Technically Speaking with Chris Wright

Red Hat
  • 5.0 (2)
  • Business
  • Updated Monthly

Struggling to keep pace with the ever-changing world of technology? For experienced tech professionals, making sense of this complexity to find real strategic advantages is key. This series offers a clear path, featuring insightful, casual conversations with leading global experts, innovators, and key voices from Red Hat, all cutting through the hype. Drawing from Red Hat's deep expertise in open source and enterprise innovation, each discussion delves into new and emerging technologies-- from artificial intelligence and the future of cloud computing to cybersecurity, data management, and beyond. The focus is on understanding not just the 'what,' but the important 'why' and 'how': exploring how these advancements can shape long-term strategic developments for your organization and your career. Gain an insider’s perspective that humanizes complex topics, helping you anticipate what’s next and make informed decisions. Equip yourself with the knowledge to turn today's emerging tech into valuable, practical strategies and apply innovative thinking in your work. Tune in for forward-looking discussions that connect the dots between cutting-edge technology and real-world application, leveraging a rich understanding of the enterprise landscape. Learn to navigate the future of tech with confidence.

  1. 4d ago

    Can agentic AI patch the internet? ft. Mike McGrath

    Every CTO and CSO faces a daunting reality: while engineering teams write clean, audited code, modern applications rely on thousands of open source dependencies they didn't write. When a critical Common Vulnerabilities and Exposures (CVE) hits one of those deep dependencies, IT leaders are trapped between two bad choices: forcing an unvalidated framework upgrade that risks breaking production, or running vulnerable software in production. In this episode of Technically Speaking, Red Hat CTO Chris Wright sits down with Mike McGrath, Vice President of Lightwell Engineering at Red Hat, to discuss how Red Hat is working to eliminate that choice entirely. Mike shares his journey from volunteering with the Fedora project in the 1990s to leading core platforms at Red Hat, before diving into the origin and mission of Lightwell, an initiative designed to industrialize vulnerability scanning and surgical remediation across the open source application ecosystem. Together, Chris and Mike explore the "Mythos Moment" in AI-driven vulnerability discovery, the power and pitfalls of agentic Large Language Model (LLM) workflows, and why surgical patching is essential for maintaining enterprise runtime stability. They also highlight Red Hat’s human-centric commitment to contributing security fixes back to upstream open source communities responsibly, ensuring maintainers aren't overwhelmed with automated bug reports while making open source software safer for everyone. Tune in to discover how AI-powered automation, validated package pipelines, and surgical patch management are reshaping software supply chain security and giving enterprise leaders true peace of mind.

  2. Sep 2

    How Red Hat cleared IT debt for scalable AI ft. Marco Bill

    While conversations around enterprise AI tend to focus on high-level possibilities, less attention is given to the foundational plumbing required to make systems actually run. What happens when an enterprise's financial data is copied across 73 different spreadsheets or bogged down by thousands of legacy virtual machines? In this episode of Technically Speaking, host and Red Hat CTO Chris Wright sits down with Red Hat CIO Marco Bill to peek behind the curtain of enterprise IT transformation and explore why the secret to AI readiness is radical simplification. Building on 20 years of productive friction between engineering and IT, Marco shares an insider's look at what it really takes to clean up legacy technical debt. From standardizing workloads on Red Hat OpenShift to taking the bold step of decommissioning 2,400 unused dashboards, Marco explains how reducing infrastructure and data complexity creates the clean, single source of truth necessary for enterprise AI. Chris and Marco dive into the real-world trajectory of enterprise AI adoption—moving from associate productivity boosts to high-ROI business process transformation. The conversation also tackles the modern pitfalls of technology governance. They discuss how overly dense legal policies accidentally fuel "shadow AI," and why organizations must replace legalese with automated security guardrails and developer-friendly workflows. Plus, they examine why the explosive demand for AI compute and accelerators is bringing bare metal infrastructure full circle within hybrid cloud strategies. Tune in to discover why true innovation often looks like subtraction, and learn how enterprise leaders can clean up their data foundations today to build scalable, secure, and AI-native organizations for tomorrow.

