This episode examines CoreWeave's path to a durable ai cloud ahead of Fully Connected. Dave Vellante of SiliconANGLE Media, Inc., co-founder and co-CEO provides a Breaking Analysis preview. Vellante draws on theCUBE Research and proprietary interviews to evaluate CoreWeave's enterprise traction and market positioning.Vellante synthesizes 13 in-depth interviews and public financial disclosures to assess GPU scarcity, inference growth, model training demand, hyperscaler relationships and compliance tooling. They evaluate operating quality, pricing strategies and product expansion as factors to convert availability advantages into a durable AI cloud.Key takeaways include that GPU scarcity drives initial adoption but performance, cost and operating experience retain customers, according to Vellante. theCUBE Research finds inference growth stacking on model training and enterprises continuing to retain hyperscalers for broader application estates. Analysts identify gaps in compliance tooling, pilot-to-production conversion and the need for flexible pricing and financing as critical action items for CoreWeave ahead of Fully Connected. The analysis highlights implications for AI infrastructure, enterprise cloud strategy and vendor differentiation.

What happens when Salesforce creates more value outside its own interface? In the latest Breaking Analysis, theCUBE Research’s Dave Vellante and George Gilbert examine that possibility after Dreamforce 2026. They map Salesforce’s next move through the System of Intelligence framework, where business context helps agents turn customer goals into action.Vellante and Gilbert explain how headless access lets customers work through Claude, Slack or other clients instead of beginning inside Salesforce. The interface may shift elsewhere, but Salesforce can remain essential by supplying trusted data, business knowledge, workflows and controls through its enterprise AI harness, connecting understanding directly with execution.New Qualitate research shows most organizations remain in Agentforce pilots or proofs of concept. Yet 75% of customers evaluating headless access expect Salesforce spending to increase. Vellante and Gilbert consider why greater consumption does not automatically guarantee customer value, and how pricing must align with measurable outcomes as deployments scale.

The cloud shared responsibility model was initially not well understood by many customers. In fact, early adopters often believed that simply having data in the cloud meant that Amazon, or a SaaS vendor were responsible for safeguarding it. Amazon had to educate its customers and partners that security and compliance duties were split between the vendor and the client organization. In short, the vendor was responsible for securing the cloud resources but you, the buyer, were responsible for securing what you put inside the cloud; based on your policies, priorities and budget. We believe a similar but much more consequential dynamic is unfolding with respect to agentic AI. Specifically, Cloud computing divided responsibility by infrastructure layer. Agentic AI distributes authority across a chain of models, platforms, clouds, partners and customers. Our premise is the industry now needs a shared accountability model for the decisions, actions and outcomes that chain produces.In short - The cloud shared-responsibility model told customers who secures what. The agentic shared-accountability model must define who can do what, who can stop it, who can prove what happened and who pays when it goes wrong.Welcome to episode 326 of Breaking Analysis. Beyond Shared Responsibility - When AI Acts, Who owns the Blast Radius. In this Breaking Analysis, Principal CUBE Research Analyst Krista Case and I explain why the agentic era demands a new accountability model. We’ll draw on learnings from last week’s CrowdStrike Fal.Con event, where the post Mythos moment and the OpenAI/Hugging Face “accident” were front and center. We’ll also draw on other new datapoints, including conversations with CISOs at Fal.Con and Palo Alto Networks’ earnings print from last week, to unpack what we’ve defined as a new AI accountability model. We’ll also test this new model against our Sovereignty framework, developed by Amit Govrin and assess sovereignty in the context of business recovery. We’ll explore the sequence of events that leads up to the ultimate question of who pays when something goes wrong?

