LLMs are optimized to sound convincing—not to know when they’re wrong. In this episode, Deanna Emery breaks down why hallucinations are fundamentally tied to how language models work, why confidence is often disconnected from correctness, and how better evaluation strategies can make AI systems more reliable in production. We also get into uncertainty, semantic reasoning, and what humans still do better than models.

00:00 — Why LLMs hallucinate confidently
09:00 — The limits of current eval systems
18:00 — Why uncertainty matters in AI
27:00 — Semantic reasoning vs memorization
38:00 — What humans still do better than models

The biggest risk in AI isn’t wrong answers. It’s wrong answers delivered with confidence.

Building a great AI team takes more than hiring smart people. In this episode, Brooke Wenig breaks down how Databricks built the AI FDE organization, why culture compounds faster than technical skill, and what separates high-trust engineering teams from teams that slowly degrade over time. We also get into mentoring, hiring in the age of AI coding tools, and why software engineering fundamentals matter more than ever.

00:00 — How Databricks built the AI FDE team
08:00 — AI cheating in technical interviews
19:00 — Why culture degrades as teams scale
31:00 — Building a team brand around specialists
43:00 — What skills matter most in the AI era

Great AI teams aren’t built through rules. They’re built through people who reinforce the right standards every day.

Most AI startups optimize speed, automation, or revenue. Sol built one to stop people from emotionally destroying each other. After a brutal divorce and years trapped inside high-conflict co-parenting, he realized the real problem wasn’t logistics, it was emotional escalation through constant communication. BestInterest uses AI to filter manipulative, hostile, and triggering messages before they reach the other parent, turning AI into a psychological buffer instead of a chatbot. AI has the potential to bridge challenging social gaps. While there is a lot of fear around this capability, this case study for navigating challenging parenting relationships showcases how unbiased AI personas can mitigate these problems.

Chapters

• 00:00 The Origin Story of Best Interest
• 06:06 AI as a Mediator in Co-Parenting
• 12:57 Designing for Impersonal yet Supportive Nature
• 18:00 The Best Interest of the Kids
• 22:57 Fine-Tuning Communication Expectations
• 28:10 Product Insight and Differentiation
• 36:52 Passion-Driven Work and Meaningful Impact
• 42:37 AI and Human Communication
• 49:37 AI as an Engine of Peace