In this captivating episode of 'How I Met Your Data Today,' hosts Anjali Bansal and Karen Meppen interview fellow podcaster Jamie McCusker, the self-proclaimed Opinionated Ontologist. Jamie shares the journey into the world of ontology development. McCusker sheds light on the importance of bringing experience and perspective to data modeling, challenging the notion of being an impartial mediator.

Jamie delves into academic and professional experiences, highlighting work with methodologies like protege, RDF graphs, and OWL.

As she recounts her involvement in large projects, including a pharmaceutical data initiative, Jamie explains the complexities and significant benefits of ontologies. She argues against the common misconceptions of AI and advocates for a realistic understanding of generative AI's capabilities.

Packed with insights, practical advice, and a humor-filled recount of her professional journey, this episode reveals why ontologies are powerful tools for organizing and understanding data, making a compelling case for their broader application.

In this episode of How I Met Your Data, Christina Hois, a data leader with over 30 years in financial services, joins Anjali and Junaid to explore why data challenges rarely stem from technology — and almost always come down to people.

Christina shares why breaking down cultural silos, building stakeholder trust, and prioritizing data tied to real business outcomes matter more than deploying new tools. The conversation highlights the critical role of emotional intelligence, credibility, and collaboration in making data governance actually work.

The takeaway is clear: technology enables scale, but trust and teamwork determine success.

In this episode of How I Met Your Data: The Prompt, Anjali and Karen dig into one of the fastest-emerging patterns in development today: vibe coding - the practice of describing what you want and letting an LLM generate the code. It’s new. It’s evolving. And right now, it’s causing as much frustration as it is excitement.

Karen breaks down what vibe coding actually looks like in practice: developers prompting AI to produce entire features or files, navigating the wildly different “personalities” of today’s LLMs, and learning how to guide systems that might generate brilliant structure… or unintended chaos. Together, they talk through the real friction points - overly eager model behavior, unexpected file changes, incomplete suggestions, and the creeping loss of hands-on debugging skills that used to tie engineers closer to their code.

But underneath the surface is a bigger enterprise theme. The rise of vibe coding speaks to deeper issues: end users who still aren’t getting what they need, bottlenecks in IT and data teams, and the rapid expansion of citizen development as people search for faster paths to outcomes. Anjali and Karen unpack the operational and governance implications, from maintainability and handoff challenges to compliance blind spots and the need for standards that can coexist with AI-assisted creation.

They also dive into where AI does shine today - those repetitive, operational workflows that quietly save teams hours - and why focusing on value, ownership, and workflow design matters far more than chasing the next flashy LLM demo.

This episode is an honest, grounded look at how AI-assisted development is taking shape: what’s promising, what’s painful, and what it means for teams trying to build responsibly, collaboratively, and at scale.