About this episode

Jeff McMillan discusses the foundational aspects of AI implementation and the importance of high-quality data and governance.

Everyone wants to talk about agents and models. Jeff McMillan, starts where almost nobody else does: the foundation. In this episode, Jeff McMillan, founder of McMillanAI, former Head of Firmwide AI at Morgan Stanley, and advisor on enterprise AI, maps AI as a stack: high-quality accessible data → semantic layer (knowledge graphs, RAG) → control and governance → models → orchestration → applications. The heavy lifting is in the bottom layers. Organizations that skip them can fake it for a handful of agents, but at 150 or 15,000 agents, you need near-100% accessibility and 99%-plus quality, or you’re monitoring chaos you can’t see. Josh and Robb press him on why knowledge management feels unfundable, why tribal institutional knowledge breaks when machines execute without judgment, and why evaluation (golden datasets, custom org evals, regression when models upgrade) is the work builders hate and operators can’t skip. Robb names the trap CTOs are falling into: grinding tokens on feature backlogs that never reach production or revenue. Jeff agrees on the strategic gap — after controlled experimentation, leaders should ask what destroys the business in ten years, not what demo ships…

People in this episode

Hosts: Josh, Robb

Guest: Jeff McMillan

Topics covered

• AI stack
• knowledge management
• enterprise AI
• data governance
• organizational strategy

Keywords

• AI
• data quality
• knowledge graphs
• governance
• enterprise AI
• evaluation
• process mapping

Mentioned in this episode

Organizations: McMillanAI, Morgan Stanley

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