Victoria Gayton
Latest from Victoria Gayton
Union.ai on the rise of experimental AI development infrastructure in the enterprise
Building software has long followed a reliable playbook: Write code, test, deploy and iterate. But when deterministic algorithms give way to artificial intelligence models that learn and adapt, the old playbook falls apart. AI development infrastructure has become essential for enterprises trying to move projects from prototype to production. The shift stems from a fundamental ...
Synthetic recovery gains traction as a new frontline defense against escalating cyberattacks
When a cyberattack hits, organizations face an impossible choice: Roll back to a known, clean copy and accept significant data loss or push forward with potentially compromised systems. That no-win gamble has defined disaster recovery for years. A new approach, synthetic recovery, is reframing the equation entirely. The concept, introduced by Commvault Systems Inc. at ...
Developer workflow poised for change as AWS advances continuous-learning AI agents
For all the hype around artificial intelligence coding assistants, many treat every session as a blank slate — no memory of yesterday’s preferences, context or institutional knowledge. That’s the gap agentic AI aims to close, not just helping developers write code but functioning as persistent, context-aware teammates. Developers typically spend only 20% to 30% of ...
AI agents reshape expectations for data connectivity as Salesforce expands its ecosystem strategy
Enterprise data integration is fast becoming the quiet power broker behind modern AI, reshaping how companies stitch together sprawling data estates, evolving application stacks and an ever-widening menu of model options. What’s emerging is less a tooling problem and more a coordination challenge — one that surfaces the moment agentic workflows and AI-driven operations start ...
AI-native observability is becoming the new enterprise compass, says Honeycomb.io CMO
Cloud-native practices have matured into stable foundations, and the industry is accelerating toward an AI-native observability future. Observability is becoming essential for ensuring direction and measurable outcomes in this fast-paced environment. Cloud-native and AI-native observability are reshaping workflows, data practices and engineering culture. With the rise of agentic systems, enterprises face unprecedented volumes of data ...
How Zendesk built the AI engine powering billions of customer interactions
Customer service automation has become one of enterprise tech’s most AI-intensive workloads. The shift goes beyond chatbots to multimodal interactions, proprietary training data and infrastructure handling hundreds of billions of application programming interface requests annually. Cloud-based software company Zendesk Inc.’s approach is built on a multifaceted relationship with Amazon Web Services Inc., spanning infrastructure, voice ...
Enterprises tightening the stack as AI workloads surge
Enterprises are rebuilding their digital foundations as artificial intelligence accelerates demand for smarter, more resilient AI infrastructure. Across the industry, teams are reconsidering how tightly their systems need to work together to keep up with modern workloads. The pressure to move faster and handle more data is reshaping expectations for how next-generation platforms are designed, ...
Three insights you might have missed from theCUBE’s coverage of KubeCon + CloudNativeCon NA
For years, cloud computing’s entire pitch was “forget about hardware.” Kubernetes doubled down on that promise, abstracting infrastructure into something developers could safely ignore. But AI workloads don’t play by those rules. Inference engines, agentic systems and foundation models are pulling hardware back into the conversation — and this time, ignoring it isn’t an option. ...
Three insights you may have missed from theCUBE’s coverage of Celosphere 25
Enterprises are building the connective tissue that lets data, processes and decisions flow as one system. Intelligence is no longer confined to isolated dashboards or static reports. Now, it moves across silos in real time, fueled by AI agents and process intelligence platforms that map how work actually happens. It’s the digital equivalent of the ...
What to expect during AWS re:Invent: Join theCUBE Dec. 2-4
Enterprise infrastructure is hitting an inflection point, where production-scale workloads, purpose-built silicon and strategic ecosystem partnerships converge to power the next generation of intelligent systems. Organizations are moving beyond experimentation with AI, building deployments that demand massive compute, structured development practices and AI infrastructure to support autonomous agents at scale. One area of focus at AWS ...