This episode of AppDev ANGLE examines Broadcom's VMware partner reshuffle and the implications for total cost of ownership, VMware Cloud Foundation 9 and Tanzu integration, and preparing artificial intelligence-ready infrastructure. Jamie Konzelman of RapidScale, field chief revenue officer, joins Paul Nashawaty of theCUBE Research, practice lead and principal analyst, to discuss partner ecosystem dynamics and migration strategy. Konzelman draws on field revenue and cloud operations experience and emphasizes that credible VMware migration requires an application-portfolio program rather than a simple hypervisor swap; they outline practical considerations for workload placement, data locality and lifecycle governance. Nashawaty presents theCUBE Research findings that cost and embedded complexity are primary decision drivers; they highlight total cost of ownership as a dominant factor and note underutilization of VMware Cloud Foundation 9 bundles.The conversation analyzes operational and skills challenges of migration, converged platform capabilities from VCF 9 and Tanzu integration, private versus public cloud trade-offs, and practical steps for application modernization and platform engineering. The discussion addresses cloud migration strategy, TCO optimization, and building AI-ready infrastructure to support modern workloads and platform services. Watch for actionable insights on partner strategy, platform consolidation, workload placement and governance to inform enterprise modernization plans.

This episode of AppDevANGLE explores balancing generative artificial intelligence and mathematical optimization to improve decision making in commercial and educational settings. Jerry Yurchisin of Gurobi Optimization, manager of decision intelligence strategy, explains how mathematical optimization complements generative artificial intelligence in real world decision problems. Yurchisin states that AI excels at code generation, model drafting, debugging and research; they emphasize that optimization delivers provably optimal decisions under constraints and supports prescriptive analytics for complex scheduling and supply chain decisions.Paul Nashawaty of theCUBE Research, practice lead and principal analyst, hosts the conversation and examines use cases such as supply chain design, scheduling and curriculum integration while highlighting the distinct roles of optimization and language models within an AI toolkit. Nashawaty emphasizes curriculum gaps and the need for AI literacy; they recommend starting with decision framing, adding guardrails and teaching students to validate and trust AI outputs. Yurchisin recommends Gurobi's gurobi.com/learn resources and classroom games for hands-on adoption and practical modeling experience.

This conversation examines governing artificial intelligence-generated code at scale. Itamar Friedman of Qodo, chief executive officer and co-founder, and Paul Nashawaty of theCUBE Research, practice lead and principal analyst, explore agentic development, AI-assisted coding, verification bottlenecks and how engineering teams design an AI software development life cycle that combines coding agents, verification swarms and memory systems to preserve development velocity while increasing trust.Key takeaways include:- Nashawaty explains that the primary bottleneck shifts from code generation to verification and governance. They emphasize the need for scalable verification frameworks and policy controls to manage AI-generated code.- Friedman recommends a layered approach in which coding agents pair with verification agents and contextual memory so only disputed items surface for human review. They stress preserving velocity while increasing trust.- The conversation stresses continuous governance integrated across continuous integration and continuous deployment, telemetry and security pipelines to enable automated checks and traceability.- Engineering managers are urged to review recent production incidents and define practical go/no-go verification checks that map to observable telemetry and security signals.

Barry Rosen of Interaction Associates joins Paul Nashawaty and theCUBE Research team to discuss collaborative intelligence and the human delivery gap that artificial intelligence cannot close in application development. Rosen describes Interaction Associates' work in training, team consulting and high-stakes meeting facilitation and explains why facilitation operates as a discipline that reduces decision-making cycle time. They emphasize the role of facilitation, emotional and social intelligence and stakeholder alignment in shaping software delivery.Hosts frame the conversation with theCUBE Research findings about innovation time loss in engineering teams. Key takeaways emphasize people and process over tooling. According to theCUBE Research, 65% of engineering teams spend up to 20% of their time on net-new innovation. Rosen recommends distributing collaborative intelligence across organizations, upskilling project managers in facilitation and stakeholder alignment and validating AI outputs such as meeting minutes through human review to prevent misalignment and accelerate informed decisions.

In this AppDevANGLE conversation, an instructor of Schiller International University who teaches big data, IT and artificial intelligence joins hosts of theCUBE Research to discuss how universities prepare graduates for AI-facing roles. The instructor outlines approaches for integrating prompt engineering as a practical discipline, applying creative problem solving frameworks, designing classroom exercises and aligning curricula with employer expectations for AI-enabled development teams.The instructor emphasizes that prompt engineering requires repeated practice and domain understanding, and that structured creative problem solving helps students manage AI hallucinations and verify sources. The analysts note that hiring and investing in entry-level talent remains critical because AI shifts cognitive workload toward innovation; employers should balance generalist capabilities with specialist depth when building teams.Topics include curriculum design, assessment strategies, employer expectations and talent development for AI-enabled roles. Viewers receive practical guidance on integrating prompt engineering exercises into coursework, measuring competence and creating clear pathways from university programs to application development and DevOps teams.Subscribe for further AppDevANGLE episodes and analysis from theCUBE Research on AI, application development and workforce development.

