Let’s Solve IT! Podcast

About Let’s Solve IT! Podcast

IT leaders, are you ready to turn strategy into results?  Welcome to Let’s Solve IT!, the podcast designed exclusively for IT decision-makers who are ready to tackle today’s toughest challenges head-on. If you’re facing IT challenges, you’re not alone. This bi-weekly podcast dives into real IT challenges from AI adoption to cybersecurity risks with candid conversations, lessons learned, and practical solutions. Hosted by Matt Brown, Sr. Executive Director at NetApp, Let’s Solve IT! helps you bridge the gap between strategy and execution. Listen now to gain practical insights, tackle complex challenges, and deliver real results.

Publisher

NetApp

Category

news · technology

Language

en

Explicit

No

First episode

9 Mar 2026

Latest episode

7 Oct 2026

Latest episodes

16 episodes in the feed.

1. 

   7 Oct 2026

   Ep. 16 - Are you building bots when you really need an AI intern?

   AI agents can follow instructions, but how do they learn your organization's unwritten rules? Matt Brown welcomes Robert Vaughn, IT AI domain owner at Intel, to explore the “AI intern”: a metaphor for systems that use institutional knowledge and ongoing feedback to understand better what matters. They discuss the difference between AI reduction and synthesis, how risk compounds across agentic workflows, and why human oversight remains essential. Discover why building more useful, trustworthy enterprise AI takes more than connecting bots. In this episode, you’ll learn: Why institutional knowledge is a missing piece in enterprise AI How feedback helps AI account for changing priorities, roles, and information Why synthesis introduces greater risk than summarizing or extracting information How human oversight can help AI support higher-value decisions How complementary retrieval pipelines can combine documented information with organizational context You are not alone. Let’s Solve IT. Learn More: IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown https://www.linkedin.com/in/robert-lawson-vaughn-7a65103/ Agentic AI, AI agents, AI intern, enterprise AI, institutional knowledge, organizational context, AI awareness, feedback loops, human oversight, human-in-the-loop, AI risk management, trustworthy AI, retrieval-augmented generation, RAG pipelines, AI reasoning, AI synthesis, IT automation, Robert Vaughn, Matt Brown, Intel, NetApp, Let’s Solve IT!

2. 

   23 Sept 2026

   Ep. 15 - Is your telemetry all cost and no action?

   Organizations are collecting more telemetry than ever, but is all that data actually delivering value? Matt Brown sits down with Marty Mayer, Senior Director of Product Management at NetApp, to explore how NetApp turns massive amounts of telemetry into actionable insights. Marty shares how Active IQ uses data from more than 300,000 systems across 24,000 customers to improve support, identify risks, optimize infrastructure, and help customers get more from their NetApp investments. They also discuss the importance of continually evaluating what data is worth collecting, how Value Insights can help quantify business outcomes, and how AI is moving telemetry beyond recommendations toward automated action. In this episode, you’ll learn: Collect telemetry with a clear use case—not simply because you can. NetApp Active IQ receives roughly 10 TB of telemetry each month from more than 300,000 systems across 24,000 customers. Telemetry can deliver value far beyond break/fix support, including security, capacity optimization, planning, and customer success. Measuring how data is actually being used helps determine what should be retained, archived, or pruned. The next evolution is moving from insight to recommendation to automated action through AI agents. Start small with AI, establish guardrails, test with trusted users, and expand based on feedback. The quality and accessibility of your data ultimately determine the value AI can deliver. You are not alone. Let’s Solve IT. Learn More: IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown https://www.linkedin.com/in/martymayer/ Telemetry, Active IQ, AI, AIOps, AI agents, data strategy, data analytics, IT operations, infrastructure optimization, automation, predictive insights, customer support, Value Insights, storage efficiency, capacity planning, cybersecurity, NetApp

3. 

   9 Sept 2026

   Ep. 14 - Are you bringing a dull knife to your data strategy?

