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.

Susan Laine of Quest Software, global field chief technology officer CTO, discusses AI governance and data readiness on AppDevANGLE. This episode focuses on governance and trusted data in enterprise artificial intelligence AI deployments. Laine brings practical experience in data management and modernization and they outline challenges related to data readiness, semantic layers, model retraining and operationalizing AI. Hosts from AppDevANGLE and Paul Nashawaty of theCUBE Research contribute additional perspective.Laine explains how metadata, data products and a control plane factor into moving validated models safely into production while mitigating risks from agentic AI behavior. Key takeaways include a widening governance gap and the need for durable, change-ready frameworks. Paul Nashawaty of theCUBE Research observes that many organizations rely on public AI tools while lacking enterprise-wide governed frameworks. Laine recommends building trust through semantic layers, reusable data products and a control plane and they suggest using AI for AI to scale safe data modeling and maintain production reliability. The discussion highlights implications for data governance, data strategy, machine learning operations MLOps and artificial intelligence operations AIOps in enterprise AI modernization.

This episode examines how artificial intelligence, abbreviated as AI, agents transform software delivery to accelerate developer productivity and improve developer experience. Paul Nashawaty of theCUBE Research hosts the discussion with Deepak Singh of AWS and Steve Charza of Amazon.com. The conversation explores Kiro's capabilities, spec-driven workflows, agent steering, context as code and real-world applications of agentic automation to scale engineering.Nashawaty reports research showing 65% of respondents spend up to 20% of engineering time on net new innovation, highlighting a substantial productivity gap. Singh observes that teams that redesign workflows and give agents clear intent and context see outsized gains; they recommend spec-driven approaches and agent steering to capture those gains. Charza reports median shipping speed improvements of 4.5× and cites spec-driven development combined with Kiro and agentic automation as enabling features to ship months faster.

This episode examines Meko and shared memory for agentic artificial intelligence knowledge infrastructure. The guest, co-founder and CEO of Yugabyte, draws on a decade of experience in distributed systems, databases and cloud-native architecture. In conversation with Paul Nashawaty of theCUBE Research on AppDev ANGLE, they explore Yugabyte's new product Meko, agent-native data infrastructure, shared memory for agent collaboration and how data architecture underpins agentic AI deployments and enterprise use cases.The co-founder and CEO of Yugabyte explains that the primary limitation on agentic AI is data infrastructure rather than models and that shared observable memory across agents reduces token costs and operational complexity. They describe how Meko delivers auditability, multi-tenant scalability and efficiency while promoting collective memories and traceable reasoning to support compliance, return on investment and more predictable enterprise agent workflows. The discussion highlights implications for observability, vector databases, PostgreSQL compatibility and open source strategies for enterprise adoption.Watch to understand the role of data architecture in scalable agent deployments and practical factors to consider when implementing agent-native knowledge infrastructure in production environments.

This discussion examines identity security for artificial intelligence agents and the role of zero trust in protecting enterprise environments. Geoff Mattson of SecureAuth, chief executive officer, joins Paul Nashawaty of theCUBE Research, practice lead and principal analyst, to examine how SecureAuth addresses agentic threats as AI agents expand the enterprise attack surface. Mattson highlights passkeys, behavioral analytics and continuous identity evaluation as core components, and they describe combining static authorization policies with behavioral profiling and analytics driven step up and step down authentication to reduce phishing, minimize user friction and mitigate rogue agent behavior. Nashawaty underscores rising attack volumes and recommends identity first zero trust architectures and real time controls.Key takeaways include treating agents as dynamic identities that require transaction level evaluation, according to Mattson. They emphasize that combining static policies with behavioral profiling and continuous identity evaluation reduces risk while preserving user experience. Nashawaty and theCUBE Research advocate identity first zero trust, real time controls and stronger authentication models to manage agentic threats across finance, healthcare and retail. This conversation addresses authentication, authorization and identity and access management within modern cybersecurity strategies.