The Reasoning Show

Massive Studios
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The Reasoning Show AI moves fast. Thinking clearly matters more. The Reasoning Show cuts through the hype to explore how the smartest people in enterprise AI actually make decisions — the strategy, the tradeoffs, and the hard lessons no press release mentions. Every week, hosts Aaron Delp and Brian Gracely sit down with the founders building the tools, investors funding the shift, and operators running AI in the real world. Not hype. Not panic. Just clear-headed conversations with people who have to make actual decisions. Because the AI revolution isn't just happening. It's being reasoned through.  New shows every Wednesday and Sunday.  Topics: Enterprise AI strategy · LLMs in production · AI leadership · Agentic AI ·  Digital Sovereignty · Machine Learning · AI startups ·  Cloud Computing 

  1. 2日前

    How AI is Transforming Software Development

    SUMMARY:  Discover how AI is transforming software development and what it means for engineering leaders.  GUEST: Jeff Keyes, Field CTO at AllStacks  SHOW: 1017 SHOW TRANSCRIPT: The Reasoning Show #1017 Transcript SHOW VIDEO: https://youtu.be/cXPu8iWeB0k SHOW SPONSORS: ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES: Topic 1 - Welcome to the show. Tell us a little bit about your background, and what you focus on these days at AllStacks.  Topic 2 - You’ve been talking to a lot of engineering leaders using AI coding tools—what’s the most surprising gap you’re seeing between increased code generation and actual delivery outcomes? Topic 3 - Why does increasing developer output with AI often lead to more debugging, duplication, or cleanup instead of faster delivery? Topic 4 - You’ve described an ‘invisible rework loop’—can you walk us through what that looks like inside a modern engineering team? Topic 5 - As code generation gets easier, where does the real bottleneck shift in the software delivery lifecycle? Topic 6 - How do unclear product or engineering specifications get amplified in an AI-assisted development environment? Topic 7 - If traditional metrics like lines of code or velocity are becoming misleading, what should engineering leaders actually measure to know if AI is improving delivery? Topic 8 - What does a ‘healthy’ AI-assisted development workflow look like 12–18 months from now? FEEDBACK? Email: show @ reasoning dot showBluesky: @reasoningshow.bsky.socialTwitter/X: @ReasoningShowInstagram: @reasoningshowTikTok: @reasoningshow

    34 分鐘

  2. 5日前

    AI SRE for Complex Systems

    SUMMARY: With the explosion of AI-generated code and applications, the modern SRE requires an AI-native approach to managing complex systems.  GUEST: Anish Agarwal - CEO/Cofounder of Traversal SHOW: 1016 SHOW TRANSCRIPT: The Reasoning Show #1016 Transcript SHOW VIDEO: https://youtu.be/hF3MCRDhMno SHOW SPONSORS: Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES: Traversal (homepage)Topic 1 - Welcome to the show. Tell us a little bit about your background, and what you focus on these days at Traversal.  Topic 2 - AI is dramatically accelerating code generation, but not improving production outcomes. What’s fundamentally breaking in the traditional SRE model—and where do you see the biggest friction between speed and reliability? Topic 3 - What are the most common failure patterns or mistakes you’re seeing in production from AI-generated code—and what’s driving them? Topic 4 - AI can generate functional code, but it often lacks context about how systems behave in production. How is this changing what ‘good observability’ needs to look like? Topic 5 - How do you see SRE evolving in an AI-first world? Does it become more automated, more policy-driven, or even partially autonomous? Topic 6 - For organizations that want to embrace AI-assisted development but avoid production chaos, what are the most important guardrails they should put in place? Topic 7 - If we fast-forward 2–3 years, what does a ‘modern’ production stack look like in a world where most code is AI-generated? What capabilities become absolutely essential? In one sentence—what’s the #1 thing a CTO should do right now? FEEDBACK? Email: show @ reasoning dot showBluesky: @reasoningshow.bsky.socialTwitter/X: @ReasoningShowInstagram: @reasoningshowTikTok: @reasoningshow

