Smarter AI Models Won't Fix Your Deployment | Maryam Ashoori, VP PM/Eng (IBM, Watsonx)

In this episode, we’re joined by Maryam Ashoori, VP of Product and Engineering at IBM’s Watsonx platform. With a background that includes 2 master's degrees in AI, a PhD in Systems Design Engineering, and named on over 30 patents at IBM, she’s been on the bleeding edge for over a decade. Currently leading the charge on Agentic AI and AI Governance at IBM, Maryam is a bridge between the theoretical frontier of AI and the messy reality of enterprise deployment.

In this episode, Maryam:

• Tells why AI has been stuck in pilot purgatory for longer than expected, and what you need to do today for a successful enterprise deployment
• Calls shenanigans on the “biggest, best model” crowd, and why often a smaller, more focused tool is the right choice
• Explains how to build an agnostic architecture that can handle the realities of an AI world where models advance faster than anybody can keep up

Links

LinkedIn: https://www.linkedin.com/in/mashoori/
IBM: https://www.ibm.com/us-en

Resources

Reinventing SaaS: Zuora's AI Transformation | Karthik Chakkarapani and Shakir Karim (Zuora): https://www.youtube.com/watch?v=gHVxnLikMpQ
Linear’s Secret to Building Powerful AI Products | Nan Yu, Head of Product (Linear): https://www.youtube.com/watch?v=27rGB-6XQJg

Chapters

00:00 Intro
02:18 From ChatGPT hype to enterprise reality: use cases, ROI, and the rise of agents
06:11 Security, accountability & governance: who’s responsible when agents go wrong?
10:37 Risk-based rollout: use-case scoping, Risk Atlas, and guardrails like PII detection
17:10 Observability for agentic workflows
18:21 Why compute optimization matters
22:58 Designing for model agility: abstraction layers, routing, and picking the right model
27:23 Conclusion

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