   A strong data strategy isn’t built when the project begins; it’s built in the preparation that comes before it. In this episode of Let’s Solve IT!, Matt Brown is joined by Spencer Hamons, Executive Architect at NetApp, who explains why organizations must measure, classify, and understand their data before investing in infrastructure. The discussion covers how to identify hot, warm, and cold data, why storage performance matters more than ever as SSD prices rise, and how telemetry and observability help organizations make smarter infrastructure decisions. In this episode you’ll learn: Why AI projects fail without data preparation The “sharpen the knife” approach to data strategy Hot, warm, and cold data explained Measuring performance before making infrastructure decisions SSD price increases and the return of tiered storage Telemetry and observability for smarter storage planning Optimizing AI training, RAG, and inference data Why culture matters as much as technology Continuous improvement for AI infrastructure Whether you’re evaluating your virtualization strategy, preparing for AI adoption, or leading an IT organization through change, this episode offers practical guidance for turning disruption into opportunity. You are not alone. Let’s Solve IT. Learn More IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown https://www.linkedin.com/in/hamons/ AI, artificial intelligence, data strategy, storage, enterprise storage, data management, observability, telemetry, infrastructure, GPUs, RAG, retrieval augmented generation, inference, AI infrastructure, SSD, hard drives, hybrid cloud, object storage, NetApp, CIO, IT leadership, data architecture, data center modernization, AI adoption

4. 

   26 Aug 2026

   Ep. 13 - The hypervisor Odyssey: Are you letting a good crisis go to waste?

   The hypervisor landscape is changing. Licensing costs are rising. AI is reshaping enterprise IT. For many organizations, it feels like two major waves colliding at once. In this episode of Let’s Solve IT!, Matt Brown sits down with Spencer Sells, Vice President of Global Technology Alliances at NetApp, to discuss why today’s virtualization disruption shouldn’t simply be viewed as a cost crisis—it should be viewed as an opportunity. Drawing inspiration from The Odyssey, they explore how IT leaders can navigate uncertainty, make more intentional technology decisions, invest in their teams, and build platforms that will support the next decade of innovation. The conversation also examines why successful IT transformations depend as much on people as technology and why organizations that neglect training, experimentation, and culture risk falling behind. In this episode you’ll learn: Why the hypervisor disruption is about more than licensing costs How leading organizations are approaching VMware and alternative platforms Why AI and virtualization are creating simultaneous transformation challenges The importance of investing in people, not just technology How to encourage experimentation while maintaining governance Why “not making a decision” is still making a decision Practical leadership advice for IT managers navigating change Whether you’re evaluating your virtualization strategy, preparing for AI adoption, or leading an IT organization through change, this episode offers practical guidance for turning disruption into opportunity. You are not alone. Let’s Solve IT. Learn More: IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown https://www.linkedin.com/in/spencersells The hypervisor odyssey: Spencer Sells of NetApp on turning IT crisis into strategy Episode overview In this episode of "Let's Solve IT!," host Matt Brown talks with Spencer Sells, Vice President of Global Technology Alliances at NetApp, about two crises hitting IT organizations at once: the disruption in the hypervisor market following Broadcom's acquisition of VMware, and the rapid rise of AI. Playing off the movie blockbuster, "The Odyssey," Matt and Spencer frame the hypervisor shift as an odyssey, with changes forced by a licensing and pricing shock rather than a genuine technology gap. Spencer argues IT leaders should not let this crisis go to waste and should instead use it to build their next platform deliberately. Throughout the conversation, Spencer Sells returns to one argument: IT platforms are enabling tools, but the people running them, described repeatedly through the metaphor of "rowing the boat," determine whether an organization succeeds through the transition. Spencer Sells advises IT leaders to budget time for staff training, address the psychological effects of change directly, and get hands-on with new technology themselves to build credibility and empathy with their teams. Spencer shares data from his customer conversations: about 20 to 25% of customers plan to stay on VMware by Broadcom and move to VCF, while about 60% are actively evaluating or blending in new hypervisor or Kubernetes platforms. Spencer cites a specific operational example: a NetApp account team planned to migrate a customer off VMware by Broadcom in a single month, a timeline Spencer says grossly underestimates the work required for staff training, networking changes, data protection, monitoring, support-level planning, and CMDB integration. Key takeaways The following points summarize the operational guidance Spencer gave for IT leaders navigating the VMware by Broadcom transition and the concurrent adoption of AI. IT organizations face two simultaneous disruptions: the hypervisor market shift caused by Broadcom's VMware acquisition and pricing changes, and the emergence of AI as a business-critical technology. About 20 to 25% of customers Spencer Sells has spoken with are staying on VMware

5. 

