For years, big consulting firms have been selling "cloud and AI strategy" as if it were a product you can just buy off the shelf. In 2026, the jig is up. This video is your no‑nonsense buyer's guide to how large consulting firms should be engaged for cloud and AI work—what to let them do, what to keep in‑house, and where you're most likely to get burned.

We'll walk through the real incentives behind those "preferred partner" AI cloud recommendations, how vendor alliances quietly shape your architecture, and why so many roadmaps end up looking like a sales deck instead of an operating model. You'll learn how to structure engagements so you get industrial‑scale execution—landing zones, governance, migrations—without handing over your strategy, your data, or your future.

We'll cover the critical questions to ask before you sign, the red flags in proposals and SOWs, and how to demand deliverables that leave you stronger and more independent, not permanently dependent on the same firm. If you're a CIO, CTO, architect, or tech leader about to bring in a big consultancy for cloud or AI, watch this first. It might change how you buy—and what you're willing to buy.

Oracle is reportedly tied to roughly USD 56 billion in AI data-center financing, and Wall Street is treating it like a stress test, not a victory lap. In this video I break down why "build it and they will come" can turn into "borrow it and you will bleed." Data centers are fixed-cost monsters: power commitments, depreciation, and interest expense don't care if enterprise customers take six quarters to migrate workloads. If demand ramps slower than supply, Oracle's only lever is discounting—lower prices to fill empty capacity—which can crush margins right when debt service rises. That's how overbuilds become spirals: weaker cash flow leads to tighter financing, tighter financing forces cuts, cuts weaken competitiveness, and the cycle feeds itself.

I'll also compare Oracle's bet to the broader AI infrastructure boom—other builders using heavy leverage—and explain why a sector-wide capacity glut could trigger a price war. If you're an investor, operator, or just tired of AI hype, this is the cold-water analysis: what could go wrong, how it snowballs, and what signals to watch next. We'll talk contract reality, utilization math, and why "strategic capex" can become a balance-sheet hostage situation. Plus: the red flags—syndication strain, downgrades, and sudden price cuts.

In this crucial video, cloud security leader David Linthicum exposes a troubling statistic: 61 percent of cloud security incidents are completely preventable. Drawing on the latest security research, David reveals the most common—and avoidable—mistakes that leave enterprises vulnerable to cyberattacks, data leaks, and compliance violations. He breaks down the top culprits, from misconfigured cloud environments and weak access controls to lapses in ongoing monitoring and lack of employee training.

David explains why organizations often falter on basic security hygiene and shows how these oversights create easy targets for attackers. Importantly, he translates these findings into actionable solutions. Viewers will learn why regular audits, continuous education, and automated security tools are critical for reducing risk, and how building a security-first culture can close the door on costly incidents.

Packed with practical advice, this video gives IT leaders, security professionals, and business executives a blueprint for dramatically improving their organization's cloud security. Don't let your company become another statistic—discover how to avoid the 61 percent of incidents that should never happen, and transform the cloud from a weak spot into your enterprise's strongest line of defense.

Why did Microsoft stock drop even after a headline beat? In this episode, cloud analyst David Linthicum breaks down the market's "beat-and-drop" reaction to Microsoft's latest earnings and what it signals about Azure, AI, and hyperscaler spending. He explains how expectations for a clear cloud re-acceleration collided with guidance that sounded more like "we're investing ahead of demand," raising concerns about capital intensity and near-term margins. Linthicum walks through the optics around Azure growth, capacity build-outs for AI training and inference, and why investors are increasingly sensitive to capex without fast operating leverage.

The conversation also explores a structural shift in enterprise cloud choices—hybrid, private and sovereign cloud, colocation, and managed service providers—and how workload economics (egress, governance, and consumption creep) can make public cloud less attractive for steady-state compute. Finally, he balances the bear case with the bull case: Microsoft's distribution advantage across Microsoft 365, security, and developer tools, and the possibility that today's spend is strategic moat-building. If you want a clearer framework for reading cloud earnings, this video delivers. You'll learn what metrics to watch next quarter, how to interpret "capacity constraints" versus demand, and where AI monetization may show up first in pricing, usage, and margins.

