask-y.ai/knowledge-distillation-podcast Learn more about ASK-Y: www.ask-y.ai