   12 Aug 2026

   Ep. 12 - Is zero downtime becoming your biggest cybersecurity risk?

   What happens when cyber vulnerabilities can be discovered and exploited faster than your organization can safely deploy a patch? In this episode of Let’s Solve IT!, Matt Brown welcomes back Gavin Guttersen, NetApp CISO, to discuss how AI-powered cyber models are transforming the threat landscape. They explore why traditional patching timelines may no longer be fast enough, how years of accumulated security debt are increasing organizational risk, and why the long-standing expectation of zero downtime may need to be reconsidered. You’ll hear: How AI is dramatically lowering the barrier to entry for cyber attackers Why vulnerabilities that once took weeks to exploit can now be weaponized in minutes How security debt and aging infrastructure increase business risk Why faster patching can create operational risk and unexpected downtime How to identify the systems, applications, and data your business cannot afford to lose Why limiting the potential blast radius is critical when preventing every breach is unrealistic How IT, security, system owners, and business leaders should share responsibility for cybersecurity decisions What organizations can do in the short, mid, and long term to prepare for AI-accelerated threats The question is no longer whether an attacker will get in. It’s whether your organization knows what matters most and is prepared to minimize the impact when a breach occurs. You are not alone. Let’s Solve IT. Learn More IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown https://www.linkedin.com/in/gaving Gavin Gutterson on AI cyber models: why zero downtime is becoming a security risk Episode overview In this episode of "Let's Solve IT!," host Matt Brown talks with Gavin Gutterson, NetApp's CISO, about how AI-powered cyber models have changed the calculus around uptime and patching. Gavin Gutterson explains that a model called Mythos, along with competing AI cyber models racing to outpace each other, can now identify critical vulnerabilities in decades-old platforms and generate working exploits "in a matter of minutes." Gavin Gutterson states plainly: "This is just the beginning. This is the very, very tip of the iceberg." The main argument from Gavin Gutterson centers on a shift in IT's core assumption. IT organizations have always prioritized always-on availability, patching systems on a 30-day cycle after testing in subproduction environments. Gavin Gutterson argues that this timeline no longer works when AI can create exploits in hours, and he raises a direct question for IT leaders: how do you patch in 30 minutes when your process was built for 30 days? Gavin Gutterson also introduces "security debt" as the security equivalent of technical debt: outdated, unpatched systems (Gavin Gutterson cites Windows 98 as a real example still running inside NetApp for regression testing) that accumulate risk over time. Gavin Gutterson's recommended response involves three levers: cleaning up old systems, adding compensating controls around systems that cannot be patched, and limiting the "blast radius" when, not if, a bad actor gains access. Key takeaways The following takeaways summarize the guidance Gavin Gutterson shared for IT and security leaders managing AI-accelerated cyber risk. AI cyber models, including Mythos, can find critical vulnerabilities and build exploits for them in minutes, a process that previously took bad actors months. Mythos is not the only AI cyber model driving this shift; Gavin Gutterson describes multiple models "playing leapfrog with each other," each improving over the last. Traditional patching cycles (30 days, with testing in subproduction before deployment to production) cannot keep pace with AI-generated exploits that emerge in hours. Security debt describes the accumulation of outdated, unpatched systems in an environment, and Gavin Gutterson equates it directly with technical debt. Organi

6. 

   29 Jul 2026

   Ep. 11 - Are you spending your precious tokens on trash?

