About
Courses by David
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Agentic AI Fundamentals: Architectures, Frameworks, and Applications1h 15m
Agentic AI Fundamentals: Architectures, Frameworks, and Applications
By: David Linthicum
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Cloud Computing: Understanding Core Concepts1h 23m
Cloud Computing: Understanding Core Concepts
By: David Linthicum
Articles by David
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195K followers
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David Linthicum shared thisThis is way more important than most people understand.David Linthicum shared thisYou don’t need to rewrite COBOL to optimize your mainframe. In our webinar, we’ll show how organizations can: • Reduce batch COBOL on the CPU by over 80% • Significantly reduce batch processing times • Improve SLA windows • Ensure 100% business continuity By making COBOL workloads eligible for zIIP, teams can unlock additional capacity - with no interruption to daily operations. Keep your business running. Improve what already works. Create room for what comes next. Register now: https://bit.ly/4un6f2L #MainframeSmarter #IBMZ #COBOL
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David Linthicum reposted thisDavid Linthicum reposted thisCloud backup teams don’t usually discover protection gaps when things are going well. It's usually after an outage, a failed recovery, or a compliance review. This is a challenge that isn’t limited to enterprise IT teams. MSPs are under even more pressure to proactively identify backup gaps across multiple customer environments before they become risks. This is extremely important when you're responsible for business continuity across dozens of clients. In N2W v4.6, we introduced a new Governance Dashboard that gives customers an instant view of compliance gaps across all connected cloud accounts including unprotected resources and those that haven't been locked for immutability. This is just one of the updates in v4.6, along with new storage cost savings capabilities and enhanced DR features. Join us on June 3rd as we walk through everything 👉 https://lnkd.in/dajAYvbF
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David Linthicum shared thisWho could have foreseen this? What genius would have seen this coming? How could somebody have known such a thing was going to happen? How could anyone have seen this outcome? #IToldYouSo #IToldYouSoAgain https://lnkd.in/eXjGXKzMWhy are AI's Top CEOs Pedalling Back on Job Predictions?Why are AI's Top CEOs Pedalling Back on Job Predictions?
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David Linthicum shared thisI’ve received no fewer than 30 emails in the last 48 hours asking if I’ll be meeting up with folks at Cisco Live this week. So, in the interest of saving everyone a few more emails, a few calendar holds, and at least one “just circling back” message, I figured I’d put this out there now: Unfortunately, I won’t be making it to Cisco Live this year. I know, I know. Tragic. Somewhere, a coffee meeting that was never formally scheduled is now mourning its loss. I always appreciate the invites, the kind notes, and the effort to connect. I just didn’t want anyone stalking the expo floor, scanning session rooms, or conducting a multi-day analyst sighting operation on my behalf. So while I won’t be there in person, I’m wishing everyone a great event, good conversations, strong coffee, and minimal badge-scanning fatigue. And for those who reached out: thank you. Please consider this my attempt to save us all a few emails. #CiscoLive #NotInvited #MaybeNextTime
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David Linthicum shared thisThe Real AI Cloud Showdown: AWS vs. Microsoft vs. Google—Who Really Delivers? After months of hype and speculation, we finally went there: we broke down the major AI cloud players—AWS, Microsoft, and Google—to get to the truth of who does what best, why it matters, and when enterprises should (or shouldn’t) bet on their AI platforms. In this week's video (dropping Thursday at 8:00 AM!), I stepped back from the marketing noise and dug into the real strengths and trade-offs of Amazon Bedrock, Azure AI Foundry, and Google Vertex AI. How does each provider truly support AI-powered enterprise workloads? Where does each platform genuinely fit—and just as importantly, when might an alternative approach (like private or on-prem AI) actually make more sense? If you're wrestling with the cost, performance, and strategic implications of cloud AI, this is the conversation we should be having. My analysis revealed that AWS Bedrock offers amazing flexibility and seamless integration for enterprises with a heavy AWS footprint, but be warned: moving data outside AWS can rack up significant costs. Microsoft’s Azure AI Foundry is perfect for organizations deeply invested in Microsoft’s ecosystem, especially those that prioritize governance, workflow, and