Beyond the Black Box: Building Transparent, Trustworthy Multi-Agent AI
Explore how to build trustworthy multi-agent AI systems. AI’s next frontier will not be defined by bigger models, but by trust. As enterprises push agentic AI into higher-stakes workflows, the question is no longer what AI can generate—it is whether its decisions can be justified and defended. With only 49% of enterprises reporting high trust in AI outcomes and just 29% having formal trust frameworks in place, the gap is clear. In this episode, Scott Hebner and Openstream.ai’s Magnus Revang explore why transparent, auditable multiagent systems—not black-box models—are the foundation for enterprise-grade AI.
Agentic AI Governance Becomes the Enterprise Differentiator
Why agentic AI governance, data quality, and API-first architecture determine enterprise success beyond experimentation.
Reskilling the Network Workforce for an AI-Driven Era: Part Two
Aligning Business Leadership, Governance, and Workforce Transformation In Part One of this series, we explored how AI and generational shifts in the workforce are redefining the technical skill requirements for network engineers. But the impact of AI extends well beyond technical domains. In this second installment, the conversation with Par Merat and Ryan Rose turns […]
Reskilling the Network Workforce for an AI-Driven Era: Part One
From Talent Pressure to Applied AI Skills Enterprise networking is entering a period of structural transition. Artificial intelligence is reshaping how networks are designed, operated, and secured at the very moment when a significant portion of the industry’s most experienced engineers is approaching retirement. This convergence creates a dual inflection point: a generational workforce shift […]
307 | Breaking Analysis | theCUBE Research 2026 Predictions: The year of enterprise ROI
Observers commonly refer to AI as still in the early innings. The reality is AI is much further along than most marketers acknowledge. In 2012, AlexNet was a watershed deep learning moment when massive and freely available Internet datasets met Nvidia GPUs. This is what truly kicked off the modern AI era, leading to further breakthroughs like generative adversarial networks. In 2017, Google researchers introduced the transformer architecture to the world followed by the scaling laws. Then of course, the mass adoption began with ChatGPT setting off the current AI arms race.
Fourteen years into the modern AI era, our research indicates AI is maturing rapidly. The data suggests we are entering the Enterprise Productivity phase; where we move beyond the novelty of RAG-based chatbots and agentic experimentation. Where 2026 will be remembered as the year that kicked off decades of enterprise AI value creation. We can’t promise that it won’t be messy. White collar job pressures, AI safety, new security and governance threats all loom. But the AI train isn’t stopping and enterprises that don’t get on board risk obsolescence.
2026 Enterprise AI Predictions
It’s time for theCUBE Research’s 2026 Enterprise AI predictions. Join Scott Hebner and Christophe Bertrand as they give their 2026 Enterprise AI predictions and pressure-test what changed in 2025. The enterprise AI market is now operating on innovation cycles measured in quarters, not years, and the competitive gap is compounding: organizations that learn, instrument, and govern faster will […]
Ericsson Unveils Cradlepoint R2400: A Modular, AI-Ready 5G Platform for Mission-Critical Mobility
Ericsson has introduced the Cradlepoint R2400, a ruggedized in-vehicle 5G router designed for public safety, mass transit, and fleet operations. The platform combines an industry-first Dual SIM/Dual Standby (DSDS) architecture on a single modem, support for up to five simultaneous 5G Standalone connections plus low-Earth-orbit (LEO) satellite links, centimeter-level positioning via RTK and dead reckoning, […]
Open Source at Scale Requires Stewardship, Not Assumptions
Ingress NGINX EOL exposes the need for open source lifecycle stewardship, governance, and compliance planning at scale.
306 | Breaking Analysis | Cloud earnings bring capex clarity, concern and confusion
This winter’s 2026 hyperscale earnings prints from Meta, Microsoft, Alphabet and Amazon made it quite clear that CapEx is accelerating. Combined these four firms will spend more than $615B in CapEX this year, an increase of approximately 70% over what was already considered an inflated 2025. Despite strong fundamental AI and general purpose computing demand, this news caused significant concern for market watchers because the aggressive spending has murky payoffs. Coupled with the Anthropic-infused SaaS attack, investors took stocks down for most of the week, including Nvidia. Confusingly, much of the CapEx spend is going to Nvidia – perhaps as much as 60% of the AI portion of the CapEX will go to that company – a point investors seemed to overlook. Notably, the market is bouncing back today (Friday) after this week’s earlier rout.