   Is your AI delivering business value, or are you just paying to generate expensive garbage? In this episode of Let’s Solve IT!, Matt Brown talks with Cecile Kellam, NetApp Senior Solutions Architect, about why successful AI initiatives depend on more than good prompts. They discuss the importance of clean, relevant, secure data; why data ownership and custodianship must involve the business; and how organizations can avoid wasting tokens, budget, and trust as AI projects move from pilot to production. You’ll hear: Why many organizations are wasting AI tokens on poor-quality data Why great prompts alone cannot overcome bad or outdated data How to identify the right data sources for different AI use cases Who should own data quality, governance, and AI success Why business leaders—not just IT—must be involved in AI initiatives How data integrity directly impacts AI accuracy, trust, and adoption How to build AI initiatives that deliver measurable business value instead of unnecessary costs If your AI can’t trust your data, why should your employees trust your AI? You are not alone. Let’s Solve IT. Learn More: IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown Cecile Kellam | LinkedIn Cecile Kellam on AI tokenomics: why clean data beats clever prompts Episode overview In this episode of "Let's Solve IT!," host Matt Brown of NetApp talks with Cecile Kellam, Senior Solutions Architect at NetApp, about a problem she sees across enterprise AI projects: teams "spending precious tokens on trash." Cecile Kellam defines tokens as the cost of every AI query, and Cecile Kellam explains that this cost covers more than money. Tokens also consume energy and people-management resources, so every prompt an organization sends counts as a real investment. The central argument from Cecile Kellam is direct: clean, secure, well-governed data matters more than a perfectly written prompt. Cecile Kellam points out that a strong prompt still fails when the underlying system pulls from outdated engineering code, incomplete records, or poorly governed HR data. To make the point concrete, Cecile Kellam contrasts AI needs across engineering, finance, and HR departments, since each department queries very different tools and data. Cecile Kellam also warns about the cost of scaling AI from a small pilot to full production. Cecile Kellam describes customers who successfully built digital twins in the cloud, then watched costs turn "astronomical" when they tried to run those digital twins for more than a couple of hours a day. Cecile Kellam ties this risk back to a familiar pattern: companies that went "all in" on the cloud without clear goals and later faced surprise bills. Key takeaways The following takeaways summarize the practical guidance Cecile Kellam shared for IT leaders planning or scaling enterprise AI. Tokens represent the full cost of AI queries, including financial spend, energy use, and people-management costs, so wasted prompts waste real budget. A well-written prompt fails to deliver good results when the AI system lacks access to clean, current, and relevant data. Data accuracy is an ongoing discipline, not a one-time task, because information that was correct years ago can produce wrong answers today. Data ownership and governance often cause friction at the start of AI projects, so organizations should settle who owns, manages, and uses the data early. Engineering, finance, and HR departments each require different tools and data access, so AI systems must be built around each department's specific use case. Line-of-business owners hold the strongest stake in AI success, since they see the return when their teams save time and automate processes. End-user buy-in improves when leaders position AI as a tool that removes tedious work rather than a replacement for jobs. Scaling a successful AI pilot to full production can create "disastrous" bills, so

7. 

   15 Jul 2026

   Ep. 10 - Is AI a Technical Wave or a Cultural Tsunami?

