The Reasoning Show

SUMMARY: On today’s "Models and Markets" - we explore about the FinOps experience from Cloud is having to adapt to the changing demands of Enterprise AI. SHOW: 1045SHOW TRANSCRIPT: The Enterprise AI Show #1045 TranscriptSHOW VIDEO: https://youtu.be/Plb88y-IkZYSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Topic: Finops for AI?Why now? Cost of tokens goes up as model performance increases, but still needs subsidies…Past: FinOps for Cloud - prices grew out of control, needed centralization for expense management and capital allocationPresent: TokenMaxxing, the move from per-seat to per-token pricingFuture: What happens when you can’t afford the Ferrari anymore? Will there be a glut of FinOps for AI startups? What happens when usage is regulated and centralized?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: Something new - "Models and Markets" - Aaron and Brian explore how recent news and macro trends are causing more companies to explore whether they should Buy, Build or Rent their AI future. SHOW: 1044SHOW TRANSCRIPT: The Enterprise AI Show #1044 TranscriptSHOW VIDEO: https://youtu.be/vcroGCXd3N4SHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:Topic: Own AI or Rent AI?Why now? Fable 5 and GPT 5.6 get restricted in the USPast: Private Cloud (on-prem/server huggers) vs. Public cloud vs. *gasp* hybrid cloudPresent: OSS Models vs. Big API modelsFuture: What happens when the subsidies go away, and rational business practices hit the industry??FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: While we spend a lot of time discussing AI models, we don’t always spend enough time on the challenges of managing the unstructured data used to train, tune, and enable those models. SHOW: 1043SHOW TRANSCRIPT: The Enterprise AI Show #1043 TranscriptSHOW VIDEO: https://youtu.be/OAqnuhorMJ4SHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Topic 1 - Welcome to the show. Tell us a bit about your background and where you focus today at NasuniTopic 2 - We’ve spent two years talking about models. Are we finally entering the era where the biggest differentiator is data quality rather than model quality?Topic 3 - When customers inventory their AI-ready data, what surprises them most?Topic 4 - Where is the intersection of file data, metadata, and RAG systems that augment a company’s AI experience with their own data?Topic 5 - People talk about AI governance, but isn’t most AI governance actually data governance?Topic 6 - Are today’s enterprise file systems designed for machine consumers (AI Agents) instead of human consumers?Topic 7 - What are the economics of data, in your world, as it relates to AI?Topic 8 - What’s next for enterprise file platforms?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: Are CEO's frustrated with the lack of control, costs and sovereignty of their AI environments? SHOW: 1042SHOW TRANSCRIPT: The Enterprise AI Show #1042 TranscriptSHOW VIDEO: https://youtu.be/xgQv8WP-DNISHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:Palantir and NVIDIA partnership (June 2026) - first 11 minutesPalantir CEO (Alex Karp) on CNBC“The VPC Privacy Illusion - Why Private LLMs still expose your data”The biggest mistake organizations make isn’t choosing the right model, it’s focusing on models at all (via LinkedIn)There’s a level of unhappiness and distrust of the frontier labs from CEOsThere needs to be an application layer on top of LLMs (e.g. “harness”, Palantir Ontology)This application layer prevents the LLMs from learning your business from your data“Alpha” is business differentiation (ability to outperform the market)He questions why the frontier model labs are charging by tokens and not outcomes (questions the entire AI business model)He questions “the true cost” of AI outputs He claims that CEOs are now concerned about frontier labs entering the business of the customers - brings up an interesting misunderstanding of how interacting with LLMs works (“we’re safe, it’s deployed in our VPC”)FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY:  Brian Gracely (@bgracely) and Aron Delp (@aarondelp) discuss the biggest AI news stories from the month of June, 2026. SHOW: 1041SHOW TRANSCRIPT: The Enterprise AI Show #1041 TranscriptSHOW VIDEO: https://youtu.be/SXmPOgE5jGkSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Links to all the AI News covered in this month’s showFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: As AI within the Enterprise matures, we look at 10 concerns and challenges that are still causing Chief AI Officers to worry about success in the future. SHOW: 1040SHOW TRANSCRIPT: The Enterprise AI Show #1040 TranscriptSHOW VIDEO: https://youtu.be/RyB4m17YK_4SHOW SPONSORS:Nasuni - Activate your data for AI and request a demoOutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architectureShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:THESIS: After spending time with a number of Enterprise companies, what are a list of challenges and concerns they still have in implementing GenAI across a broad set of use-cases within the Financial Services industry?Everybody started with what was available (e.g. CoPilot)Enterprise implementations (now) aren’t autonomousRising costs are the looming concernGovernance is a rising concernMeasurements of improvement are available, but variedExplaining measurements is complicatedExplaining trust is more complicatedUse-cases are fragmented, but there if you apply the technology, but not always obviousDe-centralized (shadow AI) to Centralized to De-centralized (semi-controlled) The learning curves are very asymmetrical across teamsNot everyone has access to Mythos or GPT-5.5-Cyber (yet)FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: What does a Forward-Deployed Engineer actually do? And what about deploying AI Harness? Let’s dig into the real-world with these evolving AI concepts and technologies. SHOW: 1039SHOW TRANSCRIPT: The Enterprise AI Show #1039 TranscriptSHOW VIDEO: https://youtu.be/QY0fqu2O84MSHOW SPONSORS:OutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architectureShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:Mozilla Thunderbolt launched Mozilla Thunderbolt (homepage)Topic 1 - Welcome to the show, tell us a bit about your background and what you focus on these days.Topic 2 - Let’s talk about the role of Forward Deployed Engineer, it’s being talked about a lot, but you’re living in that world now. What problems are FDEs usually