AI & Data Testing + Create a Coaching Relationship with AI

Hamish Watson — dual Microsoft MVP (Data Platform and AI), technologist, and community educator — opened the evening with a compelling argument: you can't have good AI without good data. The relationship is intrinsic and non-negotiable.

Drawing on a vivid example from 2017, when he spent weeks cleaning and testing data for a University of Canterbury machine learning project, Hamish demonstrated that returning to the same dataset in 2024 with AI assistance reduced that work to minutes. The exponential improvement wasn't incremental — it was a category shift.

His talk tackled one of the persistent pain points in data engineering: testing production data. Traditional approaches — copying production, restoring as test, then scrambling with data masking for PII compliance — are cumbersome and error-prone. AI changes this by enabling smarter data generation, automated pattern identification, bias reduction, and practical test-driven development (TDD) workflows for data pipelines.

Hamish made an impassioned case for TDD in data — writing tests before writing code — an approach he's championed since 2018. His live demo showed how AI can now scaffold this process, reducing the friction that has historically made data testing so difficult.

His core message: "It's not going to be AI that replaces us. It's going to be a person who uses AI." — a framing that landed well with the technically-minded crowd.

Note: The live meetup livestream did not capture Caelan's presentation. The recording below is an expanded replay of the same material, covering additional depth and practical exercises.

Caelan Huntress — AI educator, public speaker, and founder of the AI Coaching Academy — explored how to move beyond treating AI as a search engine and instead build a genuine coaching relationship with it.

He introduced a spectrum of AI adoption: from dissidents (actively resistant, eventually obsolete) through novices and explorers to builders and champions — people who have achieved a symbiosis with AI and couldn't conceive of working without it. Champions use AI all day every day; builders an hour a day; explorers once or twice a week.

The session introduced the concept of the coaching container — a structured context you create for your AI that enables it to coach you effectively. This involves feeding personality profiles, personalization data, and your specific goals into the model so it can give targeted, meaningful feedback rather than generic responses.

Practical outcomes from Caelan's AI training workshops: participants reported a 65% increase in productivity and a 75% improvement in strategic decision-making. The key driver? Hands-on practice — not just reading about AI, but getting behind the wheel.

He closed with a challenge to the audience: identify where you sit on the adoption spectrum, and ask yourself what it would take to move one level higher.