Use the AI Tools Yourself, Then Show Your Colleagues
Kenn So on how AI actually spreads inside a company: use the tools yourself, show a colleague, and try a new one every quarter.
Use AI for the Questions Nobody in the Room Will Ask
Chris Butler of GitHub on using an LLM in decision-making: no stake in the hierarchy, no care about power, and in 2025 about 80 percent junk.
AI Is a Tool for Augmenting People, Not Replacing Them
Sean White on AI as a tool that augments people, owning your own intelligence on premises, and the no surprises rule for wearable data.
An AI Committee Needs Every Department and Real Authority
Isar Meitis on the AI committee: who sits on it, what it decides, and why clear guardrails make people experiment more rather than less.
Judge a Model on Cost and Latency, Not Just Accuracy
Ivan Lee of Datasaur on judging an AI model in production: unit cost first, then latency, then quality, and no single model wins.
Synthetic Data Has a Place, but It Is Not the Bias Panacea
Matt Maccaux of Google Cloud on whether you can generate your way out of biased training data, and why he leans on humans in the loop instead.
Bring the AI to Your Data, Not Your Data to the Cloud
Mark Heynen of Knapsack on why the fix for AI data risk is architectural: run the model where the data already sits instead of uploading it.
Own Your Own Intelligence Before Your Vendor Learns It
Paul Baier of GAI Insights on what a vendor learns about your business while it processes your data, and the steps he tells companies to take first.