tasked with trying to solve, or new things to implement?Topic 3 - We’ve seen other roles (DevOps, PlatformEng, etc.) that evolved from other roles or skills. What type of background lends itself to success in FDE? What skills are needed going forward?Topic 4 - You’re also working on some AI harness implementations. What can you tell us about those challenges and the technologies behind the harness?Topic 5 - At what point does an AI harness make sense for a company? What types of AI challenges typically require those next steps? Topic 6 - Working in the middle of this evolving AI space, what are some perspectives you’ve gained over the last 6-12 months? What do you wish you knew ahead of time? FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: On Father's Day, how would you explain some of the volatility of the AI market to your father? What advice might he give you to navigate the ups and downs and uncertainties?SHOW: 1038SHOW TRANSCRIPT: The Enterprise AI Show #1038 TranscriptSHOW VIDEO: https://youtu.be/T2ZIYLpl_cESHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoOutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architectureSHOW NOTES:Leaked documents show OpenAI is losing billionsAnthropic’s Fable and Mythos models banned from non-US foreign nationalsThe AI layoff wave is becoming a powder kegProfessors says AI-related job losses are inevitableTHESIS: On this Father’s Day, with an AI market that often times doesn’t make any sense, I thought about the type of advice that my father gave me over the years and how it would apply to this time of significant change.  Show up, keep up and shut upMake yourself invaluableFocus on what you can controlBe an expert in somethingWhen in doubt, get closer to people and how money is madeWhen things don’t make sense, focus on fundamentalsMarkets can be irrational way longer than you can be solventTry and think a couple steps aheadFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: As tools like Mythos create new AI-cybersecurity concerns, CIOs and CISOs need to be prepared for two challenges: Security Remediation and Patch to Production acceleration. SHOW: 1037SHOW TRANSCRIPT: The Enterprise AI Show #1037 TranscriptSHOW VIDEO: https://youtu.be/H5KxoiEIfUoSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoOutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architectureShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Project Lightwell (Red Hat and IBM)Athena (Chainguard)Anthropic Project GlasswingOpenAI GPT 5.5-CyberTHESIS: Major initiatives are forming to help enterprise organizations combat security vulnerability threats found or created using new AI-cyber tools such as Anthropic Mythos. What are the key considerations, and what additional steps do organizations need to take to be advantaged by these capabilities? Part 1The Breaking Point and the Mythos MomentThe scope of open source security and supportPatches, disclosures and upstream open sourceClearinghouses, EOs, Laws and CommunitiesRemediation - Build vs. BuyPart 2How fast can you get from Patch to Production?Mitigation before patchingFast path and stable patch pipelines?Automation in patching vs. automation in deploymentFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: How can CIOs balance innovation and control as they roll our AI capabilities across their organization. How can they balance onboarding, experience, security and flexibility? SHOW: 1036SHOW TRANSCRIPT: The Enterprise AI Show #1036 TranscriptSHOW VIDEO: https://youtu.be/ZgkMF7G3YfoSHOW SPONSORS:OutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architectureShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:Andy Weir (The Martian) on Eps. 193Systems of Record Won the SaaS Era - Clearinghouses Will Win the Agents EraHarness Engineering is where Enterprise AI becomes realTHESIS: It comes up as different control points, but CIOs are ultimately trying to figure out how to get the value from Enterprise AI while delivering a set of consistency across different teams and use-cases. Let’s explore what this “Enterprise Harness” is starting to look like. Enterprise Clearinghouse Enterprise Intelligence (a.k.a. Middleware)Enterprise Catalog - Models as a Service, Agents as a ServiceEnterprise Skills or Shareable Prompt HarnessesSymantec Routing to ModelsAI Gateway ControlsFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: If the cost of public AI continues to rise, because of various market shortages, should CIOs start looking at backup plans to better own their AI journeys and futures?SHOW: 1035SHOW TRANSCRIPT: The Enterprise AI Show #1035 TranscriptSHOW VIDEO: https://youtu.be/ngBBpP2LgdoSHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoOutShift by Cisco - “Scaling Out Superintelligence”  The Internet of Cognition architectureSHOW NOTES:THESIS: Between pending IPOs (Wall St. demands), high user-demand, GPU/TPU shortages, Data Center shortages, Model prices increasing (open models fading away), the cost of using AI is going to get more expensive over time. Should CIOs start thinking about a Backup plan to their current AI adoption that has lower cost alternatives?Topic 1 - Assuming you could get access to GPUs/TPUs/Accelerators, and suitable data center space to host them, what would be your thinking as a CIO if you felt like you needed to own some aspect of your AI roadmap/journey? Topic 2 - Assuming the normal “Shadow AI” backlash that you’d receive for offering something that wasn’t “frontier” level, how would you go about trying to communicate that within your organization?Topic 3 - What metrics or KPIs would you initially target to try and get buy-in that your approach was acceptable and moving towards the company goals?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: When we get to the end of 2026, how will enterprise companies be measuring the success of their AI projects? And how well will their teams be sharing their AI learning curves?SHOW: 1034SHOW TRANSCRIPT: The Enterprise AI Show #1034 TranscriptSHOW VIDEO: https://youtu.be/TvIFwNN-6ckSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoOutShift - “Scaling Out Superintelligence”  The Internet of Cognition architectureShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Why AI Economics are changingHow will team collaboration evolve with Enterprise AI?Topic 1 - How do we measure AI-adoption success? Number of workloads?Financial metrics (Spend, ROI, Costs-Saved, etc.)