   Technology isn’t the biggest obstacle to AI adoption. People are. In this episode of Let’s Solve IT!, Matt Brown talks with Hem Nerkar, NetApp Senior Vice President and CIO, about why AI adoption is fundamentally a cultural transformation, not just another technology rollout. They discuss how CIOs can overcome fear, build trust, align leadership, and create an environment where employees feel empowered to experiment, learn, and embrace AI as part of their daily work.  You’ll hear: Why AI represents a cultural shift far bigger than a technology upgrade Why fear, not technology, is often the biggest barrier to AI adoption How executive alignment creates confidence across the organization Why communication, empathy, and transparency are critical to successful AI initiatives How measurable AI goals encourage experimentation instead of perfection How NetApp IT is building an AI-first culture through leadership, training, and Centers of Excellence Why organizations should focus on progress over perfection as AI continues to evolve If AI changes technology overnight, how do you prepare people to change with it? You are not alone. Let’s Solve IT. Learn More IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown https://www.linkedin.com/in/hem-nerkar-445b731 Episode overview In this episode of Let's Solve IT!, host Matt Brown interviews Hem Nerkar, NetApp's Senior Vice President and Chief Information Officer, about how large organizations adopt AI. Hem Nerkar argues that AI is not another technical wave like the personal computer or the internet. Hem Nerkar describes AI as a cultural tsunami, a disruption larger than anything organizations have faced before, and frames that scale as an opportunity rather than a threat. Hem Nerkar explains that the role of IT is shifting from a support function to a strategic enabler of business transformation and shareholder value. That expanded role now includes managing organizational psychology, which covers employee fear, governance, and adoption. Hem Nerkar's central claim is that AI will augment jobs rather than replace them. AI moves teams from a traditional pyramid structure to a diamond structure, where more employees focus on higher-value work while AI handles routine tasks. NetApp uses specific mechanisms to drive AI adoption. NetApp established Centers of Excellence (COEs) to share best practices across the company, created secure innovation labs for experimentation inside the firewall, and embedded AI objectives into annual employee reviews. NetApp reports measurable results in quality assurance, where AI reduced testing time, and in IT infrastructure, where AI accelerated the vulnerability patching lifecycle. Throughout the conversation, Hem Nerkar identifies empathetic, continuous communication as the factor that makes AI transformation stick. Key takeaways The episode gives IT leaders a practical framework for moving an organization past fear and into measurable AI adoption. Each takeaway below stands on its own. AI adoption is a cultural challenge first and a technical challenge second. NetApp's organizational model is shifting from a pyramid structure to a diamond structure, where AI handles routine tasks and employees focus on higher-value work. Centers of Excellence (COEs) capture and share AI learnings across NetApp so teams don't repeat the same work. Innovation labs give NetApp employees a secure, low-risk environment to test AI use cases inside the firewall. AI objectives embedded in annual employee reviews turn adoption into a tangible, measurable goal. Anonymous employee surveys give NetApp leadership an honest read on how comfortable teams feel with AI. Empathy combined with constant communication is the primary driver of successful AI adoption, and Hem Nerkar states that no amount of communication is enough. A "fail fast" mindset gives teams permission to experiment and values the atte

8. 

   1 Jul 2026

   Ep. 9 - Are you building AI to fire me?

   AI was supposed to make work easier. So why are companies racing to cut people before the results even exist? In this episode of Let’s Solve IT!, NetApp’s Matt Brown sits down with Dave Blodgett, VP, Global Head of Infrastructure, to unpack the uncomfortable truth behind AI hype, skyrocketing infrastructure costs, and the growing fear that “productivity” is becoming corporate code for layoffs. You’ll hear: Why companies are investing billions into AI before provingreal businessvalue How “productivity gains” are becoming justification for workforce cuts The hidden infrastructure and cloud costs powering enterprise AI Why AI hype is colliding with operational reality inside IT organizations What the future of work couldlooklike as automation accelerates Why the biggest AI challenge may not be technology but trust Because the future of work may not be what the AI evangelists promised. You are not alone. Let’s Solve IT! Episode keywords:  AI infrastructure, enterprise AI, AI costs, future of work, workforce automation, cloud infrastructure, AI productivity, generative AI, AI strategy, IT operations, cloud operations, artificial intelligence, AI adoption, enterprise technology, AI investment, digital transformation, automation, infrastructure scaling, tech layoffs, AI and jobs, operational efficiency, CIO strategy, infrastructure management, NetApp, cloud computing, AI hype, business transformation, IT leadership, AI governance, productivity gains Learn More IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown Dave Blodgett | LinkedIn Transcript Episode overview: Is AI being built to replace people—or to help IT teams move faster, work smarter, and focus on the problems that actually differentiate the business? In this episode of Let’s Solve IT!, host Matt Brown sits down with Dave Blodgett, NetApp’s VP of Cloud Infrastructure and Operations, for a direct conversation about one of the biggest questions facing CIOs, CTOs, and IT leaders today: how do you harness AI without losing the trust, judgment, and innovation that only people bring? If your organization is under pressure to deliver AI-driven productivity gains, this conversation reframes the issue. The real opportunity is not replacing people. It is using AI to unlock the work IT teams have been too constrained to do—work that improves operations, accelerates delivery, and helps the business compete. At the center of the discussion is a practical leadership challenge: AI can increase human velocity, but only if teams understand the strategy, trust the intent, and have real access to the tools. Dave argues that AI is already delivering meaningful gains in areas such as software development, code quality, operational triage, and NOC services. But he is equally clear that complex engineering work still depends on human judgment, context, and innovation. If your team is still asking whether AI is coming for their jobs, this conversation offers a better question: how can AI help people move faster, solve harder problems, and focus on work that humans are uniquely equipped to do? Topics covered: Why AI should be treated as a force multiplier, not simply a workforce reduction tool How AI can help IT teams shift attention from keeping the lights on to strategic, differentiating work The limits of “vibe coding” and why engineering judgment, nuance, and expertise still matter What makes this AI wave different from previous automation and cloud transformations How autonomous NOC workflows, AI agents, event correlation, and root cause analysis can materially reduce time to resolution Why AI adoption requires transparency, hands-on exposure, business-value metrics, and team trust How leaders can help employees move from fear to fluency by making AI part of the engineering reflex Episode themes AI as Augmentation, Not Replacement: The idea that AI will enhance and assist human worker

