Practical AI for Business Growth

Event: AI Field Day 7

Appearance: Utilizing AI Podcast

Company: The Futurum Group

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Personnel: Nick Patience, Stephen Foskett

Stephen Foskett and Nick Patience are introducing a new podcast called Utilizing AI, where they focus on the practical applications of artificial intelligence in enterprises to drive efficiency, improve decision-making, and foster innovation. They invite listeners to participate in weekly episodes that discuss practical AI applications within various business sectors, offering insights and examples of real-world outcomes from incorporating AI technologies. The episodes will also explore AI Field Day events and analyze insights from The Futurum Group’s research and AI practice.

The podcast’s first episode was recorded live during AI Field Day in Santa Clara, bringing various groups together, including individuals from TechStrong, Tech Field Day, and Futurum’s research and analyst team. They aim to present different perspectives on how AI can be transformative within enterprise IT, presenting AI as a pervasive general-purpose technology impacting various facets of business operations. Highlights from the discussion included upcoming AI Field Day events, planned appearances at industry conferences, and an exploratory overview of significant players and their roles, such as AWS, Google, and Oracle, in the AI ecosystem. The podcast intends to focus on keeping up with the fast pace of AI developments and distinguishing meaningful trends and innovations from fleeting ones.

They shared insights into AI’s impact on industries and detailed upcoming plans and discussions related to AI usage. As AI continues to evolve and impact various industries differently, there’s an emphasis on enterprise adoption of AI technologies to automate processes, improve customer service, and optimize operations. The team plans to highlight practical examples and discuss how businesses can navigate the rapidly-changing AI landscape, balancing the fear of missing out with the day-to-day operational needs. The podcast is set to respond to weekly changes and announcements in the AI field, continuously aiming to inform and discuss the current state and future of AI technologies.


Considering ResOps – a Tech Field Day Roundtable at Commvault SHIFT 2025

Event: Tech Field Day Experience at Commvault SHIFT 2025

Appearance: Commvault SHIFT Roundtable Discussion

Company: Commvault

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Personnel: Jay Cuthrell, Karen Lopez, Michael Stempf, Shala Warner, Stephen Foskett, Tom Hollingsworth

At the Commvault SHIFT 2025 Tech Field Day Roundtable in New York City, moderator Stephen Foskett convened a panel of industry experts to discuss the latest trends in data protection, resilience, and artificial intelligence. The panel included Jay Cuthrell, Karen Lopez, Shala Warner, and Tom Hollingsworth, as well as Michael Stempf from Commvault, each bringing perspectives from security, data management, DevOps, and cloud architecture. The discussion focused on Commvault’s strategic announcements around ResOps—an emerging discipline combining practices from DevOps, SecOps, and FinOps into a holistic approach to cyber resilience. Panelists noted the importance of cross-team collaboration, integrations with major cloud and security platforms, and the convergence of operational practices, all of which align with the increasing complexity of enterprise IT environments and the growing threat landscape fueled by AI-driven attacks.

A key topic was the shift from traditional disaster recovery (DR) and backup, which assumed non-malicious outages, towards a mindset anchored in active defense against adversarial threats like ransomware. Jay Cuthrell and Tom Hollingsworth highlighted innovations such as synthetic restore—a method to selectively recover clean data and minimize downtime after an attack—as well as the crucial role of identifying attack persistence in overlooked areas like Active Directory. The panel emphasized the necessity of incorporating AI for faster detection and remediation, but also pointed out the risk of AI-generated threats and the importance of comprehensive data inventories. Karen Lopez stressed that recovery, not just backup, should be the ultimate goal, asserting that organizations need robust strategies to know what data they have, where it lives, and how it is being protected.

The roundtable concluded that Commvault’s announced direction—moving beyond storage toward broader cyber and AI resilience—was credible and matched the realities of modern IT. Panelists praised new capabilities such as conversational interfaces and integrations with collaboration tools (e.g., Office 365, Google Workspace, and cloud-native databases), while also pointing to the need for organizations to invest in people and processes, not just technology. The panel agreed that cyber resiliency is now a “team sport,” requiring cooperation across IT, security, legal, and business units, facilitated by intelligent automation and education programs. The event served as both a showcase of Commvault’s evolution and a broader industry call to arms for holistic, AI-aware data protection.