?Speed improvements?People-level?Topic 2 Right now the AI tools are very individual-centric The machinery to share, even at the basic enterprise-level, is very difficultThe experience to share is non-deterministic, just as everyone’s working style is different.Topic 3 - The motivation to share is still unknown. How do you encourage collaboration when so many companies are laying off people, or the specter of that happening is growing?What was the motivation before (team goals?) and how does that change now? People don’t want to be monitored, so how does a manager have visibility?What happens when companies remove the managers (“the counters”)? FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: After the first successful AI IPO of 2026, we dig into what makes the Cerebras WSE architecture unique in the market for fast inference. GUEST: Andy Hock, Chief Strategy Officer at Cerebras AISHOW: 1033SHOW TRANSCRIPT: The Enterprise AI Show #1033 TranscriptSHOW VIDEO: https://youtu.be/ed2nVbOtZiASHOW SPONSORS:OutShift - “Scaling Out Superintelligence”  The Internet of Cognition architectureShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:OpenAI announces 750MW partnership with CerebrasCerebras and AWS partnershipCerebras announces IPOTopic 1 - Welcome to the show. Tell us about your background, and what you focus on today. Topic 2 - For anyone that’s not familiar with Cerebras, give us an overview of the company, and especially an overview on the Cerebras technologies (e.g. Wafer-Scale Engine).Topic 3 - Cerebras’ WSE architecture is different from many of the GPU or GPU-like architectures in the market today. Centralized vs. distributed architectures always have their tradeoffs. Walk us through the technical and economic value of the Cerebras architecture.Topic 4 - Congratulations on the recent IPO (raised $5.55B). Let’s use that as a point in time vs the previous planned IPO. How has the market changed in that timeframe, and how has the Cerebras position changed? Topic 5 - Cerebras (today) offer both WSE hardware, and Cerebras Cloud (API) - very different GTM paths. Can we expect both of those to stay top priorities, or have the market dynamics shifted such that the priorities shift more towards the WSE business - as we’re seeing OpenAI, AWS and other engagements announced?Topic 6 - Is Cerebras a training and inference company, or are the economics of inference significantly different enough that it needs to be the sole focus of the company (for now)? Topic 7 - How much effort is it for any company to add support for the Cerebras chips if they have previously been using other architectures?Topic 8 - An IPO is a major milestone for any company, but the markets will now look for your future story. How do you see the AI market evolving over the next 2-5 years, and what are some things that people aren’t understanding yet about how it will evolve?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: The biggest enterprise AI question is which organization can most effectively operationalize, govern, and economically scale AI agents across the business.SHOW: 1032SHOW TRANSCRIPT: The Enterprise AI Show #1032 TranscriptSHOW VIDEO: https://youtu.be/GsK_RUnYroISHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance. We got this.Nasuni - Activate your data for AI and request a demoSHOW NOTES:Opening Thesis - How will team collaboration evolve within Enterprise AI?Question: Any suggestions on how to introduce enterprise-level governance and standardisation for agentic coding? Like skills, rules, plugins, context etcKey Topics 1. This isn’t a Coding-specific problem. Every team has this issue. If your processes weren’t well defined and enforced before, they will be worse nowNot it’s not just process standardization, but “buy-in” standardization2. Everything moves so fast, so managers don’t have the answers (yet) AI value is being created bottom-up, but paid for (and mandated) top-downThe current measurements aren’t useful (tokenmaxxing, all-or-nothing, etc.)3. The governance tools don’t exist yet.And it’s not clear that anyone wants them. They didn’t want them before. How do you even define governance? What’s the baby step before that, reuse and basic sharing? 4. Are we ready to invest in “Centers of Excellence” again? 5. We under-estimate the “creativity” element in human buy-in. Is success measured in improvement or replacement?How much of that did “you” do? We don’t know how to measure that.We haven’t lived through an AI-centric promotion cycle yet6. Bottom-up and Top-down need to find some common language and middle ground. Have they walked a mile in each other’s shoes yet (or lately)?How to bring a reality to the hype vs. demands vs. learning curve?How long is an AI-centric cycle vs. a pre-AI-centric cycle? FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY:  Brian Gracely (@bgracely) and Brandon Whichard (@bwhichard, Software Defined Talk and Failover Media) discuss the biggest AI news stories from the month of May, 2026. SHOW: 1031SHOW TRANSCRIPT: The Reasoning Show #1031 TranscriptSHOW VIDEO: https://youtu.be/MNihDdBSteISHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Links to all the AI News covered in this month’s showFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: The biggest enterprise AI question may no longer beWhich model is smartest? Instead, which organization can most effectively operationalize, govern, and economically scale AI agents across the business?’SHOW: 1030SHOW TRANSCRIPT: The Enterprise AI Show #1030 TranscriptSHOW VIDEO: https://youtu.be/acOBfRI0P3USHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance. We got this.Nasuni - Activate your data for AI and request a demoSHOW NOTES:Opening Thesis - Was the first wave of AI adoption artificially cheap? - The industry may be transitioning from subsidized growth to usage-based economics. Key Topics 1. Evidence AI Was Subsidized Massive CAPEX vs low end-user pricing Generous enterprise bundles Frontier model access for $20/month 2. The Hidden Economics of AI Agents - Agents consume exponentially more inference Tool orchestration, retries, memory, verification 3. Why Frontier Labs Are Shifting Focus From benchmark supremacy to orchestration Governance, memory, connectors, MCP, workflows 4. Forecasting AI Pricing 12 Months:  Commodity inference gets cheaper - Frontier reasoning remains premium 24 Months:  AI billing resembles AWS-style infrastructure billing Runtime, memory, latency and