271 | Breaking Analysis: Mapping Jensen’s World – Forecasting AI in Cloud, Enterprise, and Robotics

We are in the midst of a fundamental transformation of computing architectures. We’re moving from a world where we create data, store it, retrieve it, harmonize it and present it so that we can make better decisions, to a world that creates content from knowledge using tokens as a new unit of value; and increasingly takes action in real time with or without human intervention, driving unprecedented increases in value. What this means is every part of the computing stack, from silicon, infrastructure, security, middleware, development tools, applications and even services, is changing. As with other waves in computing, consumer adoption leads us up the innovation curve where the value is clear, the volume is high and the velocity is accelerated, leading to lower costs and eventual adoption into and disruption of enterprise applications. Importantly, to do this work on today’s data center infrastructure would be 10X more expensive, trending toward 100X by the end of the decade. As such, virtually everything is going to move to this new model of computing. 

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.

270 | Breaking Analysis | Security Do-Over…How Palo Alto Networks Sees the Reset

Automation generally and AI specifically, render today’s cybersecurity stacks ineffective. Previously, stopping 99% of attacks and leaving the 1% for armed human hunters to deal with was, while not ideal, at least feasible. With AI, that all goes away because adversaries can scale phishing and other attacks at unprecedented rates, which overwhelms the ability of humans. This creates a wider gap between exfiltration times, which are shrinking, and mean time to remediation, giving even greater advantage to attackers. As such, the only way to fight AI is with AI. Moreover, the ever expanding number of tools in an organization’s security stack continues to exacerbate the problem. According to Palo Alto Networks, the answer is a complete makeover of your cybersecurity stack where consolidating multiple tools into a single platform and gaining comprehensive access to the right data, simplifies security operations and enables AI to operate in real time.

Cloud Native Application Protection: a WINning Strategy

In the modern cloud era, security is no longer a standalone effort; it requires seamless collaboration across ecosystems. We explore how Wiz, a leading cloud-native application protection platform (CNAPP) that is in the process of being acquired by Alphabet / Google, has strategically built a thriving partner ecosystem through its Wiz Integration Network (WIN). We discuss Wiz’s platform and organizations’ growing challenges in securing multicloud environments, from visibility gaps and alert fatigue to shifting ownership models, dive deep into Wiz’s unique approach to technical partnerships, highlighting why the Tech Partnerships function resides within the Product organization and how the WIN program drives co-build, co-market, and co-value outcomes. With over 300 partners and 150+ certified integrations, WIN exemplifies what a modern, open, customer-centric partnership model looks like.

FinOps + CloudOps = The Future of Cloud Governance

Discover how FinOps and CloudOps are merging to enable proactive cloud governance, cost control, and automation. Learn why unified cloud operations are critical for AI and multicloud success.

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 State of DevOps and AI’s Growing Influence

AI is transforming DevOps, enhancing automation, security, and developer productivity. Learn how AI-driven DevOps impacts software delivery, stability, and compliance.

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!

269 | Breaking Analysis | The New Age of Analyst Relations in Tech

The analyst relations (AR) function is undergoing a fundamental transformation. Once dominated by a handful of large research houses, such as Gartner, IDC and Forrester, the market now features a spectrum of independent analysts and influencers. The fast-paced nature of the tech industry, its speed of change, the relentless competition and ubiquity of technology, make […]