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David Vellante shared this316 | Breaking Analysis | Personal Agents Light the Fuse as Snowflake and Databricks Move Up the AI Stack - co authored w/ George Gilbert This week on Breaking Analysis, George Gilbert and I unpacked why the next phase of enterprise AI may look a lot like the PC era at first - bottom-up, personal, productivity-driven and often self-funded. But there’s one major difference that stands out... PCs helped people create documents, spreadsheets and dashboards. Agents act. If every individual, department and vendor builds its own island of intelligence, enterprises will recreate the same silo problem that has plagued software for decades - only faster, with greater risk. Our premise is that the first wave of enterprise AI will be driven by personal agents, but the durable value will accrue to the platforms that organize enterprise knowledge into a true System of Intelligence. That’s why Snowflake and Databricks remain relevant ahead of their respective summits. They’ve crossed the Rubicon. They are no longer just data platforms serving analytics. They’re moving up the AI stack toward the layer where enterprise data, rules, context, actions and business logic become human-readable, agent-readable and eventually executable. And they’re not alone. Salesforce, SAP, Microsoft, Palantir Technologies, Celonis, Oracle, Google, Anthropic, OpenAI, Amazon Web Services (AWS) and others are all moving toward some version of this control point. The key idea is this: How sophisticated your data model is determines how sophisticated your analytics can be. And how sophisticated your analytics are determines how much action your agents can safely take on your behalf. That is the battle for data intelligence. Personal agents light the fuse. The System of Intelligence determines who captures the value. Full Breaking Analysis in comments. #AI #AgenticAI #Snowflake #Databricks #DataIntelligence #EnterpriseAI #SystemOfIntelligence #DataPlatforms #DigitalTwin #CIO #ChiefAIOfficer #theCUBEResearch
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David Vellante shared thisHere's a preview of today's Breaking Analysis. In this episode, George Gilbert and I put forth a vision of what the emerging AI software stack looks like, how it is evolving in a top/down/bottom-up fashion and what the risks are to enterprises that allow AI silos into their enterprise architecture.316 | Breaking Analysis PREVIEW | Personal agents light the fuse in the age of intelligence316 | Breaking Analysis PREVIEW | Personal agents light the fuse in the age of intelligence
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David Vellante shared thisSpecial Breaking Analysis | IBM and Red Hat’s Project Lightwell: Securing Open Source in the Age of Frontier AI Open source security is entering a new era, catalyzed by frontier AI. Anthropic's Mythos and a spate of capabilities from other frontier model vendors including OpenAI have prompted responses from tech vendors like Oracle and now IBM and Red Hat IBM and Red Hat announced Project Lightwell - a $5B commitment to create a trusted enterprise clearinghouse for open source software security, backed by AI-driven vulnerability validation and more than 20,000 engineers. In our view, this is a response to a fundamental change in the threat model. Frontier models are getting orders of magnitude better at reading code, reasoning across dependencies, identifying vulnerabilities and mapping out exploit paths. The result is the cost of exploiting weakness is dramatically falling - and attackers will increasingly use AI to compress discovery cycles. The old way of protecting systems is insufficient. You know...scan frequently, file tickets, hope committers get involved, patch when there's a window... This operating doesn't work when exploitations move at machine speeds. Project Lightwell is IBM and Red Hat’s attempt to create a trusted remediation layer. The idea is to combine AI, engineering at scale, enterprise validation and upstream coordination so organizations can accelerate validated fixes - without trying to manage the entire open source supply chain on their own. The early adopter list reads like an IBM Z Systems client list: Bank of America, BNY, Citi, Goldman Sachs, JPMorganChase, Mastercard, Morgan Stanley, RBC, State Street, Visa and Wells Fargo. But this goes beyond mainframe affinity. These are firms where open source security is mission-critical infrastructure. The big question to us is execution. IBM and Red Hat must show how Lightwell integrates into DevSecOps workflows, how community governance works, what software is covered, how AI validation is audited, and what SLAs or liability models look like. Nonetheless, strategically, this is the kind of complex enterprise problem IBM should be solving in our view so kudos for the initiative. In the frontier model era, software supply chain resilience is foundational to enterprise trust. Read the full analysis and recommend actions for business technology execs in the comments. #OpenSource #Cybersecurity #AI #SoftwareSupplyChain #RedHat #IBM #DevSecOps #EnterpriseIT #AIsecurity #CyberResilience