orchestration become billable 36 Months: Outcome-based pricing emerges AI spending shifts from IT budgets to labor budgets Final Takeaways  Commodity AI becomes utility-priced Frontier reasoning becomes premium Agents reshape enterprise economicsKey Conclusions1. AI probably was subsidizedThe economics strongly suggest adoption-first pricing.2. The subsidy era may be endingPremium tiers and metered pricing are emerging.3. AI agents fundamentally alter economicsUsage scales exponentially with autonomy.4. Commodity AI and frontier reasoning are separatingOne becomes cheap.One becomes premium.5. The real battle is moving upward in the stackThe future moat may be:orchestrationgovernanceworkflowsenterprise contextoperational toolingFinal Closing Thought“The biggest enterprise AI question may no longer be:‘Which model is smartest?’Instead:‘Which organization can most effectively operationalize, govern, and economically scale AI agents across the business?’”FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: As AI Agents are being brought into complex, regulated workflows, we explore the importance of accountability and accuracy, and how platforms and harnesses accomplish that goal. Can the CFO really fall in love with AI? GUEST:  Ram Venkatesh, Co-Founder/CTO of Sema4.aiSHOW: 1029SHOW TRANSCRIPT: The Enterprise AI Show #1029 TranscriptSHOW VIDEO: https://youtu.be/Lc3XS44Ixg4SHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance. We got this.SHOW NOTES:Topic 1 - Welcome to the show. Tell us about your background, and what led you to create Sema4.ai?. Topic 2 - AI Agents vs. Automation 2.0. What Actually Changed. Tell us about the Sema4.ai platform and capabilities. What challenges does it solve today?Topic 3 - You’re initially focused on solving challenges for the CFO, which means there is a ROI-focus all the time. Why did you target that segment of the business first?Topic 3a - What are the biggest hidden costs in enterprise AI deployments today?Topic 4 - Sema4.ai emphasizes “your LLM, your VPC, your data.”  What are the biggest considerations for companies looking to create these private/sovereign AI solutions? What typically gets overlooked?Topic 5 - How do you tend to frame the conversation about AI trustworthiness, and the role of humans vs. agents for enterprise work? Topic 6 - It feels like so much has changed or evolved with AI in the last 2-3 years. How does an Enterprise think about this much change for something that will be core to many critical applications? What will the Enterprise Architecture look like in 2 years?Topic 7 - Sema4.ai emerged partly from the acquisition of Robocorp and has roots in open-source automation.  Do you have a perspective on the role open-source will play in AI going forward? FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: As AI agents become embedded in everyday work, Microsoft 365 governance is no longer a back-office compliance exercise. it’s the “traction control” that lets enterprises innovate faster without losing control of their data, identities, and workflows.GUEST: Richard Harbridge, Principal Industry Advisor, Microsoft 365 at ShareGateSHOW: 1028SHOW TRANSCRIPT: The Enterprise AI Show #1028 TranscriptSHOW VIDEO: https://youtu.be/sgqg7uqErA0SHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance. We got this.Nasuni - Activate your data for AI and request a demoSHOW NOTES:Nearly 1 in 3 Organizations Report AI-Driven Data Exposure IncidentsOther Resources:A complete checklist for Microsoft 365 governance https://sharegate.com/guides/checklist-for-microsoft-365-governance Request a demo of ShareGate: Get a 1:1 ShareGate demo tailored to your Microsoft 365 use case Article around that divide of confidence vs reality of data exposure sharegate.com/blog/93-of-it-leaders-are-confident-in-their-ai-governance-but-nearly-1-in-3-report-data-exposure-incidents The State of Microsoft 365 industry report with more stats and insights - State of Microsoft 365 2025 | Free survey report – ShareGate | Sharegate (new one coming SOON)Topic 1 - Welcome to the show. Tell us about your background, and what you focus on today. Tell us about Sharegate. Topic 2 - How has generative AI changed the definition of “governance” inside Microsoft 365 environments?Topic 3 - What are organizations underestimating about AI readiness in M365?Topic 4 - What do you think about “oversharing risk” in the era of AI assistants?Topic 5 - What patterns are you seeing around shadow AI and unsanctioned SaaS usage?Topic 6 - How should organizations rethink identity and access management for AI-driven workflows?Topic 7 - What does good AI governance look like operationally—not just as a policy document?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: RIP Reasoning, hello The Enterprise AI Show. We do a point-in-time analysis of the AI market for May 2026, across 11 major categories. SHOW: 1027SHOW TRANSCRIPT: The Enterprise AI Show #1027 TranscriptSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Reviewing the Major AI Vendors FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: We  explore one of the most overlooked bottlenecks in the AI boom: energy and infrastructure and  why power availability is becoming the limiting factor.GUEST: Wannie Park, Founder/CEO of PADO AISHOW: 1026SHOW TRANSCRIPT: The Reasoning Show #1026 TranscriptSHOW VIDEO: https://youtu.be/satMQRxKQC8SHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:1. AI’s Hidden Constraint: PowerAI growth is no longer limited only by GPUs and computePower generation, cooling, and grid interconnects are emerging as major bottlenecksData centers could account for 10–12% of North American power demand in coming years2. Why Data Centers Are Being ReimaginedTraditional data centers were built for enterprise IT, not AI-scale workloadsAI infrastructure introduces:Massive power density needsAdvanced cooling challenges3. The Grid Wasn’t Built for AIUtilities are designed around peak demand scenariosMost grids run well below peak capacity most of the timeAI workloads create volatile and unpredictable consumption patternsLong interconnection timelines are pushing companies toward alternative infrastructure models4. GPU Utilization Is Surprisingly LowGPU clusters are often underutilized because of:Scheduling inefficiencies, Cooling limitations, SLA constraintsEffective GPU utilization may be as low as 12–13% in some environments5. Cooling as a Major Optimization LayerLegacy data centers often cool