9. 

   17 Jun 2026

   Ep. 8 - Is your IT support strategy creating a security risk?

   What if your biggest security vulnerability isn’t a hacker, but your support strategy? In this episode of Let’s Solve IT!, Matt Brown sits down with Mike Eubanks, Senior Director of IT Operations at NetApp, to explore why reactive IT support is becoming a growing business risk. From technical debt and aging infrastructure to ransomware and expanding attack surfaces, they discuss why proactive operations, observability, and AI are becoming essential tools for modern IT organizations. You’ll hear: Why reactive IT support is becoming a growing security risk in the age of ransomware and cyber threats What a technical debt, aging infrastructure, and poor technology hygiene expand an organization’s attack surface The role of observability, AI, and proactive operations in identifying and resolving issues before they impact the business Practical strategies for reducing risk, improving security posture, and shifting IT support from firefighting to prevention Support teams rarely get recognized when nothing breaks, but that’s exactly the point. The real challenge in modern IT isn’t responding to disasters faster. It prevents outages, ransomware attacks, and operational disruptions before the business ever feels the impact. You are not alone. Let’s Solve IT! Learn More: IT case studies | NetApp Connect with us: Matt Brown | LinkedIn Michael Eubanks | LinkedIn Below is a summary of this episode’s transcript: What does it really mean to make IT support proactive in an era defined by AI? In this episode of Let’s Solve IT!, host Matt Brown sits down with Mike Eubanks, Senior Director of IT Operations at NetApp, for a candid, real-world conversation about why traditional IT support models are breaking—and what it takes to evolve them. Key topics: Why unsupported systems and legacy applications create hidden security vulnerabilities How observability enables predictive, proactive IT support The role of AI in correlating data, reducing troubleshooting time from hours to seconds How to build a secure AI environment with governance and guardrails Why culture is critical to shifting from reactive to proactive operations The importance of failing fast, iterating quickly, and empowering teams to act early If your team is still waiting for tickets to come in, this conversation will challenge you to rethink what modern IT support should look like—and how to get ahead of risk before it disrupts the business. At the center of the discussion is a fundamental shift: IT support can no longer afford to be reactive. While business leaders continue to invest in innovation and AI-driven transformation, support organizations are expected to operate like a utility—always on, always available, and invisible when working well. But under the surface, aging infrastructure, unsupported systems, and growing data complexity are creating a constant stream of hidden risk. Notable Quotes: “Being secure requires a different focus." (1:58) - Stated when explaining growth of security risks forced IT and the business to change their approach. AI is fundamentally changing both sides of the equation. On one hand, it’s accelerating innovation and enabling faster insights. On the other, it’s amplifying security risks, exposing new ways for bad actors to identify and exploit weaknesses. "You have to listen to the experts. You have to let them plan and understand the plan and then communicate that plan." (2:45) - Said while describing his leadership philosophy in IT support, emphasizing collaboration and expertise. “We don't look for things that are broken. We look for things that are breaking and AI helps us do that." (5:22) - This was Mike's explanation of the shift from traditional monitoring to proactive observability. He shares how his team is shifting from traditional monitoring to modern observability, using AI-powered analytics to identify patterns, detect anomalies, and predict issues before they im

10. 

    3 Jun 2026

    Ep. 7 - Should you buy your way out of a supply chain crisis?

