Formerly known as Wikibon

The Next Frontiers of AI

with Scott Hebner

About the podcast

AI is still in its infancy, but innovation cycles and the pursuit of high-value ROI are advancing at warp speed. The ability to keep up will determine who leads, who lags, and who fails.
Join theCUBE Research principal analyst Scott Hebner and industry pioneers and experts to explore the latest advancements shaping the future of AI and how to prepare today.

episodes

277 | Breaking Analysis | How Dell Is Riding the AI Wave While Serving Its Massive Installed Base

Dell’s founder-led business is one of the most remarkable and under appreciated stories in tech. Dell Technologies is not particularly sexy, nor does it put forth an earth- shattering vision that bends the mind. Yet it’s a company that has consistently figured out how to ride successive waves without becoming driftwood. And like Hyman Roth of Godfather fame, Michael Dell always seems to make money for his partners. Unlike Roth, Mr. Dell is not a gangster, rather he’s a gentleman that literally wrote the book on how to play nice and win.

In this Breaking Analysis and ahead of DTW 2025, we examine the question, how will Dell capture the explosive AI opportunity, while transitioning the millions of servers, arrays, and PCs it already has in the field to this new AI era?

Agentic AI – Why Architecture Matters

In this episode of the Next Frontiers of AI, we delve into the array of new technologies fueling Agentic AI and why architecture matters more than ever. I am joined by George Gilbert, the principal analyst at theCUBE Research, who covers data platforms, intelligent apps, and agentic frameworks, to dissect the approaches that industry pioneers are taking. As enterprises seek to harness AI’s full potential, the focus shifts from GenAI and LLMs to sophisticated AI agents capable of autonomous decision-making and continuous learning. We’ll share our insights about the importance of building a multi-layered architecture of AI agents.

Join us as we explore the future of AI agents and their role in enhancing workflows and driving innovation in enterprise technology. We will discuss how agentic AI fundamentally changes the nature of what software can do and how it is built. It is a must-watch conversation for anyone just getting started with agentic AI.

A Blueprint for Scaling a New Agentic AI Business

What does it take to build — and rapidly scale — a successful company in the era of Agentic AI?  In this episode, we explore that question with Haoyu Zha, the Y-Combinator founder of HOAi, a fast-growing startup harnessing AI agents as digital workers to transform how homeowner associations (HOAs) operate, create value, and engage their communities.  Founded in 2023, it turned real-world frustrations into an AI solution now adopted by major HOAs such as EJF Real Estate Services, Tyco Property Management, and CAMCO.

With the Agentic AI market projected to grow by nearly 45% CAGR through 2030, HOAi offers a rare case study on how to capitalize early on a breakout category. Their platform enables AI agents and human supervisors to partner, speeding up workflows and improving decision-making, making their solution fundamentally different from traditional business automation solutions.

Whether you’re a founder, investor, or tech strategist, this is your front-row seat to the blueprint for scaling a business in one of AI’s fastest-growing frontiers.

The Role of AppDev SDLC Platforms in the Era of Agentic AI

As enterprises rapidly embrace AI agents and agentic systems to revolutionize decision-making and automation, the question arises: Are Software Development Lifecycle (SDLC) solutions critical to the future of Agentic AI? 

As Agentic AI increasingly becomes central to business innovation, understanding how Software Development Lifecycle (SDLC) platforms intersect with AI development is becoming mission-critical for business and technology leaders. This market brief, informed by discussions with industry expert Paul Nashawaty on theCUBE Research’s “Next Frontiers of AI” podcast, explores the significance of SDLC methodologies within AI workflows, highlights potential challenges, and examines how software developer roles adapt to widespread AI adoption. We also explore the evolving role of software developers in the era of AI.