entire zones inefficientlyPado AI alignsAI workloads, Cooling systems, Power allocationWorkload-aware orchestration helps optimize cooling and compute efficiency6. The Rise of “Compute Forecasting”Pado forecasts compute demand instead of energy demandThe platform models:GPU workloads, Power consumption, Cooling requirements, SLA prioritiesGoal: maximize “compute per megawatt”7. AI Workloads Become Time-AwareAI providers may increasingly:Shift workloads to off-peak periodsIncentivize delayed non-urgent jobsDynamically balance compute demandUsers are already seeing variable inference latency in real-world AI systems8. Sustainability vs Reliability vs ProfitabilityOperators must balance:Uptime expectations, Infrastructure costs, Sustainability goalsRenewable adoption is growing, but reliability still drives investment in natural gas and battery-backed systems9. Brownfield vs Greenfield OpportunitiesPado AI is focused primarily on existing (“brownfield”) data centersExisting enterprise infrastructure can often be extended and optimized instead of rebuiltEnterprises may gain significant AI capability without hyperscale GPU deploymentsFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY:  Brian Gracely (@bgracely) and Brandon Whichard (@bwhichard, Software Defined Talk and Failover Media) discuss the biggest AI news stories from the month of April, 2026. SHOW: 1025SHOW TRANSCRIPT: The Reasoning Show #1025 TranscriptSHOW VIDEO: https://youtu.be/Gl-49dmAgBsSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Links to all the AI News covered in this months showFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: Draft guru Brandon Whichard (Software Defined Talk) joins us for the inaugural AI Draft, where we predict the next year of AI winners, losers, trends, and headlines. GUEST: Brandon Whichard, Software Defined TalkSHOW: 1024SHOW TRANSCRIPT: The Reasoning Show #1024 TranscriptSHOW VIDEO: https://youtu.be/BjT_HKhOcRESHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:Brian’s PicksGoogleMajor AI-centric IPO in 2026 ($1T valuation)Amazon (cloud)Company has more Agents that EmployeesTSMC (hardware)AMD (hardware)Family asks about AI at the holidaysData center issue causes a significant change to human existenceBrandon’s PicksAnthropicNVIDIABroadcomOpenAI (frontier model)AI Consumption-based pricing (end of subsidies)AI Energy DemandThe end of “vibe-coding”Sam Altman out at CEO of OpenAIFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: Exploring how to fully embrace AI-driven, agent-based software development, resulting in dramatically increased productivity and faster feature delivery. It highlights a broader shift in engineering—from writing code to orchestrating AI agents.GUEST: Sam Ramji, CEO/Co-founder at SailplaneSHOW: 1023SHOW TRANSCRIPT: The Reasoning Show #1023 TranscriptSHOW VIDEO: https://youtu.be/q50s0oL37pQSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Halt and Retool (presentation) OpenAI Harness EngineeringAnthropic Harness Engineering1. The “Halt and Retool” MomentA single-day build and deployment of a production feature triggered a company-wide realizationPaused all development to reassess how AI fundamentally changes engineering workflowsCreating “shock moments” (like stopping work) is key to driving mindset shifts2. From Coding to Agent OrchestrationDevelopers are shifting from writing code → managing AI agentsWork resembles “multi-boxing” or conducting an orchestra of parallel agentsSuccess depends on coordinating tasks, not executing them directly3. The Rise of Harness EngineeringDefined as everything between raw AI prompts and production-ready outputFocus: eliminating friction across the software development lifecycle Key practices:Logging agent errors and friction pointsContinuously refining workflows and toolingLetting AI reflect on and improve its own mistakes4. Spec-Driven Development Becomes CriticalPoor specifications lead to exponential inefficienciesTeams now spend significantly more time on design and specs than coding5. Measuring the Impact~3x increase in code velocityNear-zero “bit rot” Faster feature delivery—sometimes within 24 hours6. Token Maxing & Developer FitnessHigher token usage often signals better workflows and deeper integration with AIPerformance becomes about system design, not efficiency constraints7. New Tools & InterfacesIncreased use of voice interfaces over typingTerminal-first workflows replacing traditional IDE-centric approachesAI-accessible knowledge bases becoming standard8. The Future of Software EngineeringWithin ~6 months: developers may stop writing codeWithin ~12 months: developers may stop reading codeFocus shifts to:Intent, design, and orchestration. Domain expertise and problem modelingFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: How software development is rapidly evolving in the age of AI and automation. Matt Moore shares how his team is rethinking secure software supply chains, scaling infrastructure, and safely integrating AI agents into development workflows.GUEST: Matt Moore, CTO at Chainguard SHOW: 1022SHOW TRANSCRIPT: The Reasoning Show #1022 TranscriptSHOW VIDEO: https://youtu.be/9Q0kWkTYRs8SHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:Chainguard Factory 2.0DriftlessAFScaling Challenges & “Factory” EvolutionEarly automation relied on tools like GitHub ActionsAt scale, simple systems broke due to:Massive event volumesAPI rate limits (e.g., GitHub quotas)Exponential fan-out effectsKey innovation: custom work queue + reconciliation model~90% event deduplicationControlled throughput and backpressureImproved reliability and system stabilityIntroduced Driftless Built on reconciliation principles (inspired by Kubernetes):Compare desired vs. actual stateContinuously reconcile differencesBenefits:Resilience to missed eventsAutomatic retries and recoveryScales better than purely event-driven systemsAI Agents in Software DevelopmentAI is dramatically accelerating development workflowsChainguard uses agents to:Remediate vulnerabilities (CVEs)Update dependenciesFix failing tests and adapt to upstream changesKey Design PhilosophyLeast privilege → “least tool call”Avoid giving agents full system accessProvide narrowly scoped tools for specific tasksDelegate execution to sandboxed systems (e.g., CI pipelines)Focus on safe, controlled automationIndustry Shift: Velocity vs. SecurityExplosion of AI-driven tools (e.g., autonomous PR generation)Massive increase in development