business process integration. Meanwhile, Google’s Vertex AI and Gemini present more open and cost-competitive alternatives, making them especially compelling for those seeking cross-cloud flexibility and cutting-edge AI advancements. But here's the bottom line: the “best” solution isn't universal. It all depends on your data, your AI use cases, and your business systems. The days of vague cloud AI recommendations are over—it’s time for real, actionable advice. Ready to see how these platforms compare side by side and get the truth about cloud AI for your enterprise? Watch the full breakdown here: https://lnkd.in/e6_RBQ5s #CloudAI #AWS #MicrosoftAzure #GoogleCloud #AIPlatforms #EnterpriseAI #DavidLinthicum #AIIntegration #CloudStrategy #TechLeadershipThe Enterprise AI Cloud Battle: AWS vs Microsoft vs GoogleThe Enterprise AI Cloud Battle: AWS vs Microsoft vs Google
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David Linthicum reposted thisDavid Linthicum reposted thisNew Substack post about what it takes to redesign your processes or workflows with AI. Hint: it's hard! https://lnkd.in/evuNXQEU
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David Linthicum posted this🚀 Unlocking the Future of AI and Cloud Governance! 🌐 I am excited to highlight the impactful book "Unlocking the Power of Cloud Governance and Intelligence," which has been shaping the conversation in our field since its release in the fall of last year. A special shoutout to the lead author Meredith Stein for her outstanding leadership throughout this project. Without her guidance and vision, this book would not have achieved the success it has. Her dedication has been crucial in bringing this work to fruition. This book delves into the transformative power of hybrid AI and the critical importance of data governance in today's digital landscape. It offers actionable insights for enterprises looking to effectively harness AI while ensuring compliance and security. If you're interested in navigating the complexities of cloud governance and leveraging AI for your organization, I highly recommend picking up a copy. If it’s within your budget, you won’t regret it! 📚 [Get your copy here!](https://lnkd.in/epXuJ4EZ) Let’s embrace the future of technology together! #CloudGovernance #AI #HybridAI #DataIntelligence #Leadership #Innovation #MeredithStein #DavidLinthicum
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David Linthicum shared thisAgentic AI isn't the cheap digital labor many believe it to be. It's probabilistic software demanding budgets, monitoring, and human oversight. The true measure of success will be completed outcomes, not tokens used. Agentic AI is significantly more costly than anticipated, both to build and operate. As we scale, the costs associated with back-end LLMs will only increase, impacting the dynamic behavior and autonomy of these agents. It's crucial to understand the system's scaling potential, token consumption, and overall business justification before committing. These fundamental questions are often overlooked, leading to unexpected expenses and an inability to decouple from costly LLM dependencies. Evaluate if agentic AI is truly needed and cost-justifiable for your enterprise. #AgenticAI #AIStrategy #LLM #TechCosts #BusinessValue #FutureOfAI
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David Linthicum shared thisMany generative AI providers are currently offering capabilities at a loss. Even with substantial payments, there's a risk they may still be incurring losses. This model is unsustainable, and price increases are inevitable. As organizations become more reliant on LLMs for agentic AI systems, they risk being heavily influenced by future pricing. This dependency could lead to unexpected significant costs in the coming years, potentially exceeding anticipated business value. A primary concern with agentic AI is its reliance on remote LLMs. These "agents" often don't run locally but are orchestrated through remote cloud services. This lack of direct control means organizations are subject to the LLM provider's pricing strategies. If costs rise and business value cannot be justified, adoption may falter, leading to the rejection of initial prototypes due to prohibitive expenses. #AI #GenerativeAI #LLM #CloudComputing #BusinessStrategy #TechTrends