What Would You Send a Cloud Scout to Fix with SOUTHWORKS

Event: Tech Field Day at KubeCon North America 2025

Appearance: Southworks Presents at Tech Field Day at KubeCon North America 2025

Company: SOUTHWORKS

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Personnel: Johnny Halife

This segment grounds the idea in practice. We’ll examine how embedded engineers have helped product teams go beyond reactive fixes — from automating post-mortems to co-designing self-healing infrastructure and predictive testing frameworks. The focus is on what changes when teams own reliability together: faster iteration, fewer handoffs, and more precise success metrics. We’ll close with an open discussion on how organizations can experiment with the Cloud Scout model — and what it signals for the next evolution of DevOps.

The presentation addresses the challenge of organizations needing to adopt new technologies, such as AI, but facing uncertainty and risk. The Cloud Scout model is presented as a way to mitigate these risks by embedding engineers to assess the current state, identify opportunities, and demonstrate the value of new tools and practices. The goal is to de-risk innovation and empower teams to embrace change, particularly concerning AI adoption, which is driven by business mandates but often faces resistance due to security concerns or a lack of clear implementation strategies.

A key aspect of the Cloud Scout approach is its focus on practical application and measurable business outcomes. The scouts aim to demonstrate, not just tell, how AI can be utilized to achieve specific goals, such as reducing alert fatigue or enhancing efficiency. While the initial engagement is typically a 40-hour-a-week commitment for three months to understand the problem and prototype a solution, it can evolve into a fractional engagement with a specialist or lead to a separate project for building out the solution. This approach emphasizes the importance of senior expertise in navigating uncertainty and mitigating risk associated with new technology adoption, ultimately enabling organizations to become more mature and effectively embrace innovation.


Demonstrating AI-Assisted Development for Leading European Streaming Service with SOUTHWORKS

Event: Tech Field Day at KubeCon North America 2025

Appearance: Southworks Presents at Tech Field Day at KubeCon North America 2025

Company: SOUTHWORKS

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Personnel: Johnny Halife

A Cloud Scou is a forward-deployed engineer who joins the product team to co-own reliability, scalability, and evolution. Drawing from the Forward-Deployed Engineer for SR and AI-Managed DevCrew models, Scouts act as both architectural advisors and implementers — blending human judgment with AI-driven companions to build, test, and tune cloud-native systems. We walk through how this embedded approach fosters continuous improvement, strengthens technical decision-making, and creates a shared sense of accountability between Dev, Ops, and AI.

Johnny Halife from SOUTHWORKS presented an example of their work with a European streaming service facing issues with their electronic program guide (EPG). The EPG, built on Node.js, Lambda, S3, BigQuery, and XML, was experiencing blank displays due to ingestion problems. The issue was traced to an unexpected 413 error indicating that the request entity was too large, specifically related to image transformation failures. This problem was impacting viewers, who were seeing blank screens.

To address this, SOUTHWORKS employed a Cloud Scout, leveraging tools such as GitHub Copilot and their own MCP servers, which are connected to AWS CloudWatch. The process began with the scout prompting GitHub Copilot to create a Jira ticket, which was then assigned. The agent analyzed the error by running CloudWatch MCP, finding related logs, and contextualizing them within the solution codebase. This analysis revealed a missing validation and a data conflict between files, providing evidence-backed insights. The agent then proposed solutions, including code changes, which were compiled into a pull request.

The final step involved a code review by the Scout, along with standard organizational pre- and post-requisites, including SonarQube and linting. This process, previously taking days, was reduced to a few hours. By implementing this AI-assisted approach, the streaming service experienced faster issue resolution, fewer noisy alerts, and predictive scoring for deployments, resulting in a significant reduction in recovery time. This approach enabled them to transition from a defensive strategy of increased monitoring and tooling to a proactive approach, aimed at preventing issues before they arise by analyzing past incidents and identifying potential risks.