History’s Guide To The Future Of AI

“In episode #8 of the Next Frontiers of AI Podcast, I’m joined by Irving Wladawsky-Berger—MIT research affiliate, legendary IBM executive, and influential technology innovator. We explore how 50 years of transformative tech provides valuable insights for AI’s future. Drawing from Irving’s experiences shaping mainframes, PCs, client-server systems, e-business, cloud, IoT, and AI, we ask: are we watching the same movie again with new characters? Tune in!”

The Anatomy of a Decision-Making Agent

In this episode of the Next Frontiers of AI Podcast, I go solo to address an array of questions I have received about how to build decision intelligence capabilities in AI Agents and agentic systems.  As the market quickly realizes, generative AI and LLMs are insufficient to fuel these AI Agents, and businesses must build an extended ecosystem of specialized AI models. You’ll learn my point-of-view, which has been informed by dozens of AI experts and pioneering companies. I am eager to hear your views!

Create Resilient Supply Chains with Causal AI

In the latest episode of the Next Frontiers of AI Podcast, hear from Ishansh Gupta, the lead data scientist for quality management at BMW Group. We discuss how advancements in AI are being used to create more resilient and trustworthy supply chains and manufacturing processes.

You’ll also learn more about the power of Causal AI, why Ishansh became an early Ph.D. in the rapidly expanding field, how he earned his management’s trust, and how he is now nurturing the next generation of AI and data science talent. 
 

AI That Knows Why

In this episode of the Next Frontiers of AI Podcast, I am joined by Stuart Frost, the CEO and founder of Geminos. We discuss the future of AI-powered business decision-making, which understands why outcomes occur. You’ll learn how this industry pioneer has delivered next-generation AI platforms that incorporate new innovations in Causal Knowledge Graphs. By integrating causal relationships, Causal Knowledge Graphs transform knowledge graphs from passive repositories into dynamic, self-reinforcing systems that provide a foundation for more intelligent decision-making AI agents.

Next-Generation AI in Financial Services

n this episode of the Next Frontiers of AI Podcast, I am joined by Jayeeta Putatunda, the director of the AI Center of Excellence at the Fitch Ratings, to discuss the unique needs of financial services organizations and how institutions are addressing the limitations of today’s AI. You’ll learn about the power of advanced RAG frameworks, agent-based architectures, and knowledge graphs and how Causal AI combined with RAG represents the next frontier for actionable, interpretable, and reliable AI decision-making.

Making AI Decisions Explainable

In this episode of the Next Frontiers of AI Podcast, I am joined by Marc Le Maitre, the CTO of Scanbuy, to discuss how his organization achieved a 10x ROI in digital advertising campaigns by creating fully explainable and transparent AI models through the emerging innovation of causal AI. Listen in and discover why Scanbuy is “flying their flag on Causal AI” to transform the world of programmatic advertising. You’ll also learn why causal AI will become a critical component in future Agentic AI systems and is rapidly being democratized for the masses to achieve similar business outcomes.

The Ladder to Agentic AI

The AI landscape is evolving fast, and 2025 is shaping up to be the year of Agentic AI—where AI moves beyond task automation and prediction to goal-driven decision-making. But here’s the challenge: 90% of enterprises want to embark on this journey, yet only one in three know where to start.

On the latest Next Frontiers of AI podcast, we broke down the roadmap to Agentic AI adoption with a simple framework—the Ladder to Agentic AI

#1 – Predictions for AI in 2025

In this first episode of The Next Frontiers of AI Podcast, I am joined by my industry colleague Tim Sanders, VP of Research Insights at G2, to debate theCUBE Research’s predictions for AI in 2025.   We begin 2025 grounded in the consensus that will see the rise of agentic AI. In our predictions, we won’t restate that widely held belief; instead, we will focus on what will shape Agentic AI. We foresee a year of advancements that will tackle various real-world barriers to AI adoption and elevate the playing field for enterprises to achieve higher ROI use cases. Join us for this informative conversation, and chime in to let us know what YOU think!