    The technology industry is facing an ever-increasing supply chain crisis, and AI is rapidly making it worse. What started as a hardware shortage is now forcing enterprises to rethink storage, data center capacity, procurement strategy, and whether their infrastructure is truly prepared for the next wave of demand. In this episode of Let’s Solve IT!, Matt Brown speaks with NetApp Technical Evangelist and The STEMINISTS co-host Phoebe Goh about a question many IT and engineering leaders are facing: Should you buy your way out of a supply chain crisis? The conversation explores why throwing money at the problem and panic-buying hardware may make things worse. As AI demand explodes, enterprises are discovering that you can’t simply hoard your way out of a supply chain crisis, especially when the real problem is how data, storage, cloud, and infrastructure strategy are being managed in the first place. You’ll hear: Why AI is increasing pressure on enterprise storage and data center capacity How the DRAM shortage and SSD supply chain challenges are affecting infrastructure decisions Why buying more hardware may not solve the real problem How AI is changing the value of cold data and historical data Why storage teams need to think more strategically about data mobility, security, and performance How cloud, tiering, and modernization can help organizations stay flexible Why IT strategy, procurement, sustainability, and infrastructure planning must be connected Because the real question may not be whether you can buy your way through the crisis. It may be whether that decision prepares you for what comes next. You are not alone. Let’s Solve IT! Learn More IT case studies | NetApp Check out The STEMINISTS Podcast: The STEMINISTS Podcast | Phoebe Goh and Mekka Williams Connect with us! https://www.linkedin.com/in/cmattbrown Phoebe Goh | LinkedIn AI data center, enterprise storage, storage infrastructure, supply chain crisis, DRAM shortage, SSD shortage, data center capacity, data mobility, cloud strategy, infrastructure modernization, IT strategy, storage optimization, AI infrastructure, cloud tiering, data center sustainability, AI workloads, enterprise AI, hybrid cloud, storage performance, data management

11. 

    20 May 2026

    Ep. 6 - Do your employees have the right AI tools to succeed?

    AI is no longer just a productivity tool. It is quickly becoming one of the biggest operational, security, and governance challenges enterprises have faced since the rise of the cloud. In this episode of Let’s Solve IT!, Matt Brown speaks with NetApp IT Director of Enterprise Architecture and AI, Paul Carau, about the uncomfortable reality many technology leaders are now facing: Employees are adopting AI faster than most organizations can govern it. The conversation explores why AI success requires far more than simply deploying the latest toolset. Leaders must now navigate employee personas, data access, governance, change management, overlapping AI capabilities, and the growing pressure to move faster without losing control of the environment. You’ll hear: Why uncontrolled AI adoption is becoming a major enterprise risk How shadow AI is creating new challenges of security and governance Why employee personas matter when deploying AI at scale The growing complexity caused by overlapping AI platforms and tools How organizations can balance innovation speed with operational control Why AI governance must evolve alongside business expectations Because the real question may no longer be whether your company is using AI. It may be whether you still control how it’s being used. Let’s talk about what that means, and Let’s Solve IT! Resources just for you: IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown https://www.linkedin.com/in/paul-carau

12. 

    6 May 2026

    Ep. 5 - More Tools. Less Output? The Truth About Developer Productivity

    Are your technology investments driving developer productivity—or just adding complexity? In this episode of Let’s Solve IT!, Matt Brown sits down with Mekka Williams, Director of Innovation and Solutions and co-host of The STEMINISTS podcast, to unpack one of the biggest disconnects in modern IT: the gap between investment and impact. They explore why more tools don’t always lead to better outcomes, what developer productivity really looks like from a business perspective, and how leading organizations are aligning people, processes, and technology to drive measurable results. You’ll hear: Why time-to-value continues to fall short of expectations How DevOps complexity is slowing teams down What meaningful productivity measurementlookslike Where AIdelivers real valueand where it introduces risk Why progress starts with action, not perfection Because improving productivity isn’t a one-time fix—it’s an ongoing business priority. You are not alone. Let’s Solve IT! Learn More IT case studies | NetApp Also make sure you check out The STEMINISTS Podcast | Phoebe Goh and Mekka Williams Connect with us! https://www.linkedin.com/in/cmattbrown Mekka Williams | LinkedIn

13. 

