Earley AI Podcast Episode 66: Reengineering Knowledge for the AI Era

In this episode of the Earley AI Podcast, host Seth Earley sits down with industry analyst and advisor Tony Baer, a seasoned expert in data, cloud, and analytics. With decades of experience guiding global tech leaders like AWS and Oracle, Tony brings a nuanced perspective on how knowledge engineering is evolving—and why context is the missing link in many enterprise AI initiatives.

Together, Seth and Tony explore the shift from static data models to dynamic knowledge frameworks, the renewed importance of governance, and how graph databases and generative AI are reshaping enterprise intelligence. This is a conversation packed with hard-earned lessons and actionable insight for data, IT, and transformation leaders aiming to make AI work in the real world.

Key Takeaways:

• Knowledge engineering today is about dynamic, adaptive structures—not static ontologies or rigid models.
• The role of the knowledge engineer is shifting: it’s less about technical mastery and more about bridging data, business, and domain expertise.
• Context is foundational. The five W’s—Who, What, When, Where, Why (and How)—unlock meaningful, actionable intelligence.
• Graph databases and AI are enabling real-time connections across data, turning static information into living knowledge.
• Generative AI delivers the most value when rooted in organizational context. RAG strategies demand clean data and strong information architecture.
• Successful AI initiatives are focused. Start with well-bounded, high-impact processes—avoid boiling the ocean. 
• Core principles from previous data waves still apply. It’s about evolving governance, stewardship, and architecture for the AI era. 
• Sustainable value comes from feedback loops, iteration, and alignment—not silver bullets. 

Tune in to discover how to make AI practical, actionable, and intelligent for your organization.

Quote of the Show: "Just because something is old does not make it wrong. There are a lot of disciplines we've built up over the years—governance, data stewardship—that still matter. The principle was right. We just adapt it and use our learnings from each cycle to become more knowledgeable and proficient." Tony Baer

Links

LinkedIn: https://www.linkedin.com/in/dbinsight/

Website: https://www.dbinsight.io

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