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David Vellante shared thisJeff Clarke's Premise: Tokenomics Moves From PoC to the P&L - How Dell Technologies Sees the Future of AI Jeff Clarke made a statement at #DellTechWorld last week that I think people may be underestimating: “Tokens will become a line item on the P&L.” That’s a profound statement because it demonstrates how the move from a technology world defined largely by SaaS to one where AI changes the operating model beyond the IT department. There is an entirely new software stack forming that will affect the technology, business and operating models of enterprises globally. Not just the IT department but the entire organization. Clarke shared two numbers that caught our attention: Cost per token down ~80% this past year; Token consumption up 320x. That’s essentially Jevons economics playing out in real time. As the cost of intelligence declines, enterprises will consume dramatically more of it. And once intelligence becomes a production input, the operating model changes. The starting point is standing up; or tapping into intelligence via AI factories. But the bigger shift is organizational and operational. Reconciling the friction in organizations that lives in silos. Specifically, today’s enterprises still run as fragmented application silos held together by human reconciliation: *meetings *spreadsheets *tribal knowledge *approvals *manual recovery *endless interpretation at the seams What Dell is arguing - and what George Gilbert, David Floyer and I have been digging into on Breaking Analysis - is that AI changes the coordination layer of the enterprise itself. An interesting example came from Dell CIO Douglas Schmitt. He described how cross-functional meetings, which we know used to devolve into: “Whose data is right?” Has undergone a transformation at Dell, where a connected data mesh and prompt-driven systems allows staff to iterate toward the answer in real time — compressing what used to take days or weeks into minutes. That’s an operating model story. In our latest Breaking Analysis, George and I argue that: frontier models are the catalyst, AI factories manufacture intelligence in the form of tokens, but the real value comes from a new System of Intelligence layer that harmonizes enterprise state, rules, semantics, and process knowledge so agents can act with confidence The result is what we call “service as software.” Not SaaS. A fundamentally different economic model where enterprises begin scaling revenue with far less proportional labor growth. This will take years to fully play out. But the direction is becoming clearer and tokens become financial primitives, while agents become operational actors, observability evolves into “Datadog for agents” and enterprises start behaving more like platforms than org charts. This is the real shift underway. Full research post in the comments #AI #DellTechWorld #AgenticAI #Tokenomics #EnterpriseAI #SystemOfIntelligence #AIInfrastructure #DigitalTransformation #FutureOfWork #theCUBEResearch
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David Vellante shared this315 | Breaking Analysis | How AI Stacks are Rewriting the Rules of Business - co-authored with George Gilbert & David Floyer Most enterprises think they run deterministic systems. In practice, they run an application jungle held together by probabilistic human interpretation. That “human semantic glue” - exceptions, meanings, approvals, reconciliations - is why the enterprise still lives with delayed truth, conflicting semantics, high coordination cost, and manual recovery. In our latest Breaking Analysis, we argue that AI doesn’t just modernize IT - it rewrites the operating model of the business. Frontier models are the catalyst and the migration engine, but the real shift happens when enterprises build the full AI stack that can coordinate work across silos and take action with confidence: *Deterministic apps remain the substrate - but they stop being the control plane; *A System of Intelligence becomes the real-time truth layer - harmonizing state, context, and policy so agents can operate; *A System of Agency provides the control loop - perceive, reason, decide, act, learn - with guardrails; *A System of Engagement closes the loop - humans in the workflow so the system improves over time. The economic impact is the platform shift is expensive because it replaces more than servers, storage and networking. It replaces the human coordination layer around fragmented applications. Capital expands toward AI factories - while coordination labor falls - and that’s where the 10x productivity conversations start to become attainable. With comments on the new AI operating model and tokens on the P&L from Jeff Clarke's Dell Technologies World keynote. An instructive example of AI ROI from Douglas Schmitt. A nuanced discussion with Anand Eswaran of Veeam Software applied to our AI stack framework. Full Breaking Analysis - link in comments. #AI #EnterpriseSoftware #Agents #DataPlatforms #SystemOfIntelligence #DigitalTwin #OperatingModel #TokenEconomics