    22 Apr 2026

    Ep. 4 - Does your data center need to go nuclear to support AI?

    It sounds extreme, but it’s not as far off as you might think. In this episode of Let’s Solve IT!, Matt Brown talks with Ralph Renne, Sr. Director, Workplace Experience, to break down what’s really happening behind the scenes: massive increases in power demand, the shift to water-cooled environments, and why most data centers aren’t built for what’s coming next. In this episode, you’ll learn: What’s driving these new AI infrastructure demands Why this isn’t just an IT problem, it’s a facilities and business problem The real timelines and costs to get ready And what you should be doing right now to prepare Because this isn’t a future problem. It’s already here. And if you’re not planning for it, chances are, you're already behind. You’re not alone. Let’s Solve It! Learn More IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown https://www.linkedin.com/in/ralph-renne-36ab0a6/

14. 

    7 Apr 2026

    Ep. 3 - Why are ERP implementations CIO career killers?

    Why do so many ERP transformations derail careers at the highest level? It’s not the technology. It’s everything else.  In this episode of Let’s Solve IT!, Matt Brown sits down with NetApp CIO Hem Nerkar to confront one of the most uncomfortable truths in enterprise IT: ERP transformations don’t start by failing systems—they start by breaking the people leading them. Because what looks like a software upgrade is actually a high-risk, multi-year bet on your company’s culture, operations, and future.  In this episode, you’ll learn: • Massive financial investment with no immediate payoff • Organizational resistance at every level • Hundreds of systems and stakeholders in play • And a clock that never stops ticking while the business keeps running  Hem Nerkar pulls back the curtain on what really makes these transformations so dangerous and what separates those projects that succeed from those that quietly unravel careers.  This isn’t about features. This isn’t about vendors.  This is about pressure, risk, and leadership when there is no safe path forward. Let’s talk about what that really means. Let’s Solve IT! Learn More Here: IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown https://www.linkedin.com/in/hem-nerkar-445b731

15. 

    9 Mar 2026

    Ep. 2 - How to afford AI and the people to run IT

    AI budgets are blowing up. Hardware prices are all over the place. And executives want ROI yesterday. So here’s the real question nobody wants to say out loud: How are you supposed to afford the tech and the people to run it? In this week’s episode of Let’s Solve IT!, host Matt Brown and Stephan Stelter, NetApp Manager, Solutions Engineering, confront the tension IT leaders feel every day: innovation pressure vs. finite budgets. They get into FOMO-driven spending, AI productivity myths, and resource scarcity. Rather than defaulting to layoffs or across‑the‑board cuts, this conversation explores a smarter path forward: reallocating resources, retasking talent, and placing the right workloads in the right environments to maximize impact without burning out teams or budgets. If you’re feeling squeezed between transformation goals and headcount limitations, this episode is for you. Let’s talk about what that really means, and Let’s Solve IT! Learn more about the world of NetApp on NetApp: IT case studies | NetApp

16. 

    9 Mar 2026

    Ep. 1 - When AI convenience becomes a business risk

    AI is everywhere — recording meetings, transcribing conversations, summarizing discussions, and storing more data than ever before. But as AI-powered productivity tools become the norm, how do organizations protect themselves from growing security and legal risk? In this first episode of Let’s Solve IT!, host Matt Brown sits down with NetApp CISO Gavin Guttersen to explore a sobering reality: AI tools can create powerful productivity gains and unexpected exposure.  From litigation risk to data governance gaps, from “AI companions” in meetings to agents talking to agents, this conversation dives into the uncomfortable truth: Security through obscurity is gone.  In this episode, you’ll learn: How AI transcription and meeting recording tools create unexpected security and legal exposure Where data governance breaks down as enterprise AI adoption accelerates What CISOs, IT leaders, and business teams must consider in an always‑recorded environment If you’re responsible for AI security, data governance, or risk management, this episode sets the foundation for the conversations organizations can’t afford to avoid. Let’s talk about what that really means. Let’s Solve IT! Learn more about the world of NetApp on NetApp: IT case studies | NetApp Connect with us! https://www.linkedin.com/in/cmattbrown https://www.linkedin.com/in/gaving

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