Jason McGee

FABCON 2026 in Atlanta was nothing short of mesmerizing-where bold ideas, breakthrough tech, and real-world impact came together seamlessly. An electrifying blend of vision, innovation, and execution that set the tone for the future of data and AI. Now, it’s a wait-and-watch moment to see how much of it proves truly real, scalable, and competitively differentiated. ** AI Foundry: Fabric IQ is positioned as a capability that makes data AI-consumable for agents and AI apps via OneLake ** OneLake Transform transformations are applied on top of shortcut or mirrored data (zero‑copy, zero‑ETL), preserving the original source while exposing a transformed view in OneLake. New Connectors have been added (SharePoint in preview). ** Data and Catalog mirroring / zero copy options across open table formats from snowflake and Databricks into Fabric ** SAP Fabric and Salesforce Fabric version with zero copy and write back functionality ** Availability of CoPilot across various platforms within Fabric exclusively designed to support that platform only ** Fabric AI and Data Agents ** Zero ETL Data Mirroring onto Onelake from Azure data for PostgreSQL. Analytics on Operational workloads made simple. ** Building declarative AI Pipelines made simpler with dspy and pixeltable Thanks to Cognizant leadership for the opportunity. Rajesh SreepadaSatish Hegde FABCON & SQLCON - The Microsoft Fabric & SQL Community Conferences Microsoft Fabric

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Proud to be part of the team behind today’s IBM announcement on the general commercial availability of GenAI on IBM Z and Power. This milestone brings PyTorch and vLLM into the heart of enterprise-grade AI systems — powering high-throughput, low-latency inference and training on IBM’s mission-critical platforms. The work reflects deep collaboration across IBM Research, IBM Systems, and the open-source ecosystem, advancing how foundation-model workloads scale securely and efficiently. Learn more about how PyTorch and vLLM enable GenAI on Z and Power at the upcoming PyTorch Conference (PyTorch vLLM). #IBMResearch #PyTorch #vLLM #GenAI #HybridCloud #AIInfrastructure #IBMZ #IBMPower #PyTorchConference

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Stop waiting for the “AI replacement.” It’s not coming—at least, not in the way most people think. I’ve been part of the technology transformation story since 2000. I started with mainframe modernization—screen-scraping IBM COBOL applications running on CICS systems and rebuilding interfaces in Java. At the time, the message was clear: open-source systems would replace mainframes. They didn’t. Mainframes evolved—and in many enterprises, became even more critical. Then came BPM and SOA. Once again, replacement was promised. What followed was more pragmatic: systems became modular, interoperable, and easier to scale. Then Watson won Jeopardy. It reshaped how we thought about machine intelligence. Yet it didn’t replace experts—it augmented decision-making where context mattered. Then came the cloud wave. “Data centers will disappear.” “On-prem is dead.” Neither happened. What emerged instead was choice, elasticity, speed, and a new operating model. Enterprises modernized selectively, not blindly. Now we’re in the Generative AI wave. The language feels familiar: “Developers will be replaced.” “Software engineering is over.” “Vibe coding is the future.” Vibe coding is not software engineering. It’s an interface shift, not the discipline itself. And AI, like every wave before it, augments capability—it doesn’t remove responsibility. The anxiety we see today isn’t really an AI story. It’s the result of inflated expectations, COVID-era over-hiring, and the belief that productivity gains would be immediate. Some bets worked. Many didn’t. That’s how transformation has always unfolded. The only advice I can offer is this: pair bold technology bets with measured hiring decisions. That balance is what turns waves of change into sustainable progress. I consider myself fortunate to have been part of this journey for over two decades—learning from each wave, helping lead transformation efforts, and preparing early for what came next. I’ve lived through enough waves to know this: Technology rarely replaces. It almost always refines. AI is no different. If history teaches us anything, it’s that the next phase won’t be about replacing humans—but about raising the bar on leadership, engineering, and decision-making. We will need more people, not fewer—just working differently. That’s the real transformation ahead. #ai #future

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https://lnkd.in/g9vjKfu4 More than 9,000 peers just kicked off #KubeCon + #CloudNativeCon in Atlanta as Cloud Native Computing Foundation (CNCF) celebrates 10 years—and the conversation has a new center of gravity. Cloud native and AI aren’t parallel trends anymore; they’re merging. The question is how we make AI boring in the best possible way: predictable, portable, and ready for operations at scale. That’s why the Kubernetes AI Conformance program announced on the mainstage matters. It sets a common floor across six pillars—accelerators, networking, security, scheduling, observability, and operators—so teams can run AI on Kubernetes without bespoke “one-off” integrations for every environment. The live demo showed the building blocks we’ve been asking for: GA Dynamic Resource Allocation in 1.34 to model GPUs/TPUs, standard metrics from the model and accelerators, and autoscaling via custom metrics paths that platform teams can actually support. Context for the urgency: inference demand is compounding. Google reported an increase from ~980 trillion to ~1.33 quadrillion tokens per month in a matter of months. That level of consumption shifts the conversation from pilots to platform. Conformance is the mechanism that aligns vendors and gives enterprises a stable target. What we’ll be watching next: how quickly providers certify and how conformance guidance evolves for multi-node and fractional accelerators. I’ll share more conversations and takeaways from the floor—stay tuned. https://lnkd.in/g9vjKfu4 #KubeCon #CloudNativeCon

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AWS to Demo VirtualZ Computing's Lozen™ Integration with Rocket Software® Enterprise Developer in its November 11, 2025, PartnerCast. https://lnkd.in/geJ47yu6 The Amazon Web Services (AWS) and VirtualZ Computing collaboration is also highlighted in the recent AWS blog post, Transforming Hybrid Mainframe Data Access with VirtualZ Lozen and AWS: https://lnkd.in/eS8q9Xbc

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Updating university libraries demands efficiency, dependability, and adaptability for the future. This customer story blog highlights how the University of Maryland successfully transitioned to the cloud with AWS in just six months, transforming library services to meet changing academic requirements. Explore the blog to gain insights from the University of Maryland's journey and envision how your institution could enhance library services through modernization with AWS Cloud. @amazon-web-servicesrnization with AWS Cloud. @amazon-web-services

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Rocket Enterprise Server supports COBOL and PL/I workloads, integrates with CICS, IMS, JES2, VSAM, and IMS DB, and provides full observability through OpenTelemetry. Deploy workloads on Linux, Windows, Unix, or cloud with high availability and secure multi-factor authentication. Review technical details: https://ow.ly/uTiF50XwPO7 #RocketSoftware #Technology #MainframeIntegration #EnterpriseApplications #CloudDeployment #ITSecurity #DevOps

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