The Reasoning Show

SUMMARY: Shadow AI is growing much faster than known AI adoption across businesses. How can IT teams get Shadow AI under control? GUEST: Uri Haramati, CEO at Torii SHOW: 1020 SHOW TRANSCRIPT: The Reasoning Show #1020 Transcript SHOW VIDEO: https://youtu.be/AUrh_xICPzM SHOW SPONSORS: ShareGate Protect. Microsoft 365 Governance, we got this!Activate your data for AI and request a demoSHOW NOTES: Torii Topic 1 - Welcome to the show. Tell us about your background and your focus at Torii. Topic 2 - Is Shadow AI really a security problem—or is it a product-market fit problem inside the enterprise? Topic 3 - Why does Shadow AI spread faster—and become more dangerous—than traditional Shadow IT? Topic 4 - What’s the first signal a company should look for to know Shadow AI is already happening? Topic 5 - How do you balance visibility vs. control without killing the productivity gains that drove Shadow AI in the first place? Topic 6 - How should organizations rethink ‘data loss prevention’ in a world where the leak is a prompt, not a file? Topic 7 - What does a ‘well-governed’ AI environment actually look like in practice—day-to-day for an employee? Topic 8 - “Do you think Shadow AI ever fully goes away—or does it become a permanent operating model that companies need to design around?” FEEDBACK? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

SUMMARY: Have we reached a point where coding is a solved problem? And if so, what are the downstream effects on companies that need software to differentiate their business? GUEST: Brandon Whichard, Co-Host of Software Defined Talk SHOW: 1019 SHOW TRANSCRIPT: The Reasoning Show #1019 Transcript SHOW VIDEO: https://youtu.be/q0mksIKcBzk SHOW SPONSORS: ShareGate Protect. Microsoft 365 Governance, we got this!Activate your data for AI and request a demoSHOW NOTES: The New KingmakersDeveloper Growth Rates[Via ChatGPT] A useful way to think about it: Topic 1 - How many years into Public Cloud did we assume that Cloud had solved the IT problem? Topic 2 - Developers - what are we solving for? Topic 2a - Business people have unlimited ideas, and most ideas are money + tech Topic 3 - [Hypothetical] Let’s assume a fairly normal company fired all their software developers tomorrow. How long before they could get a moderately complex new application of integration into production? Topic 4 - Nobody likes to work on legacy code - missing source, missing engineers, etc. What do we call any code written by AI that was abandoned within the last 6-12 months? FEEDBACK? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

SUMMARY: The RAG (Retrieval Augmented Generation) pattern is one of the most frequently used to augment LLMs with context-specific information. Let’s explore RAG. GUEST: Roie Schwaber-Cohen, Head of Developer Relations at Pinecone SHOW: 1018 SHOW TRANSCRIPT: The Reasoning Show #1018 Transcript SHOW VIDEO: https://youtu.be/-kZZEMR341Q SHOW SPONSORS: Activate your data for AI and request a demoShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES: Topic 1 - Welcome to the show. Tell us a little bit about your background, and what you focus on these days at Pinecone Topic 2 - Let’s begin by talking about RAG systems. What are they? Why do companies choose to use them? What benefits do they provide in AI systems? Topic 3 - At a high level, RAG sounds straightforward—retrieve relevant context, generate an answer. But in practice, where does it break first as systems scale? Topic 4 - I’ve heard that RAG systems can return answers that are technically correct but fundamentally wrong. What’s a concrete example of that happening in production—and why does it slip past most teams? Topic 5 - In traditional systems, we assume there’s a single source of truth. But in enterprise environments, ‘truth’ is often versioned, contextual, and conflicting. How should teams rethink ‘truth’ when building AI systems? Topic 6 - A lot of teams assume their knowledge base is ‘good enough’ for RAG. What do they usually underestimate about the messiness of real enterprise data? Topic 7 - There’s a growing narrative that better reasoning models can compensate for weaker retrieval. From what you’ve seen, where does that idea fall apart? Topic 8 - If correctness depends on things like timing, policy scope, or configuration, how should teams design systems that understand context—not just content? Topic 9 - Looking ahead, what replaces today’s RAG architectures? What patterns are emerging among teams that are actually getting this right?” FEEDBACK? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

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 Protect. Microsoft 365 Governance, we got this!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? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

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: Activate your data for AI and request a demoShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES: Traversal 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? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

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 Protect. Microsoft 365 Governance, we got this!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? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

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: ventionteams.comSHOW NOTES: Links to all the AI News covered in this months showFEEDBACK? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

SUMMARY: Brandon Whichard shares his journey into AI with a focus on Claude, exploring how it transforms productivity, coding, and daily workflows. The conversation covers practical setup tips, trust-building, and the future of AI-assisted work. SHOW: 1013 SHOW TRANSCRIPT: The Reasoning Show #1013 Transcript SHOW VIDEO: https://youtu.be/zEmEH0t67js SHOW SPONSORS: 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? 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? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