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David Linthicum liked thisDavid Linthicum liked thisAI inference doesn’t need to run entirely on GPUs — Your CPUs can be enough ✅ In this #RHSummit exclusive, #theCUBE’s Rob Strechay and Rebecca M. Knight speak with Bill Pearson, VP of Data Center at Intel, & Taneem Ibrahim, Director of Engineering, AI Inference at Red Hat, about why CPUs are becoming a critical part of modern AI deployment strategies, especially for agentic workflows, orchestration, tool calling, and scalable enterprise inference. “The shift to inference is when this started. People realized that you can do inference on a GPU, but it's expensive, takes a lot of power and it's hard to fit into small spaces. CPUs are good for a lot of models up to certain sizes. They can deliver good enough performance for a number of concurrent users. So, depending on your workload and constraints, you can go and fit your workload into a CPU and have the outcome that you're looking for with the right KPIs. Once customers take a step back to figuring out how to balance the right number of CPUs with the right number of GPUs to achieve their outcomes, they can get better results at a better price point,” Pearson explains. “The other advantage with CPU is that you already have them in your data center. There's a lot of workload and inference that can run on CPU today, like agentic workload, tool calling and data orchestration. All that does not require a GPU. It actually opens up more GPU workload driven. So, areas where you need to do high concurrent and major inference workload with large models, you have more GPU capacity available for yourself to deploy those models on top of it,” Ibrahim adds. 💡 Get more insights! https://lnkd.in/dwcxRjAv #AIInference #CPUs #GPUs #EnterpriseAI
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David Linthicum liked thisDavid Linthicum liked thisVeeam Software’s AI North Star: Enterprises can’t scale AI until they understand their own data ⭐ Join #theCUBE’s David Vellante and Krista Case (Macomber) with Tony Colon, Chief Customer Officer of Veeam, as they discuss how Veeam’s AI maturity model is built around a simple North Star: helping enterprises understand where their data lives, validate AI readiness and deploy AI agents with governance. “The North Star is getting to a state where I would say these four pillars, which is discovering, assessing and engaging data. The last pillar being where you are ready for a very trusted turning on agents for everyone in your company and there's 12 sort of dimensions behind it. You don't have to be perfect in every single one. But I do think understanding where your assets are and understanding where your data is, is kind of knowing from unknown to known. That's our perfect state scenario. You can then start activating things based on department,” Colon explains. “The perfect definition of success is when a company can say that they are ready. This has been signed off and validated by a third party. Now, they're confident that they know. The other big thing that comes into this is it's never going to be perfect. I think the power of what we've brought to the table with being able to undo AI is something that I have not seen before. When you make a mistake, how do you undo that mistake? That's the power in not just the maturity model, but the technology keeping up with these models as well,” he adds. 💡Get more insights! https://lnkd.in/gVM8n8PD #AI #AIMaturity #Data #EnterpriseAI
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David Linthicum liked thisDavid Linthicum liked thisNVIDIA has posted a record-breaking quarter, reporting $81.6 billion in revenue as rising AI adoption continues to drive demand for its chips and infrastructure. The company also announced an $80 billion share buyback and raised its quarterly dividend from 1 cent per share to 25 cents. The results for the first quarter of fiscal 2027 marked an 85% rise from last year and a 20% jump from the previous quarter, driven by continued spending on AI systems and data centres. Quarterly earnings per share also came in above market expectations, further boosting Nvidia’s momentum in the AI race. #Nvidia #ArtificialIntelligence #AI #TechNews #StockMarket
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David Linthicum liked thisDavid Linthicum liked thisIntel sees “confidential AI” as the key to building trust in enterprise AI systems 🛡️ In this “Securing the AI Factory with Dell Technologies and Intel” exclusive, #theCUBE’s David Vellante speaks with Mike Ferron-Jones Go-To-Market Lead, Platform Security & Integrity at Intel, about how they’re extending confidential computing into AI environments, helping enterprises build trustworthy AI systems people can adopt at scale. “The AI system is more than just training or inference on the GPU. There's all kinds of processes in the pipeline from data ingestion, staging, and then training, inference, the output and the processing of the result. A lot of that happens on CPUs and in partnership with GPUs. There's a prerequisite in order to get value out of AI, which is trust. If somebody doesn't trust it, they're not going to use it and not get any value from it,” Ferron-Jones shares. “The technology areas that we are focusing on is the combination of confidential computing into an AI context to create confidential AI environments. With confidential AI environments, the processes that you're running in your AI systems are put inside a trusted execution environment that is cryptographically attested for integrity and is protected from exfiltration or interference by outside software or outside actors, so it goes a long way to helping to build trust in the system,” he adds. 💡 Get more insights! https://lnkd.in/di8Zm4AM #AISystem #GPU #ConfidentialAI #EnterpriseAI