velocityNew risks:Poorly secured agent frameworksMalicious or unsafe automation patternsKey TakeawaysScale changes everythingSimple systems break under massive workloadsPurpose-built infrastructure becomes necessaryReconciliation > pure event-driven systems at scaleMore resilient, predictable, and controllableAI is a force multiplier—but requires guardrailsUnrestricted agents introduce serious riskConstrained, purpose-built agents are safer and more effectiveContinuous learning is mandatoryAI tooling is evolving too fast for static skillsetsTeams must actively experiment and adaptFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: How real-time power flow optimization at the edge is helping data centers and the electrical grid handle surging AI energy demands more efficiently. By unlocking hidden capacity and dynamically managing power systems, we explain how existing infrastructure can support significantly more compute without massive new buildouts.GUEST: Marissa Hummon, CTO UtilidataSHOW: 1021SHOW TRANSCRIPT: The Reasoning Show #1021 TranscriptSHOW VIDEO: https://youtu.be/ItcpU8UjOFESHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Utilidata (homepage)AI Data Center to Receive 50% Capacity Boost with AI Power OrchestrationKEY TOPICS:Differences between grid power dynamics vs. AI workloadsEdge AI for real-time power flow optimizationUnlocking stranded capacity in existing infrastructure“4-to-make-3” vs. “4-to-make-4” data center designAI training vs. inference power consumption patternsRole of NVIDIA-powered edge compute modulesGrid modernization and coordination with utilitiesSecurity and resilience in critical infrastructureKEY MOMENTS:From centralized AI models to edge-based decision-makingDefining efficiency: utilization vs. thermal performanceWhy AI workloads aren’t as constant as they seemNVIDIA partnership and edge compute in power systemsUsing redundancy to increase usable capacityIncreasing density of AI compute and hidden capacityData center vs. utility responsibilitiesAddressing data center bottlenecks and scaling challengesCustomer landscape: hyperscalers to enterpriseSecurity, resilience, and critical infrastructureKEY INSIGHTS:AI workloads are dynamic, not constant: Training and inference create fluctuating power demands that can be optimized.Edge intelligence is critical: Real-time sensing and decision-making at the edge unlock efficiency gains not possible with centralized models.Hidden capacity exists: Many data centers have up to 2x unused power capacity due to lack of visibility and control.Software-defined power is the future: Faster control loops allow systems to safely exceed traditional design limits.Efficiency = utilization: The biggest gains come from better use of existing infrastructure, not just improving hardware efficiency.TAKEAWAYS:AI infrastructure growth is as much an energy challenge as a compute challengeReal-time, edge-based control systems are key to scaling sustainablyExisting grid and data center investments can go further with smarter orchestrationThe future of AI scaling depends on aligning compute innovation with energy intelligenceFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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 ToriiSHOW: 1020SHOW TRANSCRIPT: The Reasoning Show #1020 TranscriptSHOW VIDEO: https://youtu.be/AUrh_xICPzMSHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:Torii (homepage)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?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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 TalkSHOW: 1019SHOW TRANSCRIPT: The Reasoning Show #1019 TranscriptSHOW VIDEO: https://youtu.be/q0mksIKcBzkSHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:The New Kingmakers (Stephen O’Grady - 2014)Developer Growth Rates[Via ChatGPT]  A useful way to think about it:Typing code → mostly commoditizedDesigning systems → partially assistedOwning outcomes → still very humanTopic 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?10% of time coding, mostly on the last 10-15% Lots of time in planning meetings (decoding requirements, resource planning, updates, etc.)Decent amount of time fixing, troubleshooting, technical debt reductionTopic 2a - Business people have unlimited ideas, and most ideas are money + techWhat would be their interface to problem solving without developers? (is this just a shift to consultants)Is this a massive opportunity for a great PaaS 3.0 company (e.g. is Vercel an example?)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?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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 PineconeSHOW: 1018SHOW TRANSCRIPT: The Reasoning Show #1018 TranscriptSHOW VIDEO: https://youtu.be/-kZZEMR341QSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate 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?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY:  Discover how AI is transforming software development and what it means for engineering leaders. GUEST: Jeff Keyes, Field CTO at AllStacks SHOW: 1017SHOW TRANSCRIPT: The Reasoning Show #1017 TranscriptSHOW VIDEO: https://youtu.be/cXPu8iWeB0kSHOW 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 @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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 TraversalSHOW: 1016SHOW TRANSCRIPT: The Reasoning Show #1016 TranscriptSHOW VIDEO: https://youtu.be/hF3MCRDhMnoSHOW 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 @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1015SHOW TRANSCRIPT: The Reasoning Show #1015 TranscriptSHOW VIDEO: https://youtu.be/IQaxE-DjIpoSHOW 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 @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1014SHOW TRANSCRIPT: The Reasoning Show #1014 TranscriptSHOW VIDEO: https://youtu.be/XwyAC-hxOQYSHOW 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 @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: With @bwhichard, we dig into how daily work-life changes when you make @AnthropicAI @claudeai the center of all workflow activities. SHOW: 1013SHOW TRANSCRIPT: The Reasoning Show #1013 TranscriptSHOW VIDEO: https://youtu.be/zEmEH0t67jsSHOW 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 @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1012SHOW TRANSCRIPT: The Reasoning Show #1012 TranscriptSHOW VIDEO: https://youtu.be/aXOr91q76yMSHOW 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 modelFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