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David Vellante shared thisSpecial breaking analysis: Veeam’s bet on data + ai trust – expanding from recovery into the trust layer According to Veeam Software's CEO, Anand Eswaran, the shift from "restore after a crash" to "trust while agents act" is officially here. At VeeamON 2026, Eswaran signaled a massive pivot. With the $1.725B acquisition of Securiti AI and its novel knowledge graph, Veeam is expanding from backing up your files to building the "Data + AI Trust" layer. In a world where autonomous agents outnumber humans and operate at machine speed, restoring a snapshot is a more like a blunt instrument. Veeam's premise is we need precision recovery - e.g. the ability to undo 5 seconds of a rogue agent's actions rather than rewinding the entire business by 3 days. The Five Pillars of the Veeam's Data + AI offering: 🛡️ Security: Protecting data as the new perimeter. ⚖️ Governance: Real-time oversight of agentic workflows. 📜 Compliance: Automating regulatory mapping for AI data. 🔒 Privacy: Binding consent and policy directly to the data. 🔄 Resilience: Moving from "assume restore" to "precision remediation." Veeam has surpassed $2B+ in ARR and is potentially showing the profitability and scale of a company ready for the public markets. By moving into the security space, they are positioning themselves as the essential harness for what we call the modern System of Intelligence. Is your CISO thinking about recovery as a core part of the AI trust agenda, or just an afterthought? Read the full breakdown in the comments - with data from ETR (Enterprise Technology Research) on Veeam's competitive spending profile and account penetration relative to Rubrik Commvault Cohesity / Veritas #Veeam #GenerativeAI #CyberResilience #DataTrust #CloudSecurity #EnterpriseTech #IPO #AgenticAI #DataSecurity #VeeamON
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David Vellante shared thisSpecial Breaking Analysis: Veeam pushes backup into the AI resilience era at VeeamOn 2026 Veeam's strength has always been aligning with market trends and building products that simplify difficult operational problems. At VeeamON 2026, the company leaned into the agentic era while connecting AI to the need for resilient operations. It's recent product announcements recognize four key customer needs, including: 1) Broader visibility across backup and production data; 2) Governed access to data for both humans and agents; 3) An expanded scope across hybrid/distributed systems; and 4) A methodology to assess AI readiness and maturity in the context of business resilience. These are practical enhancements and fit the current market need. But the market is changing rapidly and the architectural implications for storage and data in the AI factory era will require continuous innovation from firms like Veeam. Specifically, Veeam is rightly focused on data as the linchpin of business resilience. The next challenge and opportunity in our view will be to not only protect and recover data to bolster resilience, but to recover the actual state of a business. In this special Breaking Analysis we review the pre-game of VeamOn 2026 and put forth a challenge to the traditional data protection players. Specifically, moving how to incorporate "Organizational State" into business resilience. How do you see the move by backup vendors to become security players? And where do they go next? Krista Case (Macomber) and I will be breaking down all the action this week at #VeeamOn 2026 in NYC Full analysis in the comments...
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David Vellante shared thisSpecial Breaking Analysis: Quantum computing finds its place in the stack as an accelerator, not a replacement Quantum computing is not a magic technology that replaces classical computing. Rather it will become part of the evolving AI stack. That’s the key takeaway from recent work that Paul Gillin and I did at SiliconANGLE & theCUBE Research around World Quantum Day, made possible by Hewlett Packard Enterprise. We had conversations with leading national labs and brought other research into the mix. The future is quantum + classical. It’s a hybrid of CPUs + GPUs + QPUs, orchestrated through software, scheduling, data movement, AI-assisted tooling and domain-specific algorithms. In other words: quantum becomes another specialized accelerator inside a broader hybrid compute fabric. For mainstream enterprises, this means two things. First, don’t get distracted by “quantum fever.” Most organizations should stay focused on AI, data governance, infrastructure modernization and cyber resilience. Second, post-quantum cryptography needs to move onto the 2026 planning agenda now. The “harvest now, decrypt later” risk is real. Sensitive data stolen today could become vulnerable later if cryptographically relevant quantum systems emerge. The near-term enterprise action is understanding where cryptography lives, which data has long confidentiality lifetimes, and how to build cryptographic agility across applications, infrastructure, devices and third parties. The medium-term opportunity is hybrid experimentation in domains where classical scaling starts to break down - materials science, chemistry, energy, pharma, logistics and national security. The long-term opportunity is taking advantage of a new compute fabric, building applications where CPUs, GPUs and QPUs are orchestrated together to solve problems no single architecture can handle alone. Quantum will not replace the AI stack.It will become part of the stack. And that may be the most important focus the market can have right now. Full research note in the comments. #QuantumComputing #AI #HPC #Cybersecurity #PostQuantumCryptography #PQC #EnterpriseIT #DataSecurity #HybridComputing #theCUBEResearch