    33 分鐘

  3. 4月1日

    The Future of Service belongs to Self-Improving AI

    SUMMARY:  Today’s episode is all about a transformation happening in customer service—one that’s moving us from static systems and scripted workflows into something far more dynamic: AI systems that can actually learn and improve over time. GUEST: Shashi Upadhyay (President of Product, Engineering, and AI at Zendesk) SHOW: 1015 SHOW TRANSCRIPT: The Reasoning Show #1015 Transcript SHOW VIDEO: https://youtu.be/IQaxE-DjIpo SHOW SPONSORS: ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES: The future of service belongs to self-improving AITopic 1 - Welcome to the show. Tell us a bit about your background and your focus today.  Topic 2 - You describe this moment as a shift from systems of record to intelligent systems of action. What’s fundamentally broken in today’s customer service model that’s forcing this transition now? What changed in the last 2–3 years to make this possible? Topic 3 - There’s been a lot of AI in customer service that overpromised and underdelivered. What are the biggest gaps between what customers actually need—like resolution—and what legacy automation has been delivering? Topic 4 - The concept of a “self-improving” system is really powerful. What’s actually new here—what enables AI to improve with every interaction without constant human tuning? Topic 5 - You’ve moved from assistive copilots to what you call “agentic AI” that can resolve issues end-to-end. Where are we today on that journey—and what still requires human involvement? Topic 6 - Voice has historically been one of the hardest channels to automate. What changes with this new generation of AI that makes even complex, multi-step voice interactions solvable? Topic 7 - If we fast-forward 2–3 years, what does a “best-in-class” customer service experience look like in an AI-first world? FEEDBACK? Email: show @ reasoning dot showBluesky: @reasoningshow.bsky.socialTwitter/X: @ReasoningShowInstagram: @reasoningshowTikTok: @reasoningshow

    34 分鐘

  4. 3月29日

    AI News of the Month for March 2026

    SUMMARY:  Brian (@bgracely) and Brandon Whichard (@bwhichard, Software Defined Talk and Failover Media) discuss the biggest AI news stories from the month of March, 2026.  SHOW: 1014 SHOW TRANSCRIPT: The Reasoning Show #1014 Transcript SHOW VIDEO: https://youtu.be/XwyAC-hxOQY SHOW SPONSORS: VENTION - Ready for expert developers who actually deliver? Visit ventionteams.comSHOW NOTES: Links to all the AI News covered in this months showFEEDBACK? Email: show @ reasoning dot showBluesky: @reasoningshow.bsky.socialTwitter/X: @ReasoningShowInstagram: @reasoningshowTikTok: @reasoningshow

    40 分鐘

  5. 3月25日

    Living the Claude-centric Life

    SUMMARY: With @bwhichard, we dig into how daily work-life changes when you make @AnthropicAI @claudeai the center of all workflow activities.  SHOW: 1013 SHOW TRANSCRIPT: The Reasoning Show #1013 Transcript SHOW VIDEO: https://youtu.be/zEmEH0t67js SHOW SPONSORS: VENTION - Ready for expert developers who actually deliver? Visit ventionteams.comSHOW NOTES: Topic 1 - How long have you been living the Claude-life, and when did it dawn on you to make this central to your day-to-day activities?  Topic 2 - What were the biggest hurdles you had to overcome before you trusted the system and started letting it have ownership over tasks and workflows? Topic 3 - What are some of your best practices in terms of machine setup, how or where you store data, how you decide what to give it access to? Walk me through your thoughts around things like keeping things simple, where to be complex, how you think about security, etc. Topic 4 - How are you learning to give it more responsibilities, or just figure out new ways to be productive with it?  Good resources you’re pulling from? Any tips to make it use less tokens?Skills marketplaces?Topic 5 - What have been some of the biggest barriers to successful adoption, or just areas where you’re still struggling to get it to do the things you want? Or are you still in the learning curve stage and things just keep growing on one another? Topic 6 - If you took the knowledge and skills you have now in Claude-life into your day-job, how do you see yourself working, as well as working with the rest of your team/teams? Would it bother you if you didn’t think they were using AI tools as much?  FEEDBACK? Email: show @ reasoning dot showBluesky: @reasoningshow.bsky.socialTwitter/X: @ReasoningShowInstagram: @reasoningshowTikTok: @reasoningshow