Cloud Scouts are Embedded (Human) Builders for the Cloud Native Frontier with SOUTHWORKS

Event: Tech Field Day at KubeCon North America 2025

Appearance: Southworks Presents at Tech Field Day at KubeCon North America 2025

Company: SOUTHWORKS

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Personnel: Johnny Halife

Most SRE teams were designed to ensure uptime, not to evolve products. They monitor systems but often lack the context to influence architecture or design. This segment examines why proximity — being part of the product team — is what transforms reliability into progress. When engineers operate as embedded partners, they surface deeper insights, close the gap between observation and action, and help the team own the outcome end to end.

Johnny Halife from SOUTHWORKS introduced Cloud Scouts, a new service designed to bridge the gap between SRE teams and product development teams. He explained how traditional SRE practices, while valuable for maintaining uptime and monitoring applications, often operate in silos, leading to “ticket battles” and a lack of context when issues arise. This SOUTHWORKS service addresses the evolving need for engineers who understand both the application and the platform, and can work directly with development teams to identify the root cause of problems, not just surface-level errors.

Cloud Scouts are senior software engineers who are embedded within customer teams, possessing domain expertise and the ability to quickly prototype solutions. They actively engage with software engineers, platform engineers, and architects to foster better communication and collaboration. These scouts also use AI-powered “companions” to analyze telemetry data, identify patterns, and propose fixes, while always maintaining human oversight to ensure accuracy and alignment with business goals. It is intended to provide hands-on support, rather than a consulting position.

The goal of Cloud Scouts is not to replace existing SRE or development teams, but to enhance their effectiveness by facilitating knowledge sharing, promoting end-to-end ownership, and accelerating the adoption of new technologies, such as AI. The engagement begins with a three-month assessment to evaluate the current state and establish a baseline, to achieve measurable improvements in areas such as alert fatigue, time to resolution, and overall system reliability. SOUTHWORKS emphasizes transparency and a collaborative approach, empowering customers to mature their practices and become more self-sufficient over time.


Cisco AI Networking Vision and Operational Strategies by Arun Annavarapu

Event: Networking Field Day 39

Appearance: Cisco Presents at Networking Field Day 39

Company: Cisco

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Personnel: Arun Annavarapu

Arun Annavarapu, Director of Product Management for Cisco’s Data Center Networking Group, opened the presentation by framing the massive industry shift towards AI. He noted that the evolution from LLMs to agentic AI and edge inferencing creates an AI continuum that places unprecedented demands on the underlying infrastructure. The network is the key component, tasked with supporting new scale-up, scale-out, and even scale-across fabrics that connect data centers across geographies. Anavarpu emphasized that the network is no longer just a pipe. It must be available, lossless, resilient, and secure. He stressed that any network problems will directly correlate to poor GPU utilization, making network reliability essential for protecting the significant financial investment in AI infrastructure.

Cisco’s strategy to meet these challenges is to provide a complete, end-to-end solution that spans from its custom silicon and optics to the hardware, software, and the operational model. A critical piece of this strategy is simplifying the operating model for these complex AI networks. This model is designed to provide easy day-zero provisioning, allowing operators to deploy entire AI fabrics with a few clicks rather than pages of configuration. This is complemented by deep day-two visibility through telemetry, analytics, and proactive remediation, all managed from a single pane of glass that provides a unified view across all fabric types.

To deliver this operational model, Cisco offers two primary form factors. The first is the Nexus Dashboard, a unified, on-premises solution that allows customers to manage their own provisioning, security, and analytics for AI fabrics. The second option is HyperFabric AI, a SaaS-based platform where Cisco manages the management software, offering a more hands-off, cloud-driven experience. Anavarpu explained that both of these solutions can feed data into higher-level aggregation layers like AI Canvas and Splunk. These tools provide cross-product correlation and advanced analytics, enabling the faster troubleshooting and operational excellence required by the new age of AI.