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David Vellante shared this314 | Breaking Analysis | Nvidia, AI factories and the transition to accelerated computing Co-authored with David Floyer The biggest enterprise AI story is not about the current boom in semis. It is that AI factories and the intelligence they produce will begin to replace the human reconciliation layer that keeps companies running today. Most large enterprises do not operate from a clean, unified system of truth. They operate through a maze of ERP, CRM, finance, supply chain, HR, security, analytics and industry-specific applications - each with its own data model, workflows, exceptions and version of reality. Determinism today is a myth. The reality is deterministic systems require human adjudication. *People reconcile conflicting data and interpret exceptions. *People chase approvals. *People translate between systems. *People resolve broken workflows. *People know which report is “right.” *People understand what the business process really means versus what the software says it means. This is the hidden operating model of the enterprise. It is expensive and slow. The promise of AI factories - and the important applications that must be built on top of them - is that they do not just generate tokens. They produce intelligence that can inspect systems, infer meaning, map workflows, diagnose conflicts, build integrations, operate agents and continuously improve how the business runs. In this scenario, frontier models become the semantic operating layer of the enterprise. They analyze codebases, database schemas, APIs, logs, tickets, documents and human procedures to understand how the company actually works. They collaborate with experts to define shared semantics. They identify where systems conflict. They orchestrate agents under policy. And over time, they begin to automate the reconciliation work that today depends on tribal knowledge and human intervention. That is the real operating model shift. We see the existing x86 infrastructure being absorbed into the AI factory story. Legacy systems will not disappear overnight. They will be surrounded, interpreted and gradually pulled into AI factory architectures built on GPUs, CPUs, DPUs, high-speed fabrics, context storage, semantic databases and policy-aware control planes. That is the technical “how.” The larger “why” is that enterprises want to collapse the distance between fragmented applications and real-time truth. The next decade of enterprise AI will be defined by platforms that can replace human semantic glue with machine-scale intelligence - not by eliminating people, but by moving them out of endless reconciliation and into higher-value judgment, design and governance. That is why AI factories are more profound than people realize. They are the foundation for a new enterprise operating model. In this Breaking Analysis we break this down using NVIDIA's roadmap as a guide to the future. Full slide deck here: https://bit.ly/4uCJwzB Full research in the comments.
David Vellante commented on a post
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Thanks for sharing this Muddu...Salesforce is a leading example of a deterministic system of record bringing a probabilistic dimension to its software. Headless 360 is the right vision because it recognizes explicitly that islands of automation are not the end game. Rather an enterprise "digital twin" where agents can act across all systems is the North Star. Eventually markets will catch up to the fact that, while some SaaS companies will be disrupted, the innovators will thrive. I personally put Salesforce in the latter camp.
David Vellante commented on a post
1d
Read the full research note: https://thecuberesearch.com/316-breaking-analysis-personal-agents-light-the-fuse-as-snowflake-and-databricks-move-up-the-ai-stack/
David Vellante replied to a comment
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Dean Chapman ok interesting. I need to learn more about this. So you're presumably using rules at the hardware level in terms of what's allowed and what's not. Can an agent fool your system and insert benign tokens over time that sit idle until such time as the exploit executes- if you're at T=0 how do you protect against an exploit that is initiated over weeks or months? Do you somehow store the micro actions?
Would seem a combo of VC and protection at the data level would still be advisable?
Also how are you thinking about protecting AI Factories - do you play there where pcie is not as widely used - especially deep in the Nvidia memory hierarchy. How do you capitalize on the AI factory boom?