  3. Aug 5

    Standardizing the AI stack with PyTorch ft. Steven Pousty

    You might view PyTorch simply as a tool for data scientists building models, but it has become a critical infrastructure bridge for modern AI-powered workloads. Acting as the functional "kernel" of the modern AI stack, PyTorch handles the complex mathematical abstractions and hardware offloading necessary to turn raw computing power into scalable enterprise systems. In this episode of Technically Speaking with Chris Wright, Red Hat Chief Technology Officer Chris Wright sits down with Steve Pousty, Principal AI Community Architect in the Red Hat Open Source AI Program Office. Together, they map out how open source is driving the evolution of data architecture and why Red Hat is focusing heavily on this ecosystem. They draw clear historical parallels to the early days of Linux and Kubernetes, outlining how the enterprise landscape is rapidly transitioning from raw upstream projects to fully supported, standardized AI distributions.The conversation explores the key architectural pillars within the PyTorch Foundation ecosystem. Chris and Steve break down the importance of distributed computing using cluster systems like Ray, hardware-agnostic model serving powered by vLLM, and optimization frameworks like Helion DSL that slash execution runtime constraints at scale. They also detail the introduction of Kubernetes-native distributed inference engines like llm-d and explain how open source governance establishes a neutral playing field that provides true hardware choice for the data center. Tune in to discover how to transition your AI strategies from lab experiments to robust enterprise deployments.

  4. Jul 1

    Defining sovereign AI with open source ft. Jered Floyd

    What does digital sovereignty actually mean when most AI runs on someone else's black box? In this episode of Technically Speaking, Red Hat CTO Chris Wright talks with Jered Floyd from the Red Hat Field CTO team about what sovereignty really requires in the age of AI infrastructure. They examine the four pillars of modern sovereign operations: data sovereignty, operational sovereignty, technology sovereignty, and assurance sovereignty. Along the way, Chris and Jered also take on a common misconception: that digital sovereignty is just a compliance checkbox, solved by hosting data in the right region. Real sovereignty is about control, autonomy, and resiliency across your entire stack, not just where your data sits. The discussion also gets into why this has become urgent in just the last year or so, and why open source is turning out to be one of the few real paths to keeping that control. Tune in to hear why smaller, open-weight models are challenging massive black-box AI infrastructure, and how organizations can prepare for upcoming regulatory compliance boundaries, like the Digital Operational Resilience Act (DORA), within next-generation agentic workflows. If you're thinking about how much of your AI stack you actually own versus rent, this one's worth your time.

  5. Jun 3

    Inside open source AI strategy ft. Steve Watt

    Go behind the scenes of Red Hat's internal innovation engine to discover how we evaluate emerging open source tech and choose exactly where to place our next major technology bets. In this episode of Technically Speaking, Red Hat Chief Technology Officer Chris Wright sits down with Steve Watt, Vice President of the Office of the CTO at Red Hat, for a clear, "200-level" look at what's coming down the road. Together, they map out how Red Hat’s pathfinding group tracks open source innovations and shapes raw clay into enterprise-ready layouts. Steve shares how his teams follow proven open source innovators and build strategic university partnerships to stay ahead of an AI cycle that changes every single week. Dive into the mechanics of composable intelligence, where the conversation explores the vLLM Semantic Router. This open source project, incubated within Red Hat, allows businesses to selectively route inference requests across specialized small language models or fall back to larger cloud models based on real-time cost, data privacy, and semantic analysis. Chris and Steve also break down how confidential computing protects data, showing how secure enclaves can keep proprietary model weights safe even when running in third-party environments. Finally, discover how the hardware landscape is moving past GPU scarcity. Learn how new matrix multiplication instructions are opening up inference workloads on modern x86 CPUs, how specialized accelerators like Cerebras, Grok, and IBM Spyre are meeting strict data center power budgets, and how the OpenReg project makes it easier for silicon startups to integrate with PyTorch. Tune in to see why the real enterprise AI secret sauce is no longer just the model itself, but the open source infrastructure backing it.