SUMMARY: Morgan Foster talks about the Kagenti project, which enables an AI Agent agnostic framework for security, authentication, identity and zero-trust.SHOW: 1011SHOW TRANSCRIPT: The Reasoning Show #1011 TranscriptSHOW VIDEO: https://youtu.be/djFZruLEDiwSHOW 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 @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1010SHOW TRANSCRIPT: The Reasoning Show #1010 TranscriptSHOW VIDEO: https://youtu.be/tFyLlCnkbsMSHOW 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 @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1009SHOW TRANSCRIPT: The Reasoning Show #1009 TranscriptSHOW VIDEO: https://youtu.be/7xARBtgiMQgSPONSORS:VENTION - Ready for expert developers who actually deliver?Visit ventionteams.comSHOW 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. What did you go into it thinking about?What did you learn, what did you create?What new sorts of things did you have to try?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? How do you expect that OpenClaw might need to change?How do you expect that enterprises might need to change to adapt to this new capability that might be unleashed with their employees?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? We could probably have an entire podcast on AI development in open communities.FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

Erwan Menard - SVP Product Management @CrusoeAI talks about the evolution of NeoClouds, the challenges of matching the speed of data centers, GPUs and software, and how everything is evolving to megawatts and tokens. SHOW: 1008SHOW TRANSCRIPT: The Reasoning Show #1008 TranscriptSHOW VIDEO: https://youtu.be/eA8vpPmSW0YSPONSORS:VENTION - Ready for expert developers who actually deliver?Visit ventionteams.comSHOW 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?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1007SHOW TRANSCRIPT: The Reasoning Show #1007 TranscriptSHOW VIDEO: https://youtu.be/4tdj0S0AyhMSHOW SPONSOR:VENTION - Ready for expert developers who actually deliver? Visit ventionteams.comSHOW 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?How to define tasksLanguages and frameworksAbility to orchestrate multiple agentsHuman-in-the-Loop vs. AutonomousOther?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 READINGBuilding Effective Agents" by Anthropic: designing agents with tools, memory, reasoning loopsA Comprehensive Review of AI Agents: how agents perceive, reason, decide, actTop 20 AI Agent Concepts You Should Know: covering ReAct, Chain of Thought, memory typesAI Agents in Action: Foundations for Evaluation and Governance: structured foundation for safety aspects of agent deploymentEssential ViewingAI Agentic Design Patterns w/ AutoGen: build autonomous agents that use toolsAI Agent Systems w/ crewAI: orchestrating teams of agentsLangGraph Course: how to build stateful, reliable agentsFrameworks & Tools LangGraph: standard for complex, stateful agents (nodes, edges, loops)CrewAI: Best for structured task delegation and multi-agent collaborationAutoGen: Microsoft's framework for multi-agent conversational systemsModel Context Protocol (MCP): standard for connecting agents, tools, datan8n: no-code/low-code visual agent buildingFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1006SHOW TRANSCRIPT: The Cloudcast #1006 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SHOW NOTES:Link to February 2026 News and ArticlesFEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

Aaron and Brian discuss how The Cloudcast will be changing going forward, signaling an industry shift from Cloud Computing to AI.  SHOW: 1005SHOW TRANSCRIPT: The Cloudcast #1005 TranscriptSHOW 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”)New name, same RSS feeds (same podcast players)New logoSome existing/renamed and some new social media channels (will be listed)Same co-hosts (and maybe some new friends)Topic 2 - Why are we changing The Cloudcast?The majority of our content is AI focused nowCloud has become mostly stable, AI is at the beginning and so much is changingWe’re not abandoning Cloud, just giving it the amount of coverage needs (monthly Cloudcast, monthly CNOTM)Social media algorithms have changed audience acquisitionTopic 3 - Hasn’t The Cloudcast already been covering AI for a while? Yes, it’s been about 50/50 since 2024We’ve been discussing this change for almost a year. We actually discussed having an OpenAI-specific podcast at one point, but so much as changed in the market (which is a good reason for a diverse podcast)Topic 4 - What can we expect from the new podcast?Still on Wednesday and SundayBoth audio and video formats (Apple, Spotify, YouTube, TikTok/Insta (clips))Trying to make it easier for someone new to follow along - more concentration around core topics, but not exclusivelyAI Technology, AI Economics, AI Trends, AI (Business) Use-Cases, AI Things to Watch, AI Productivity, AI RegulationWe’ll still do a “Cloudcast” once a month, as the Cloud underpins almost everything AIWe’ll likely do a “Reasoning Basics” spin-off, like Cloudcast Basics. We’ll get a newsletter pulled together (hopefully weekly). Topic 5 - Anything else?Listeners don’t have to do anything to keep getting their week podcastSubscribe to the social media channels (show notes)Leave a 5-star review on the podcast playersTell a friend to check out the showFEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1004SHOW TRANSCRIPT: The Cloudcast #1004 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"CHAPTERS00:00 - Celebrating Milestones and AI Insights02:48 - The Cost of AI Agents and Realizations06:05 - Centralization vs. Decentralization in AI08:51 - The Evolution of AI Economics12:03 - Future Trends in AI and Project Management14:52 - Connecting AI to Real-World EconomicsKEY TOPICS:AI agent costs and pricing modelsThe shift from centralized to decentralized computingToken budgets and project economics in AIHistorical transitions in computing infrastructureFuture trends in AI project managementSHOW NOTESWhen 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 IMPACTSHow much should an AI project cost?How do we translate an AI token into some unit that a business can understand?How companies be their own AI token factories?FEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1003SHOW TRANSCRIPT: The Cloudcast #1003 TranscriptSHOW 