Let’s Solve IT! Podcast

NetApp
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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. 

Episodes

  1. 1 day ago

    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 workers, particularly skilled ones like engineers, rather than replace them, was a consistent theme throughout the interview [1:57] [12:55] [13:07] (1:21, 11:58).   Efficiency Driving Differentiation: Blodgett repeatedly connected the operational efficiencies gained from AI to the opportunity for teams to focus on higher-value, "differentiating work" that improves a company's competitive edge [2:28] [3:04] (1:21).   Transparency and Trust: The importance of leaders being transparent with their teams about AI initiatives to manage fear and foster trust was emphasized at both the beginning and end of the conversation [8:18] [11:58] (8:18, 11:58).   Adoption Through Exposure: The belief that practical, hands-on experience with AI tools is more critical for adoption and assimilation than formal training was a key theme [11:04] [11:12] (11:04, 11:12).   Key takeaways   AI's primary purpose is to act as a "force multiplier" to increase efficiency, not to facilitate mass layoffs [1:57] (1:21). Blodgett argued that tech company layoffs were a correction for overhiring, with AI being used as a convenient narrative [1:21] (1:21).   Increased efficiency from AI will allow IT organizations to shift their focus from essential but non-differentiating work like maintenance and patching to strategic initiatives that make the company more competitive [2:48] [3:04] (1:21).   While some lower-skilled, repetitive roles may be reduced, engineering jobs are safe from wholesale replacement due to the complexity and need for nuance in their work [3:38] [4:14] (1:21).   Successful adoption of AI requires moving beyond abstract concepts to hands-on exposure, which helps build fluency and makes its use an "engineering reflex" [10:06] [11:28] (9:41, 11:12).   Leadership must operate with high disclosure and transparency regarding AI strategies to build team trust and mitigate fears of job displacement [8:18] [11:58] (8:18, 11:58).   Context and background   Contextual Information   The interview was framed by the current climate of public and employee anxiety surrounding AI-driven job displacement [8:05]. This context was explicitly established by the interviewer's reference to recent layoffs at the "magnificent seven" tech companies, who are also making massive investments in AI [0:42]. The conversation also acknowledged that while the concept of AI is old, dating back to 1953, the recent advancements have renewed these concerns [0:19].   Related Events   The primary related events referenced were the widespread layoffs in the tech industry, which some companies have linked to their AI investments [1:21]. Blodgett also mentioned an internal company hackathon as a specific event that spurred the creation of a valuable AI tool, the "autonomous Knock" [8:33].   Potential Impact   Blodgett's statements could have a reassuring effect on engineers and other IT professionals, reframing AI as a tool for empowerment and career enhancement rather than a threat [12:55]. His focus on using AI for competitive differentiation could influence business leaders to adopt a value-creation mindset for their AI strategies, rather than one purely focused on cost reduction [3:04]. Furthermore, his practical advice on fostering adoption through transparency and hands-on experimentation offers a tangible model for other managers and executives navigating the same challenges [11:58] [11:12].     Interview flow   The interview began with a direct, challenging question about whether AI is being built to fire people [1:16]. Dave Blodgett addressed this head-on, establishing a pragmatic and reassuring tone that he maintained throughout the conversation [1:21]. The discussion flowed logically from this central fear to the practical applications of AI in IT [6:36], leadership strategies for encouraging innovation and managing employee concerns [8:05], and finally to a broader philosophical view on AI's role in augmenting human ingenuity [12:45]. There were no significant shifts in Blodgett's calm and authoritative tone.   Episode description  How do leading IT organizations get real value from AI?  Start by putting AI where the work is measurable, repetitive, and operationally constrained:  Development acceleration through tools like GitHub Copilot, Cursor, and Claude Code, especially for repetitive coding patterns, code generation, and code quality checks  Low-variability operational workflows, such as NOC services, where incidents can be detected, triaged, correlated, and enriched before human intervention  Observability and event correlation that help teams move faster from incident detection to root cause understanding  Measurable business outcomes, including reduced time to resolution, faster time to market, improved code quality, and better operational efficiency  Dave gives a concrete example from his team: an autonomous NOC model where the observability fabric detects an incident, routes a ticket, and allows an AI agent to perform triage, correlate indicators, identify likely root cause, and recommend next steps. By the time the human engineer receives the ticket, the work has already been enriched with context. That is the difference between AI as a vague productivity promise and AI as an operational capability that can be measured.  But Dave is careful not to overstate what AI can do. He draws a clear line between automation that supports engineering work and the idea that AI can replace engineers outright. His own experimentation with vibe coding tools reinforced that technical complexity still requires engineering expertise. A non-engineer can generate a basic utility, but complex systems quickly demand architecture, reasoning, validation, and judgment.  That disti

    14 min

  2. 17 Jun

    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 impact users.  “Unsupported breeds the problem. What that means is that they don't support and they don't provide security patches and those types of things anymore, which creates a huge risk if you are keeping privileged company data or your company secrets on an old server that has an aging OS that's out of support and is not receiving patches on a regular basis or at all.” (2:16) Mike explains how legacy hardware and applications are no longer just performance liabilities—they are critical security vulnerabilities, especially when they fall out of vendor support and stop receiving patches.”  "What you have to do is first of all, you have to create a culture... where it's okay to fail. Just fail fast and learn and iterate, iterate. Don't wait until everything's perfect to release or you'll never release." (12:39) - Stated when discussing the importance of creating a culture that encourages rapid innovation and is not paralyzed by the fear of failure.    How do leading IT organizations get ahead?  Shift to modern observability with:  AI-driven correlation of massive data sets, reducing troubleshooting time from hours to seconds  A next-generation Network Operations Center (NOC) model, combining real-time visibility with intelligent diagnostics  The ability to trace issues across services, pinpoint root causes, and feed insights directly to engineering teams for permanent fixes  Continuous feedback loops that turn incidents into long-term improvements    Mike also highlights how cloud architectures are changing the game, enabling organizations to eliminate downtime entirely in some cases by shifting workloads, rebuilding environments, and avoiding traditional patching cycles.  But technology alone isn’t enough.  A major theme throughout the episode is culture. Moving from reactive to proactive support requires a mindset shift across the organization:  Teams must be trained to seek out risks before they surface  Leaders must encourage experimentation and remove the fear of failure  Organizations must adopt a “fail fast, learn fast, iterate” approach to keep pace with rapid change  Continuous learning is essential, especially as AI capabilities and threats evolve at unprecedented speed  Mike emphasizes that many teams still operate with a “if it’s not broken, don’t fix it” mentality—which is no longer viable in a modern IT environment. The new mandate is clear: identify risks early, act sooner, and build systems that improve continuously.  Practical advice for IT leaders:   Invest in a strong observability foundation  Build secure AI environments with governance and guardrails  Stay current on emerging technologies and evolving threat landscapes  Create a culture that prioritizes proactivity over perfection  Ultimately, this episode reframes IT support as a strategic capability—not just a cost center. The organizations that succeed will be the ones that can anticipate issues, reduce risk, and maintain resilience in a system that never stops moving.  If your IT team is still operating in reactive mode, this conversation will push you to rethink what’s possible—and what’s required—to stay ahead.

    15 min

  3. 3 Jun

    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

    15 min

  4. 20 May

    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

    16 min

  5. 6 May

    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 min

  6. 22 Apr

    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/

    12 min

  7. 7 Apr

    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 min

  8. 9 Mar

    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

    10 min

  9. 9 Mar

    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

    14 min
  • 9 Episodes

About

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. 

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  • Creator
    NetApp
  • Years Active
    2k
  • Episodes
    9
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    Clean
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