  6. Jan 7

    Build a production-ready AI toolbox ft. Cat Weeks

    While generative AI demos are flashy, moving those capabilities into a reliable, secure enterprise production environment is a different ballgame. In this episode of Technically Speaking, Red Hat CTO Chris Wright sits down with longtime Red Hatter and engineering leader Cat Weeks to dismantle the myth that you need a massive ""Frontier Model"" for every task. Together, they explore the practical realities of enterprise AI, advocating for a ""right tool for the job"" approach. The conversation dives deep into the necessity of moving away from monolithic models toward a diverse fleet of specialized Small Language Models (SLMs) and agentic workflows. They also tackle the critical ""illities"", reliability, security, and portability, that often derail projects after the proof-of-concept phase. Beyond the code, Chris and Cat discuss the human and process challenges of AI adoption, from navigating employee fear to ensuring data stewardship. Tune in to discover the differences between RAG and fine-tuning, how to manage agent identities, and why the future of enterprise AI belongs to a toolbox of specialized solutions, not just one giant hammer.

  7. 12/03/2025

    Platform engineering for AI agents ft. Tushar Katarki

    A decade ago, the shift from monolithic applications to microservices created an explosion of complexity that only Kubernetes could tame. Today, the enterprise is facing a similar inflection point. We are moving beyond simple chatbots to "Agentic AI"—autonomous systems capable of planning, tool calling, and executing complex workflows. But with this innovation comes fragmentation: how do you manage security, memory, observability, and scale across thousands of agents and models? In this episode of Technically Speaking, Red Hat CTO Chris Wright sits down with fellow Red Hatter Tushar Katarki to explore the critical infrastructure needed for the next wave of AI. They discuss why the agentic era needs its own "Kubernetes," the rise of the Model Context Protocol (MCP) for connecting data, and the emerging concept of an "Agent Mesh" to handle identity and security. Tune in to discover how platform engineering can bridge the gap between AI innovation and production stability, enabling enterprises to build scalable, open platforms for the future of automation.

  8. 11/05/2025

    Driving healthcare discoveries with AI ft. Jianying Hu

    We often hear about AI's potential to generate text and code, but its application in healthcare and life sciences promises a more profound impact: solving our most fundamental challenges in disease and medicine. This isn't just about applying existing LLMs; it's about building entirely new foundation models that understand the complex language of biology itself. To explore this new frontier, Red Hat CTO Chris Wright speaks with Dr. Jianying Hu, an IBM Fellow, Global Science Leader of AI for Health, and Director of Healthcare and Life Sciences Research at IBM. Dr. Hu shares her extensive insights and expertise on: •  The fundamental shift from general-purpose LLMs to domain-specific AI foundation models that learn the complex, multimodal language of biology. •  How these new models power ""in silico"" simulations to accelerate drug discovery, validate new experiments, and test therapeutic efficacy. •  The critical role of collaboration in applying AI, as seen in the IBM & Cleveland Clinic Discovery Accelerator, to create models that lead to personalized medicine. •  Why open science and shared community benchmarks are essential for driving the next wave of medical breakthroughs. Join in as they explore how this foundational, collaborative work is creating a new paradigm for scientific discovery. And discover why the future of medicine isn't just about a single AI model, but about building an open, iterative ecosystem that combines deep domain expertise with the power of AI to understand biology from the ground up.

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Struggling to keep pace with the ever-changing world of technology? For experienced tech professionals, making sense of this complexity to find real strategic advantages is key. This series offers a clear path, featuring insightful, casual conversations with leading global experts, innovators, and key voices from Red Hat, all cutting through the hype. Drawing from Red Hat's deep expertise in open source and enterprise innovation, each discussion delves into new and emerging technologies-- from artificial intelligence and the future of cloud computing to cybersecurity, data management, and beyond. The focus is on understanding not just the 'what,' but the important 'why' and 'how': exploring how these advancements can shape long-term strategic developments for your organization and your career. Gain an insider’s perspective that humanizes complex topics, helping you anticipate what’s next and make informed decisions. Equip yourself with the knowledge to turn today's emerging tech into valuable, practical strategies and apply innovative thinking in your work. Tune in for forward-looking discussions that connect the dots between cutting-edge technology and real-world application, leveraging a rich understanding of the enterprise landscape. Learn to navigate the future of tech with confidence.

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