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David Linthicum liked thisDavid Linthicum liked this"Abundant intelligence is here." That was the central line from Michael Dell's keynote at #DellTechWorld this week, framing a shift in how we think about enterprise tech. We aren’t looking at another standard infrastructure refresh cycle—we are looking at the start of a completely new operating model where intelligence is embedded across factories, hospitals, labs, and edge environments. I shared my top five takeaways for SiliconANGLE & theCUBE, looking past the keynote glow to analyze what this means for CIOs trying to operationalize this at scale. A few core thoughts: 1️⃣ AI is becoming infrastructure, not just software: Dell Technologies is effectively shifting the conversation from chatbots and copilots to the underlying physical systems enterprises must buy, secure, and operate. They aren't trying to win the AI race by owning the model layer; they want to own the enterprise deployment layer. 2️⃣ The Hybrid AI Factory: Michael Dell noted that 67% of AI workloads already run outside the cloud. In the agentic era, losing control of data, security, and IP is a massive risk. The answer is running models where the data actually lives. 3️⃣ The Reality of Agentic AI: While autonomous agents dominated the stage, an adoption gap remains. The vision of "digital workers" is highly compelling, but mainstream enterprises still need a clear playbook to bridge the gap between siloed data and autonomous execution. 4️⃣ Nailing the Hard Constraints: I was glad to see Dell tackle the pragmatics head-on—data orchestration, security blast radiuses for autonomous agents, and the massive power/cooling requirements (a single NVIDIA Rubin rack can draw over 130 kilowatts!). The Big Picture: Michael Dell delivered a great mix of big ambition and honest pragmatism. The next major hurdle? Turning this narrative into repeatable best practices for the "middle 80%" of enterprises that don't have elite, lighthouse-account resources. Check out the full article on for a deeper dive into the architecture, the anti-cloud positioning, and what’s next for the enterprise AI stack: 👉 https://lnkd.in/enzg3u7v #DellTechWorld #DTW2026 #EnterpriseAI #HybridCloud #AgenticAI #CIO #TechStrategy Anna Loftin David Brandt Angela Schmidt
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David Linthicum liked thisDavid Linthicum liked thisYou don’t need to rewrite COBOL to optimize your mainframe. In our webinar, we’ll show how organizations can: • Reduce batch COBOL on the CPU by over 80% • Significantly reduce batch processing times • Improve SLA windows • Ensure 100% business continuity By making COBOL workloads eligible for zIIP, teams can unlock additional capacity - with no interruption to daily operations. Keep your business running. Improve what already works. Create room for what comes next. Register now: https://bit.ly/4un6f2L #MainframeSmarter #IBMZ #COBOL
Experience & Education
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Linthicum Research
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Licenses & Certifications
Publications
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Unlocking the Power of the Cloud: Governance, Artificial Intelligence, Risk Management, Value
De Gruyter
Unlocking the Power of the Cloud delivers the definitive blueprint for governing in the cloud. Taking a groundbreaking 'business-first' approach, this book reveals how cloud computing creates unprecedented opportunities while fundamentally disrupting every aspect of corporate governance. The authors expose the critical intersection where cloud infrastructure meets AI deployment, showing you how to harness this convergence for competitive advantage.
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Cloud Computing and SOA Convergence
Pearsons
See publicationCloud Computing and SOA Convergence in Your Enterprise offers a clear-eyed assessment of the challenges associated with this new world—and offers a step-by-step program for getting there with maximum return on investment and minimum risk.
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Next Generation Application Integration: From Simple Information to Web Services
Pearsons
See publicationIn Next Generation Application Integration distributed computing and application-integration expert David S. Linthicum describes the effect that this new generation of middleware will have on traditional application-integration efforts. Using key industry examples and case studies, Linthicum reveals the techniques and practices that are necessary to revolutionize data-sharing for any company--from sole-proprietorship to Fortune 500.