    37 分鐘

  6. 3月22日

    Three Thoughts from NVIDIA GTC 2026

    SUMMARY: We dig into the NVIDIA GTC keynote and highlight three things - accelerated computing for everything, the complexity of the new inference stack, and NVIDIA’s “open” software stack including NemoClaw. SHOW: 1012 SHOW TRANSCRIPT: The Reasoning Show #1012 Transcript SHOW VIDEO: https://youtu.be/aXOr91q76yM SHOW SPONSORS: VENTION - Ready for expert developers who actually deliver? Visit ventionteams.comSHOW NOTES: NVIDIA GTC 2026 (Keynote)NVIDIA NemoClaw - OpenClaw + OpenShell + NVIDIA Agent ToolkitNVIDIA adds Groq LPU to their rack systemsNVIDIA to invest $26B in Open Weight ModelsInterview with Jensen about Accelerated Computing (Stratechery) Topic 1 - Jensen’s trying to paint the bigger picture of accelerated computing everywhere (robotics, autonomous driving, gen-ai, physical ai - but also just everyday enterprise apps). Everything is about keeping the stock price up, and margins high. The stock price provides the warchest to fight off all foes.  Topic 2 - The inference architecture is a complex mix of GPUs, CPUs, ASICs/LPUs, high-speed networking and seems very different from the training architecture. How big is the burden on data center providers? What are the inference alternatives emerging?  Topic 3 - Jensen talked a lot about OpenClaw and eventually about NVIDIA’s NemoClaw. How does his interest in Agentic AI tie into his interest in building NVIDIA’s own frontier model FEEDBACK? Email: show @ reasoning dot showBluesky: @reasoningshow.bsky.socialTwitter/X: @ReasoningShowInstagram: @reasoningshowTikTok: @reasoningshow

    28 分鐘

  7. 3月18日

    Kagenti - A Kubernetes Control Plane for AI Agents

    SUMMARY: Morgan Foster talks about the Kagenti project, which enables an AI Agent agnostic framework for security, authentication, identity and zero-trust. SHOW: 1011 SHOW TRANSCRIPT: The Reasoning Show #1011 Transcript SHOW VIDEO: https://youtu.be/djFZruLEDiw SHOW NOTES: Kagenti (homepage)Kagenti (use-cases)“Old Things that look like Agents”“What makes Agents different?”CNV - What Makes Agents Different?“Handing your phone to a stranger, why Agents need their own identity” Topic 1 - Welcome to the show. Tell us a little bit about your background and areas you focus on today.  Topic 2 - Tell us a bit about the Kagenti project and the types of challenges it’s trying to solve for Agentic AI deployments.  Topic 3 - How much commonality exists between different Agentic frameworks that a common, agnostic agentic orchestration approach can work? And how much difference still exists and would drive companies to silo’d deployments?  Topic 4 - How far should an Agentic Orchestration framework go, and what types of things do you expect will still be Agentic framework dependent?  Is Kagenti more of a control-plane element, or more of a data-plane element? Topic 5 - As Kagenti evolves, what are some of the adjacent things that people should be keeping an eye on that might be a dependency, or could shift the direction of the project? FEEDBACK? Email: show @ reasoning dot showBluesky: @reasoningshow.bsky.socialTwitter/X: @ReasoningShowInstagram: @reasoningshowTikTok: @reasoningshow

    41 分鐘

  8. 3月15日

    Code Red - All Jobs are Software

    SUMMARY: Brian talks about the rapidly expanding gap between people and companies that augment their work with AI and those who are making AI the center of their work world.  SHOW: 1010 SHOW TRANSCRIPT: The Reasoning Show #1010 Transcript SHOW VIDEO: https://youtu.be/tFyLlCnkbsM SPONSORS: VENTION - Ready for expert developers who actually deliver? Visit ventionteams.comSHOW NOTES: WHY THE NEED FOR A CODE RED?  Velocity of Code (new companies)Velocity of Productivity (employees)Velocity of Analysis (strategy)AgentOpsToken FactoriesDevs for Business, Re-Wiring the Concept of Business AnalystFEEDBACK? Email: show @ reasoning dot showBluesky: @reasoningshow.bsky.socialTwitter/X: @ReasoningShowInstagram: @reasoningshowTikTok: @reasoningshow

    21 分鐘
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關於

The Reasoning Show AI moves fast. Thinking clearly matters more. The Reasoning Show cuts through the hype to explore how the smartest people in enterprise AI actually make decisions — the strategy, the tradeoffs, and the hard lessons no press release mentions. Every week, hosts Aaron Delp and Brian Gracely sit down with the founders building the tools, investors funding the shift, and operators running AI in the real world. Not hype. Not panic. Just clear-headed conversations with people who have to make actual decisions. Because the AI revolution isn't just happening. It's being reasoned through.  New shows every Wednesday and Sunday.  Topics: Enterprise AI strategy · LLMs in production · AI leadership · Agentic AI ·  Digital Sovereignty · Machine Learning · AI startups ·  Cloud Computing 

資料

  • 創作者
    Massive Studios
  • 活躍年份
    2011年 - 2026年
  • 單集
    1.1K
  • 分級
    兒童適宜
  • 版權
    © 2026 Massive Studios
  • 節目網站
    The Reasoning Show

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