SUMMARY: Brian digs into Jensen’s NVIDIA GTC 2026 keynote and highlights three things - accelerated computing for everything, the complexity of the new inference stack, and the broader discussion of NVIDIA’s “open” software stack including NemoClaw. SHOW: 1012 SHOW TRANSCRIPT: The Reasoning Show #1012 Transcript SHOW VIDEO: https://youtu.be/aXOr91q76yM SHOW SPONSORS: ventionteams.comSHOW NOTES: NVIDIA GTC 2026 (Keynote)NVIDIA NemoClawNVIDIA adds Groq LPU to their rack systemsNVIDIA to invest $26B in Open Weight ModelsInterview with Jensen about Accelerated Computing 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? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

SUMMARY: Morgan Foster talks about the Kagenti project, which enables an AI Agentic 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? 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? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

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 - ventionteams.comSHOW NOTES: WHY THE NEED FOR A CODE RED? FEEDBACK? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

SUMMARY: Sally O’Malley (Principle Software Engineer @RedHat, Maintainter @OpenClaw) talks about her early experiences of immersing herself into OpenClaw and evolution of the OpenClaw community. SHOW: 1009 SHOW TRANSCRIPT: The Reasoning Show #1009 Transcript SHOW VIDEO: https://youtu.be/7xARBtgiMQg SHOW NOTES: OpenClaw - Personal AI AssistantOpenClaw - RedditOpenClaw, OpenAI and the Future (Peter Steinberger - OpenClaw creator)OpenClaw Foundation (coming soon) Topic 1 - Welcome to the show. Tell us a little bit about your background in software engineering. Topic 2 - You recently jumped into the deep end of the pool with OpenClaw. Tell us about the week of immersion with this new technology. Topic 2a - For anyone that’s new to OpenClaw, can you give us the basics of what OpenClaw does? Topic 3 - You mentioned that this is a very different (or completely different) paradigm of how software is created. Can you walk us through the differences, your observations, how you had to really rethink things that you did before and after? Topic 4 - In your day job, you’re focused on software that’s used by large enterprises that have to be concerned with security and stability, as much as they do innovation. How do you see the existing OpenClaw fitting into that world? Topic 5 - You (very) recently were accepted as a committer to the OpenClaw project. I know it’s only been a few days, but what is opening your eyes about how this community operates, especially in comparison to other open projects you’ve worked on? FEEDBACK? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

Erwan Menard - SVP Product Management @Crusoe talks about… SHOW: 1008 SHOW TRANSCRIPT: The Reasoning Show #1008 Transcript SHOW VIDEO: SPONSORS: ventionteams.com SHOW NOTES: Topic 1 - Welcome to the show. Tell us a bit about your background, and what you focus on now at Crusoe. Topic 2 - There has obviously been a lot of coverage of AI data center buildouts all over the world for the last few years. Tell us about Crusoe, and your approach to providing “neocloud” services. Topic 3 - What are the biggest challenges facing Crusoe today and in the immediate future - is it technology, energy, financing for expansions, etc.? Topic 4 - Crusoe started as a bitcoin-focused company and has evolved to more of a GenAI-focus. What types of architectural changes did you have to make for this new type of workload? And how do those impact the quality of the services your customers expect from Crusoe? Topic 5 - Is your focus more on environments to enable model training and customization, or more focus on inference for customer-facing applications? Topic 6 - A lot has changed in AI in the last couple years. What has changed the most in the last couple years, and what are you expecting to change the most over the next couple years? Topic 7 - Sovereign AI and Private AI have become much bigger topics over the last 12-18 months, and we’d expect that to grow. What unique things is Crusoe doing to adapt to these changing requirements from customers? Send a text FEEDBACK? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

OVERVIEW: Welcome to The Reasoning Show! We dig into one of the foundational building blocks of modern Generative AI, the AI Agent. So what is an AI Agent, and what do we need to think about for the next couple years? SHOW: 1007 SHOW TRANSCRIPT: The Reasoning Show #1007 Transcript SHOW VIDEO: https://www.youtube.com/@TheReasoningShow/ SHOW NOTES: Topic 1 - We’re 3+ years into the Generative AI era. Why do you think AI Agents, or Agentic AI, is now getting so much attention? Topic 2 - If someone asked you to explain what an AI Agent is, how would you do that? Topic 3 - What are some of the core elements of AI Agents that you’re seeing impact how people think about and use agents? Topic 4 - AI Agents are going to spark the great “how much should I pay for this?” discussion. Have you given this any thought yet? Topic 5 - How do you expect to use AI agents in your day-to-day work, and how do you expect this to impact Enterprise businesses? ESSENTIAL READING Building Effective Agents" by AnthropicA Comprehensive Review of AI AgentsTop 20 AI Agent Concepts You Should KnowAI Agents in Action: Foundations for Evaluation and GovernanceEssential Viewing AI Agentic Design Patterns w/ AutoGenAI Agent Systems w/ crewAILangGraph CourseFrameworks & Tools LangGraphCrewAIAutoGenModel Context Protocol (MCP)n8nSend a text FEEDBACK? @reasoningshow.bsky.social@ReasoningShow@@reasoningshow