In this AppDev Angle episode, Sudeep Goswami of Traefik Labs and Paul Nashawaty of theCUBE Research join hosts to examine provable trust and governance for autonomous artificial intelligence, AI, agents. The discussion focuses on agent governance, delegation and cryptographic evidence relevant to enterprise and regulated deployments.Goswami provides expertise in agent governance and delegation backed by cryptographic evidence. They address agent-to-agent delegation, policy enforcement and sovereignty and compare observability with provability while outlining architectural approaches for deploying agentic workflows at scale.Nashawaty presents a risk-based approach to model selection and deployment location informed by SUSE analysis. They emphasize integrating policy enforcement, observability and provenance within customer-controlled infrastructure for regulated environments that combine connected and air-gapped systems.Key takeaways include the need for cryptographically verifiable logs and independent witnesses to prevent tampering according to Goswami, a risk-based framework for model choice and deployment location according to Nashawaty and SUSE analysis and the importance of integrating policy enforcement, observability and provenance within customer-controlled infrastructure to support sovereignty and compliance. The episode highlights architectural and operational considerations for enterprises adopting autonomous AI agents at scale.

Paul Nashawaty of theCUBE Research hosts an AppDevANGLE episode on Dynatrace's acquisition of Arize AI and the evolving role of observability in moving from detection to action.Steve Tack of Dynatrace and Aparna of Arize AI join Nashawaty and the AppDevANGLE team to explore how observability adapts for the artificial intelligence era. The discussion examines agent evaluation, AI telemetry and the Phoenix open source project, platform consolidation pressures and the shift from dashboards to agent-driven operational workflows across cloud-native and AI-infused stacks.Key takeaways emphasize integrated AI observability as a remedy for tool sprawl and a path to autonomous resolution. Nashawaty says enterprises prioritize security and compliance automation in internal developer platforms. Tack explains the Arize acquisition accelerates Dynatrace's ability to deliver shared context and actionability; they connect that capability to faster operational response and reduced mean time to resolution. Aparna highlights agent evaluation and Phoenix as foundational for measuring and improving non-deterministic AI features; they underscore the importance of robust model telemetry for production reliability.The conversation also addresses machine learning operations and operational considerations for model telemetry and observability in production environments.

In this episode Paul Nashawaty of theCUBE Research, practice lead and principal analyst, hosts a conversation with Megan Carrigan of Valtech, senior vice president of strategy and innovation, on agentic commerce, the evolution of digital experience platforms or DXP and responsible artificial intelligence or AI governance in customer experience. The discussion focuses on turning AI ambitions into measurable customer outcomes and on how brands should design conversational versus autonomous experiences for consumers.Carrigan emphasizes meeting consumers where they are, beginning with simple conversational experiences to build trust and learn behavior. They recommend favoring an orchestration layer over all-in-one platform migrations to leverage individual platform strengths. Nashawaty highlights that governance, structured content for agents and a purposeful strategy are essential to move from experimentation to implementation. The episode underscores the role of DXP as connective tissue for content and data and offers practical guidance on agentic commerce strategy, AI governance and customer experience design.

This AppDevANGLE conversation examines how enterprise artificial intelligence shifts from model-centric metrics to agent-centric experience. Paul Nashawaty of theCUBE Research, practice lead and principal analyst, hosts a representative of Conviva to discuss agentic AI experience and real-time observability.Nashawaty and the Conviva representative examine real-time experience intelligence, multi-agent pipelines and how streaming-era observability lessons apply to agent deployments. They address pattern-based conversation analysis, the limits of deterministic tooling, large-scale production concerns and operational readiness for agentic workflows.Key takeaways include that real-time full-census observability is essential for agent deployments and legacy monitoring tools are inadequate, according to Nashawaty. The Conviva representative emphasizes that measuring agent experience rather than only whether an outcome is reached drives user retention and reduces cost through token optimization. Organizations should prioritize conversational pattern extraction, real-time diagnostics and treating agent experience as a primary competitive surface to improve customer experience and operational efficiency.

This conversation examines orchestration of artificial intelligence and customer experience and operationalizing AI at scale. It focuses on translating promising technologies into measurable customer outcomes and on the governance operating models and workforce design that enable scalable AI operations.Molly Moore of Liveops, president and chief operating officer, joins AppDevANGLE to discuss moving enterprises from experimentation to execution. Moore explains how they combine technology, operational design, governance and a global workforce to deliver consistent customer outcomes. They emphasize orchestration over automation and advise organizations to start with operating models, define ownership, establish governance and redesign workflows before applying AI.Paul Nashawaty of theCUBE Research, practice lead and principal analyst, hosts the conversation with the AppDevANGLE hosts and provides data that reinforces this approach, noting AI often exposes broken processes. Nashawaty highlights that mature organizations prioritize resolution, trust and measurable customer outcomes rather than token usage or speed alone.This episode is relevant for leaders responsible for enterprise AI orchestration, customer experience strategy, AI governance and operationalizing AI.

Software supply chain security presents an architecture problem. Sudeep Goswami of Traefik Labs appears on AppDevANGLE, produced by theCUBE Research, to discuss Traefik Labs' role in cloud native proxy and gateway solutions and the company's Distro Zero initiative. Goswami explains their team's experience with Kubernetes deployments and describes the architectural shift from vulnerability detection toward attack surface reduction across application programming interface, artificial intelligence and MCP gateway workloads. They outline how Distro Zero reduces the attack surface by shipping a minimal memory-safe binary and by simplifying software bill of materials management, SBOM, while easing Federal Information Processing Standard 140-3, FIPS 140-3 and broader compliance efforts.Paul Nashawaty of theCUBE Research reports that 58% of respondents rely on vulnerability scanning while 47% list software supply chain security as a top investment priority. Nashawaty adds that 54% cite the National Institute of Standards and Technology framework, NIST and 46% cite the EU Cyber Resilience Act.Goswami emphasizes technical and operational implications for cloud native architectures, Kubernetes deployments and gateway workloads, including API gateway, AI gateway and MCP use cases. They discuss best practices for supply chain security, vulnerability management, SBOM handling and compliance in enterprise environments.