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B2B Application Integration: e-Business-Enable Your Enterprise
Pearsons
See publicationMaking business applications communicate across corporate boundaries can be complicated, which is why system architects usually coordinate such projects. B2B Application Integration explains some of the approaches these system architects can take to get application A to talk to database B and Web site C, without simultaneously allowing hacker yahoos in for a look around. David Linthicum surveys technologies generally, and also the products that implement them. He's a fine teacher, able to…
Making business applications communicate across corporate boundaries can be complicated, which is why system architects usually coordinate such projects. B2B Application Integration explains some of the approaches these system architects can take to get application A to talk to database B and Web site C, without simultaneously allowing hacker yahoos in for a look around. David Linthicum surveys technologies generally, and also the products that implement them. He's a fine teacher, able to clarify complicated processes with words and illustrations. He's also well informed enough to express and support opinions on how various technologies are limited, which products live up to their claims, and how to implement specific mechanisms for application integration.
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Enterprise Application Integration
Pearsons
See publicationThis practical guide to implementing an EAI solution leads you through all the major steps, including identifying sources of data, building the enterprise metadata model, process integration, identifying application interfaces, mapping information movement, selecting and applying the technologies, testing, and maintenance. Other key topics include integrating packaged applications such as SAP R/3 and PeopleSoft, integrating the supply chain using EAI, the role of XML, and process automation…
This practical guide to implementing an EAI solution leads you through all the major steps, including identifying sources of data, building the enterprise metadata model, process integration, identifying application interfaces, mapping information movement, selecting and applying the technologies, testing, and maintenance. Other key topics include integrating packaged applications such as SAP R/3 and PeopleSoft, integrating the supply chain using EAI, the role of XML, and process automation. Comprehensive, practical, and clearly written, this essential resource will help anyone involved in this important business area understand the nature of EAI, its tools and techniques, and how to apply it for a significant business advantage.
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David Linthicum's Guide to Client/Server and Intranet Development
Wiley
See publicationClient/server guru David Linthicum shows developers how to use cutting-edge development tools and techniques to build real-life business applications. Technically detailed, the book delineates step-by-step procedures for creating these applications, explains how to select the most effective software and hardware tools, and shows how to accurately estimate project costs.
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Using Turbo C++
Que
See publicationThis book is for all levels of programmers who want an A-to-Z tutorial on Turbo C++--the highly successful product from Borland! Covers basic programming with Turbo C++, program control and data structures, structured programming, object-oriented programming, and more. Offers a tutorial on the C/C++ languages for beginning programmers. Contains valuable coverage of object-oriented programming topics for advanced-level users. Covers Version 3. -- Que Corp
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Ronald Beach, Ph.D. Virtual Leadership Expert
Ronald Beach, Ph.D. Virtual Leadership Expert
Ron Beach is a speaker, trainer, professor, and proud United States Marine Corps Veteran.<br>He’s a full professor of organizational studies at the University of Arizona Global Campus, where he teaches courses in the Bachelor of Business Administration degree program. He conducts classes globally, from his offices in Washington state to a balcony room on a cruise ship. Ron believes in staying connected with his team, no matter where he is or where team members are.<br><br>Earning his Ph.D. & Master's degrees in Organization and Management (with an emphasis in Leadership) from Capella University and a BLS in Liberal Studies from the University of Oklahoma; he brings his breadth of over 25 years of corporate experience as the Senior Director of US Manufacturing for a 750 million dollar a year electronic data storage division and a United States Marine electronic countermeasures technician while supporting operations in Laos and Cambodia during the Vietnam War.<br><br>Being an Organizational Sociologist, Ron is one of a very small number from North America who has traveled to Cambridge, England, and earned the highly coveted Belbin Team Role Assessment Certification. <br><br>When he’s not working with his remote teams, you might find him scuba diving or sailing on a beautiful cruise ship to some foreign port with his wife. Spare time finds him pursuing his quest as a Titanic history buff.<br><br>He resides in the beautiful state of Chewelah, Washington, with his beautiful wife of 54 years, Wendy.
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