The On-Premises AI Challenge for Startups

Today’s AI startups are overly reliant on public clouds and risk missing the opportunity to bring AI to data that resides on-premises. Organizations increasingly want to bring intelligence to their proprietary data that resides on-prem, to do training and inference under their own control. Startups’ primary route to market is either through hyperscaler marketplaces, which typically de-emphasize on-prem deployments, or via direct sources. When going direct, startups lack the credibility and go to market breadth to scale efficiently. As such we believe an opportunity exists for startups to partner with infrastructure leaders that have a strong on-premises installed base and both the talent and go to market expertise to penetrate traditional enterprises. 

From Youtube

In this episode, we delve into the array of new technologies fueling Agentic AI and why architecture matters more than ever. I am joined by  George Gilbert, the principal analyst at theCUBE Research, who covers data platforms, intelligent apps, and agentic frameworks, to decompose the approaches that industry pioneers are taking.  As enterprises seek to harness AI’s full potential, the focus shifts from GenAI and LLMs to sophisticated AI agents capable of autonomous decision-making and continuous learning. We’ll share our learnings about the importance of building a multi-layered architecture of AI agents, highlighting key components such as: • Perception Layer: Gathering contextual information through specialized modules. • Cognitive Core: Integrating logical reasoning and goal-setting for informed decisions. • Execution Framework: Selecting optimal actions and integrating external tools. • Learning Loop System: Utilizing feedback mechanisms to foster continuous improvement. • Inter-agent Communications: Enabling AI agents to collaborate intelligently. Join us as we explore the future of AI agents and their role in enhancing workflows and driving innovation in enterprise technology. We will discuss how agentic AI is fundamentally changing the nature of what software can do and how it's built and evolved. This is a must-watch conversation for anyone just getting started with agentic AI.


00:00 - Intro
00:06 - Exploring the Future of AI: From Frontiers to Insights
02:40 - Interview with Marc Benioff Insights
04:57 - Architecting AI: Foundations and Real-World Applications
09:16 - Emerging Technologies in AI
11:54 - Understanding Agentic RAG and Reasoning
15:01 - Future of AI Agents and Their Capabilities
18:58 - The Importance of a Harmonization Layer
28:11 - Rethinking Software with AI
31:29 - The Ladder to Agentic AI
34:32 - Advice for Getting Started with AI
37:31 - Conclusion and Final Thoughts

In this episode, we delve into the array of new technologies fueling Agentic AI and why architecture matters more than ever. I am joined by George Gilbert, the principal analyst at theCUBE Research, who covers data platforms, intelligent apps, and agentic frameworks, to decompose the approaches that industry pioneers are taking. As enterprises seek to harness AI’s full potential, the focus shifts from GenAI and LLMs to sophisticated AI agents capable of autonomous decision-making and continuous learning. We’ll share our learnings about the importance of building a multi-layered architecture of AI agents, highlighting key components such as: • Perception Layer: Gathering contextual information through specialized modules. • Cognitive Core: Integrating logical reasoning and goal-setting for informed decisions. • Execution Framework: Selecting optimal actions and integrating external tools. • Learning Loop System: Utilizing feedback mechanisms to foster continuous improvement. • Inter-agent Communications: Enabling AI agents to collaborate intelligently. Join us as we explore the future of AI agents and their role in enhancing workflows and driving innovation in enterprise technology. We will discuss how agentic AI is fundamentally changing the nature of what software can do and how it's built and evolved. This is a must-watch conversation for anyone just getting started with agentic AI.

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YouTube Video UExlbmgyMTNsbG1jWVFSbm5aWUpBRkNuczNCYUtrQTdkdi45ODRDNTg0QjA4NkFBNkQy

11. Agentic AI Architecture Matters

SiliconANGLE theCUBE May 8, 2025 10:24 am

8. History's Guide To The Future of AI

SiliconANGLE theCUBE March 21, 2025 3:45 pm

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