The tech industry is brilliant at building new things—and terrible at admitting when it gets them wrong. In this video, I break down why our predictions about cloud, AI, big data, blockchain, metaverse, and more so often miss reality by a mile. From wildly optimistic analyst forecasts (including early cloud growth predictions that were way off) to vendor-driven hype cycles, we've built a system that rewards confidence, not accuracy.

I walk through concrete examples where the narrative sounded irresistible, the slideware looked perfect, and the pilots seemed promising—but large enterprises never followed at scale. The core problem isn't intelligence or innovation; it's confirmation bias, misaligned incentives, and a complete underestimation of real-world constraints: legacy systems, budgets, regulation, skills, and risk.

You'll learn how to recognize the telltale signs of hype, how to separate "cool demo" from "sustainable value," and how to ask the uncomfortable questions that cut through the noise. Whether you're a CIO, architect, engineer, or business leader, my goal is simple: help you stop getting pushed around by tech narratives—and start making grounded, reality-based decisions.

If you're tired of being sold "the future" that never quite arrives, this video is for you.

In this video, David Linthicum breaks down the sudden explosion of "agentic AI" playbooks, frameworks, and branded platforms now pouring out of the consulting industry. Every big firm wants to look like it owns the future of autonomous work, so the market is being flooded with glossy diagrams, maturity models, and "fast paths" that promise cheap, repeatable success—sometimes with language that feels close to a guarantee.

But agentic AI is not a plug-in. It's an architecture, and architecture only works when it matches your processes, data quality, controls, integration realities, and operating model. When frameworks lead with the platform instead of the problem, enterprises end up force‑fitting agents into brittle systems, over-building orchestration layers, and running old processes in parallel "just in case." The hidden costs show up later: governance overhead, constant tuning, fragile pilots, and disappointing ROI.

You'll learn the red flags to watch for, the questions to ask before funding an "agentic transformation," and how to pursue smaller, measurable wins without buying expensive theater. If you're a CIO, CTO, or business leader, this is your reality check before the next deck lands in your inbox. We'll also discuss when simpler automation beats agents—and when agents earn their keep.

Network-attached storage (NAS) is a dedicated, always‑on storage device that connects to your home or office network and lets multiple users and devices store, share, and back up data to a central box you physically own. In effect, it's your own private cloud: instead of renting space from iCloud, Google Drive, OneDrive, or AWS, you buy a NAS once and control the hardware, the capacity, and who can access it. This model is growing quickly; the global NAS market is already tens of billions of dollars in annual sales and is projected to roughly triple over the next decade, driven by exploding photo, video, and backup needs. Just as important as capacity is cost: a mid‑range NAS with several terabytes of usable storage often runs around 600 upfront, a figure that can undercut years of recurring cloud fees for 2–6 TB plans. Many consumers and small businesses are discovering that, at larger data sizes, NAS becomes cheaper over a three‑to‑five‑year horizon. And because the data lives on devices you own—often protected by encryption, redundancy, and local access controls—NAS is increasingly seen as a way to improve privacy, security, and peace of mind compared to relying solely on third‑party clouds.

Big Tech says it's "backup," "sync," and "convenience"—but what happens when your computer quietly starts moving your personal files into the cloud by default? In this episode, David Linthicum breaks down a growing industry pattern: technology providers designing defaults that automatically capture your data, route it into their storage platforms, and make that choice feel inevitable. We start with the Microsoft Windows 11 upgrade experience, where many users discover Desktop, Documents, and Pictures being pushed into OneDrive through folder redirection and persistent prompts—often without a clear, informed decision at setup. From there, we connect the dots to Apple's iCloud, where "it just works" can also mean "it just uploads," and to Google's Drive-first ecosystem that normalizes cloud storage as the primary home for files. Finally, we revisit AWS and the long-running idea that computing is something you rent—not own—turning the PC into a subscription and your data into recurring revenue. This isn't an anti-cloud rant: cloud storage can be genuinely useful. The issue is default capture, confusing consent, lock-in economics, and the shrinking space for truly local-first computing. If your files are your property, why do vendors treat them like a product funnel?