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David Vellante liked thisDavid Vellante liked thisI will be attending AWS Summit, NYC on June 17. I am looking forward to the discussions with industry leaders, fellow analysts, AWS leaders, AWS partners, and AWS customers. See you there! cc Amazon Web Services (AWS) John Furrier David Vellante
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David Vellante liked thisDavid Vellante liked this🚨Salesforce earnings shows SaaSpocolypse is “Deadpocolypse”. You definitely couldn’t see it in Salesforce’s latest earnings report. Salesforce earnings are showing growth of AI, Agents, Data and Agentic Apps. 📈 Quarterly revenue jumped 13% to $11.13 billion, the highest in the company’s history. 🤖 Agentforce (AI and Agents) revenues crossed $1 billion. AI + Data is $3.4B and growing at 200% YOY 💹 On the earnings news, CRM stock spiked 8.47% to $191.10. According to Marc Benioff: “Agentic AI, well, it's the biggest growth opportunity for our customers, for us at Salesforce, since we brought CRM into the cloud, we're just seeing tremendous new innovation every single day. You can see it in our products, you can see it in our customer momentum, you can see it in our results. Salesforce has never been more essential to our customers.” Now, OpenAI (Sam Altman) and Anthropic (Dario Amodei) are retracting previous statements about the SaaSpocolpse. 🤖 Agentforce traction with 3.8 billion agentic work units (AWUs) over 28.6 trillion tokens in this quarter. Agentic Apps like IT Service and HR Service are contributing to these outcomes and consumption. 🔗 Headless 360: Investors and the market are intrigued by the vision and strategy. Customers and partners are adopting Headless 360 APIs, CLIs and MCPs. 💬Slack: Investors, customers, and partners are highly encouraged by the momentum in Slack and Slackbot. Slack is well positioned to benefit from the AI and Agentic wave. Slack is the best conversation OS for Agents and Humans. 📈 Agentforce IT Service and HR Service are growing rapidly. Excited to partner with organizations such as United States Air Force, PenFed Credit Union, McAfee, American Public Education, Inc. (APEI), State of Hawaii, Cooper Parry, Alstef Group. https://lnkd.in/dBNcqzgT 🚀 Anthropic is one of Salesforce’s biggest users of CRM, Sales Cloud, and Slack. Their usage through Q1 has exploded fivefold because they're using Sales Cloud from a headless perspective. 🏆 Salesforce Agentforce HR Service won the AI Impact Award from Newsweek for: AI Workplace Best Outcomes for HR https://lnkd.in/dzXsaHkA Not long ago, the buzz was about the end of SaaS software… Agentic AI is a very powerful force multiplier for SaaS companies that are a true agentic-first strategy and agentic tech stack. Here the earnings call transcript: https://lnkd.in/dp6j9jKw Press release: https://lnkd.in/d6nv9PuK Earnings deck: https://lnkd.in/djemvtaz Amazon Web Services (AWS) Google Microsoft Oracle SAP Adobe Snowflake Databricks Bloomberg Forbes The Wall Street Journal CNBC
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David Vellante liked thisDavid Vellante liked thisHappy Birthday To My Buddy Bill Tai!!! Jonathan Ross - Rick Baker - Lars Rasmussen - Trinity Chavez - Hao Zhong - Mitesh Agrawal - Kevin Hawkins - Amanda Terry - Silvia Chen - Jenny Shao, MD - Dom Sagolla - Kenji Kato - Brian Gallagher - Shehram Jamal - John Furrier - Joseph Lubin - Jimmy Vaiopoulos
Experience & Education
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SiliconANGLE & theCUBE
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Volunteer Experience
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President
Harvard Athletic Association
- 7 years
Children
Promoting fairness and participation in youth sports...Meeting the needs of all children.
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President
Harvard Youth Baseball & Softball Association
- 6 years 2 months
Children
Lead administrator for youth baseball & softball. Representative for Worcester County Little League - Head Compliance Officer for ensuring children’s safety.
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Finance committee member for local catholic parish
Finance Committee, St. Theresas Little Flower Parish
- 2 years 1 month
Poverty Alleviation
Evaluate and participate in fundraising strategies and capital allocation for local catholic parish.
Publications
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http://wikibon.org/bigdata
Wikibon
Projects
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TechTruth - Women in Tech Project
See projectTechTruth is a non-profit formed by John Furrier, Charles Sennott and Dave Vellante. It is a collaboration between SiliconANGLE Media and The GroundTruth project. Our aim is to train the next generation of tech journalists. Our first initiative focused on gender equality and diversity in the technology field.
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#theCUBE
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The CUBE is a place for big ideas to grow...It has been called The ESPN of enterprise tech...a live and on-demand social media video studio that extracts the signal from the noise and shares knowledge with an engaged audience.
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Honors & Awards
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MIT CDOIQ Outstanding Service Award
MIT
Recognized for my contribution to the MIT Chief Data Officer Symposium - MIT CDOIQ, focused on improving data quality and governance for data-driven organizations.
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