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 rankingTAKEAWAYSThe frequency of AI model releases can lead to numbness among users.Evaluating AI models requires understanding their specific use cases and benchmarks.Enterprises must consider the compatibility and integration of new models with existing systems.Benchmarks are becoming more accessible but still require careful interpretation.The rapid pace of AI development creates challenges for enterprise adoption and integration.Companies need to be proactive in managing the versioning of AI models.The industry may need to establish clearer standards for evaluating AI performance.Efficiency and cost-effectiveness are becoming critical metrics for AI adoption.The timing of model releases can impact their market reception and user adoption.Businesses must adapt to the fast-paced changes in AI technology to remain competitive.FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1002SHOW TRANSCRIPT: The Cloudcast #1002 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" A FLY ON THE WALL IN 3 ROOMS IN 2026Room1 - NVIDIA’s M&A Room (Chips, Software Stack, Hosting Services, Agentic Tools, etc.)Room 2 - Anthropic’s Agentic VisionRoom 3 - TSMC’s 2028-2030 PlanningFEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

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: 1001SHOW TRANSCRIPT: The Cloudcast #1001 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SHOW NOTES:Stratechery (Ben Thompson)WHAT DO WE WISH WE KNEW ABOUT AI IN 3 YEARS?EconomicsPoliticsTechnologyRegulationsPartnershipsBuying PatternsUsage PatternsDevicesJob Creation/DestructionFEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

If someone walked into your office today and asked you to build a framework for how to value software development, what would you think about it? SHOW: 1000SHOW TRANSCRIPT: The Cloudcast #1000 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SHOW NOTES:Chainguard introduces Factory 2.0On running a startup of Claude Code agentsAgentic Product Development and the Theory of ConstraintsSoftware AbundanceHOW SHOULD SOMEONE THINK ABOUT THE ECONOMICS OF SW DEV IN 2026?If someone walked into your office today and asked you to build a framework for how to value software development, how would you think about it? FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

Are we ready to move into an era of wild predictions about where the future of Enterprise software is headed in 2026 and beyond? SHOW: 999SHOW TRANSCRIPT: The Cloudcast #999 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW NOTESThe SPAC-king is going to fix legacy software All Enterprise software is dead Microsoft and Software Survival (Stratechery)WHAT HAPPENS TO ENTERPRISE SOFTWARE NEXT?How much do enterprises want to write their own software? How much do enterprises wish they could write more software?How much do enterprises not understand the economics of owning their own software?How much does “big SaaS” or just “big Enterprise software” actually help because people already know it?Is it possible that this new Agentic-driven software could create a type of new software community? Are “open” software communities prepared for the emerging economics of AI-created software? FEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

We take a listener question about digital sovereignty, tariffs and UK/EU independence from large US cloud providers, also Brian reaches out to the Melbourne, AUS listeners. SHOW: 998SHOW TRANSCRIPT: The Cloudcast #998 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW NOTESAWS European Sovereign Cloud Azure European Sovereign ServicesGoogle Cloud Sovereign CloudRed Hat Digital SovereigntyBroadcom Digital SovereigntyOracle Digital SovereigntyDigital Sovereignty in Europe, What’s the Plan B? (IDC)Digital Commons EDIC Established (2025)EU AI Act“Sovereign Clouds and the Digital Sovereignty Imperative: Europe's Quest for Digital Independence” (IDC #EUR149098122, December 2022)The Evolution of Digital Sovereignty: Moving Beyond Data and Cloud” (Rahiel Nasir, IDC, January 13, 2023)THE FUNDAMENTALS OF DIGITAL SOVEREIGNTY What is the definition of Digital Sovereignty? What about Digital Assurance? Sovereignty from who or what? What laws are you attempting to comply with? How are they audited or measured? Data Sovereignty - Maintaining control over how data is collected, classified, processed and stored to ensure that data regulations are metTechnical Sovereignty - Running workloads without dependence on a provider’s infrastructure or software, and protected from all extra-territorial interference and scrutiny.Operational Sovereignty - Visibility and control over provider operations from provisioning and performance management, to monitoring of physical and digital access, to the infrastructure.Assurance Sovereignty -Ability to independently verify and assure the integrity, security, and reliability of digital systems and processes including resilience of critical services.FEEDBACK?Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

Aaron Delp (@aarondelp), Brian Gracely (@bgracely) and Brandon Whichard (@bwhichard, @SoftwareDefTalk) discuss the top stories in Cloud and AI from January 2026.SHOW: 997SHOW TRANSCRIPT: The Cloudcast #997 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST:  "CLOUDCAST BASICS"SHOW NOTES:Link to January 2026 News and ArticlesFEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

Following on the discussion of the Cloud 1.0 to Cloud 2.0 transition, we explore what that future cloud might look like. SHOW: 996SHOW TRANSCRIPT: The Cloudcast #996 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SHOW NOTES:Q1 - What didn’t Cloud 1.0 achieve from the grand vision?Q2 - What seemed promising but might have been the wrong timing? Q3 - Why didn’t more SaaS get bundled by the hyperscalers?Q4 - Does multi-cloud become easier?Q5 - Do primitives continue to be the core offering, or do more integrated offerings dominate the landscape?Q6 - Do a bunch of existing primitives get turned off to make room for new AI capabilities (DC capacity)?Q7 - Is security on by default? Q8 - Do more private/sovereign capabilities get offered?Q9 - What are the new AI capabilities that nobody has even thought of yet?Q10 - How does the mix of AI workloads get distributed across clouds, or across private and public? FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpodFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow