Metadata to Knowledge Graphs: Mapping the Full AI Data Stack, with Sanjeev Mohan, Principal of SanjMo

Data foundations are the real bottleneck for agentic AI, and most teams are governing the wrong layer. In this episode of *AI Radicals*, host Satyen Sangani talks with Sanjeev Mohan, industry analyst and author of *Designing the AI-Driven Data Foundations*, about why AI's biggest promises still rest on unglamorous data fundamentals, and why agents are breaking the old rules of governance. Sanjeev walks through his layered model of metadata, semantics, context, ontology, and knowledge graphs, and the two dig into where data products fit in that stack. They debate whether governance belongs to the agent or the data itself, why deterministic rules must live with the data rather than be re-explained to every model or prompt, and how agentic systems generate entirely new categories of data that nobody has a framework for governing yet.  "There's a concept 100% related to the whole idea of context and data products, and that is governance. Now we are in the realm of AI, which is a very different beast to govern." Listen to this episode to learn: - Why semantics, not storage or compute, is becoming the real moat in the AI stack - Why agentic governance has to cover input, output, and runtime, not just clean data in and clean data out - Why data teams are entering a golden era, shifting from backup-and-restore work to business strategy and reusable data products \-------- “ One definition is that data product is a philosophy. It's not a thing. And what data product says is that when you build your artifact, you build it with the product management best practices. For example, there's a data product owner, it has a version number, and it's backward compatible. It's packaged with SLAs and contracts. So if you are packaging your semantic layer and you're building it using the product management best practices, then that's a data product, very much so.” – Sanjeev Mohan \-------- **Time Stamps** \[01:37] Sanjeev’s book *Designing the AI-Driven Data Foundations* \[03:47] Defining metadata, semantics & context \[07:28] Taxonomy, ontology & knowledge graphs \[10:01] What is a data product? \[20:24] From data governance to agentic governance \[27:30] The context layer debate \[31:32] The future of data people \[38:15] Predictions for the next 90-180 days \[42:50] Closing & key takeaways \-------- **Sponsor** This podcast is presented by Alation. Learn more: \* Subscribe to the newsletter: https://caspianstudios71626.activehosted.com/f/73 \* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/ \* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/ \-------- **Links** Connect with Sanjeev Mohan on LinkedIn: https://www.linkedin.com/in/sanjmo/ *Designing the AI-Driven Data Foundations: Architecture, Principles, and Practice*: https://www.wiley.com/en-us/shop/general-introductory-computer-science/designing-the-ai-driven-data-foundations-architecture-principles-and-practice-p-9781394396665#aboutauthors-section Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.