In the latest episode of Breaking Analysis, theCUBE Research’s Dave Vellante digs into CrowdStrike’s post-Mythos momentum and Fal.Con outlook. He connects record second-quarter performance, $333 million in net new annual recurring revenue and $5.84 billion in ARR with an expanding security platform and rising buyer urgency across the enterprise market today.Vellante explains how Falcon Flex improves consolidation and unit economics, while proprietary telemetry strengthens CrowdStrike’s competitive moat. Rebecca and Krista add on-site perspective as the conversation moves across cloud, identity, next-generation SIEM, exposure management, DeepSeek-R1 and agentic AI risks, emphasizing autonomy, blast-radius containment and recovery controls for modern security operations.

In the latest Breaking Analysis episode, theCUBE Research’s Dave Vellante and Amit Eyal Govrin examine why enterprise AI economics demand more than tracking tokens and model calls. Using Canva, Uber and Lindy as examples, Vellante and Govrin show how costs emerge when companies overlook value retained from AI investments.The conversation moves from hybrid architectures and LLM gateways to a five-pillar sovereignty model built around control. Vellante and Govrin recommend measuring cost per accepted governed outcome while owning routing, evaluations and policy. Their practical playbook helps enterprises manage budgets, vendor dependencies and failover without surrendering financial sovereignty to vendors.

NVIDIA is making a bigger bet than simply selling more GPUs. In the latest Breaking Analysis, theCUBE Research’s Dave Vellante looks at its push to turn AI compute into a financeable asset class and what that could mean for the infrastructure boom, capital markets and the timing of a potential bubble.Vellante also looks to CoreWeave and Nebius for clues about whether the model holds up. Demand and pricing remain strong, but the bigger test comes later, when scarcity eases and operators must prove that utilization, cash flow, residual values and financing can withstand a full infrastructure cycle.

In the latest episode of Breaking Analysis, theCUBE Research’s Dave Vellante examines whether AI is forming a capital bubble. Vellante assesses capital commitments, monetizable demand and supply constraints, exploring when today’s AI infrastructure shortages could give way to oversupply and what that shift could mean for the broader market.Vellante tracks key signals across high-bandwidth memory, advanced packaging, GPU rental pricing, cluster utilization, power capacity and free cash flow. Using examples including Oracle, OpenAI and Stargate, he identifies 2028–2029 as the highest-risk window for a broader correction and explains what investors and infrastructure operators should watch closely next.

In the latest episode of Breaking Analysis, theCUBE Research’s Dave Vellante examines AMD’s Helios platform and the engineering velocity shaping artificial intelligence infrastructure. Vellante questions whether AMD’s distributed development model can compete with NVIDIA’s tightly integrated approach as software, hardware, partners and validation capacity increasingly determine long-term platform leadership.Drawing on SemiAnalysis findings, Vellante explains why testing coverage, model support, production feedback and improvement rates matter more than keynote benchmarks. AMD delivered an 18-fold interactivity gain in 30 days, yet cluster instability disrupted a key vLLM target and exposed a significant internal GPU capacity gap compared with NVIDIA.

AMD’s AI ambitions take center stage in the latest Breaking Analysis, as theCUBE Research’s Dave Vellante unpacks the company’s shift from processor comeback story to full-stack platform contender. Vellante traces how EPYC, Instinct, ROCm, Helios and strategic acquisitions now support a broader push into enterprise AI infrastructure.The episode examines why AMD does not need to unseat NVIDIA to succeed. Vellante frames its strategy around building the core, buying the gaps and ceding the ecosystem while weighing ROCm maturity, supply constraints and execution. He also explains how openness and heterogeneous computing could make AMD an indispensable second platform.

In the latest Breaking Analysis, the AGI hype gets a reality check. TheCUBE Research’s Dave Vellante and George Gilbert argue that the bigger enterprise opportunity is not chasing general intelligence, but building company-specific intelligence rooted in proprietary data, workflows, rules and trusted business context.The episode connects Databricks’ Data and AI Summit announcements to a bigger enterprise AI shift. Vellante and Gilbert unpack Genie Ontology, Unity Catalog, Omnigen and AgentBricks as building blocks for trusted role-based agents, showing how governed systems of intelligence can turn data investments into measurable business outcomes.