This episode marks the transition from The Cloudcast to The Reasoning Show, focusing more on AI and cloud topics. Brian Gracely (@bgracely) and Brandon Whichard (@bwhichard, @SoftwareDefTalk) discuss recent trends in AI, the evolution of tech teams, and the shifting landscape of enterprise AI tools. SHOW: 1006 SHOW TRANSCRIPT: The Cloudcast #1006 Transcript SHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SHOW NOTES: Link to February 2026 News and Articles FEEDBACK? @cloudcastpod.bsky.social@cloudcastpod@cloudcastpod@cloudcastpod

Aaron and Brian discuss how The Cloudcast will be changing going forward, signaling an industry shift from Cloud Computing to AI. SHOW: 1005 SHOW TRANSCRIPT: The Cloudcast #1005 Transcript SHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SHOW NOTES: Topic 1 - What are we announcing? (“The Reasoning Show”, a.k.a. “Reasoning”) Topic 2 - Why are we changing The Cloudcast? Topic 3 - Hasn’t The Cloudcast already been covering AI for a while? Topic 4 - What can we expect from the new podcast? Topic 5 - Anything else? FEEDBACK? @cloudcastpod.bsky.social@cloudcastpod@cloudcastpod@cloudcastpod

This episode explores the evolving economics of AI development, the rising costs associated with AI agents, and the implications for businesses and developers. It highlights the shift from centralized to decentralized computing, the importance of understanding token budgets, and the future of AI project management. SHOW: 1004 SHOW TRANSCRIPT: The Cloudcast #1004 Transcript SHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS" CHAPTERS 00:00 - Celebrating Milestones and AI Insights 02:48 - The Cost of AI Agents and Realizations 06:05 - Centralization vs. Decentralization in AI 08:51 - The Evolution of AI Economics 12:03 - Future Trends in AI and Project Management 14:52 - Connecting AI to Real-World Economics KEY TOPICS: SHOW NOTES When AI Tokens cost more than your employees Should you own (or generate) your own tokens? On running a startup of Claude Code agents: 1 Billion tokens a monthCan AI grow corn?WE'VE REACHED A POINT WITH AI WHERE PEOPLE ARE STARTING TO THINK ABOUT THE BUSINESS IMPACTS FEEDBACK? @cloudcastpod@cloudcastpod.bsky.social@cloudcastpod@cloudcastpod

Aaron and Brian review some of the latest AI model releases and discuss how they would evaluate them through the lens of an Enterprise AI Architect. SHOW: 1003 SHOW TRANSCRIPT: The Cloudcast #1003 Transcript SHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SHOW NOTES: Last Week in AI Podcast #234Artificial Analysis.AIOpus 4.6 ReleaseGPT Codex 5.3 ReleaseGLM-5 ReleaseOpenAI Preparedness FrameworkSam’s Tweet that 5.3 Codex hit “high” ranking for cybersecurityFortune Article on 5.3 high rankingTAKEAWAYS FEEDBACK? @cloudcastpod.bsky.social@cloudcastpod@cloudcastpod@cloudcastpod

As we move into Q1 2026, Brian talks about 3 rooms where he'd like to be a fly on wall to see the blueprints of significant AI companies shaping the markets. SHOW: 1002 SHOW TRANSCRIPT: The Cloudcast #1002 Transcript SHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" A FLY ON THE WALL IN 3 ROOMS IN 2026 Room1 - Room 2 - Room 3 - FEEDBACK? @cloudcastpod.bsky.social@cloudcastpod@cloudcastpod@cloudcastpod

Aaron and Brian explore the evolving landscape of AI over the next three years, discussing its economic implications, political influences, technological advancements, partnership dynamics, changing buying patterns, and the potential impact on job creation and destruction. They emphasize the uncertainty surrounding AI's future and the need for understanding its broader implications. SHOW: 1001 SHOW TRANSCRIPT: The Cloudcast #1001 Transcript SHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SHOW NOTES: StratecheryWHAT DO WE WISH WE KNEW ABOUT AI IN 3 YEARS? FEEDBACK? @cloudcastpod.bsky.social@cloudcastpod@cloudcastpod@cloudcastpod