Dave Linthicum Is Not AI

Enterprise AI is entering its most dangerous phase: the moment when spending outruns judgment. Companies are rushing into pilots, model deals, consulting engagements, and platform commitments before they have defined the business problem, cleaned up the data, or built the operational discipline required to make any of it work. That means the next chapter of AI will not be defined by breakthrough s...

  In a world increasingly dominated by technology, some AI gadgets take the cake for sheer absurdity. This article dives into five of the silliest and downright stupid AI gadgets that are more entertaining than practical. From smart toasters that burn your bread with a personalized message to robotic pets that can hardly fetch, these inventions are a testament to the fact that not all tech is crea...

Everyone is talking about autonomous AI agents like they're cheap digital employees, but the real story is far more complicated. In this video, I break down what actually happens when you let AI agents plan, loop, call tools, retry steps, update memory, and collaborate across workflows. On paper, the token costs can look surprisingly low. In practice, those costs multiply fast when you add multipl...

AI fatigue is the growing sense of exhaustion, skepticism, and disengagement that occurs when individuals and organizations are overwhelmed by the constant push to adopt, integrate, and manage new AI tools. It manifests as decision paralysis, reduced productivity, and declining trust in AI initiatives, even as investment and hype continue to rise. In enterprise settings, this fatigue often stems f...

Generative AI is moving into the enterprise faster than most organizations can properly evaluate it, and that speed is creating a dangerous blind spot. In this video, David Linthicum examines the growing token trap facing enterprises that are building applications, workflows, and agentic systems on top of remotely hosted large language models. What looks inexpensive today may not remain inexpensiv...

This video breaks down five underrated ways businesses can use AI that go far beyond writing captions, emails, and generic content. Instead of repeating the same obvious advice, it focuses on practical strategies that help companies move faster, make better decisions, and uncover hidden opportunities inside their own operations. You'll see how AI can turn everyday conversations into reusable busin...

Over the past year, the AI industry has begun to retreat from some of the more aggressive claims it made during the peak of the generative AI boom. In 2023 and 2024, many executives, investors, and commentators suggested that AI would rapidly transform white-collar work, deliver near-human autonomous agents, and generate huge economic returns almost immediately. By 2026, the tone has become notice...

AI robots have not failed because the idea was foolish; they have disappointed because the real world is harder, costlier, and less predictable than the hype suggested. Many were introduced as machines that would cut labor costs, improve safety, and deliver smoother service than humans. Instead, several high-profile deployments exposed the limits of current robotics. Walmart dropped shelf-scanning...

Artificial intelligence was supposed to arrive with excitement, optimism, and a sense of progress. Instead, in many places, it is being met with skepticism, frustration, and growing resistance. This video explores why public opinion around AI seems to be shifting and why more communities, workers, artists, and everyday consumers are starting to push back. From fears about job displacement and misi...

Everyone in tech wants to sound visionary, so they slap "AI-first" on every strategy deck and call it transformation. But turning AI into your business religion is how companies waste money, confuse priorities, and build expensive systems nobody actually needs. In this video, I break down why "AI-first enterprise" is a dangerous phrase, why it repeats the same mistakes we saw with cloud, blockchai...

In this video, we look at one of the biggest mistakes teams make with modern technology: assuming every business problem needs AI. Sometimes AI is the right answer. Sometimes traditional software is faster, cheaper, safer, and easier to explain. The real skill is knowing the difference. We break down the patterns that make a system a strong fit for AI, including messy inputs, prediction, classific...

Big Tech is doing what Big Tech always does: taking a promising idea, slapping a trendy label on everything, and selling it like a revolution before the business value is proven. In this video, David Linthicum breaks down how agentic AI is quickly becoming the latest enterprise buzzword, with vendors pushing terms like agentic cloud, agentic data, and agentic everything else, whether the technolog...

In this video, we teach you the basics of agentic AI in just 10 minutes. If you've heard the term but aren't sure what it means, this beginner-friendly breakdown will make it simple. You'll learn what agentic AI is, how it differs from traditional AI chatbots, and why it matters so much right now. We'll walk through how agentic systems work, including goals, planning, actions, tools, and feedback...

In this video, David Linthicum explains why the future of AI should not be judged by the pace of data center construction. Recent headlines about delayed or canceled data center projects have led many people to assume that AI growth is in trouble, but that conclusion misses the bigger picture. AI is not fundamentally about building more infrastructure. It is about using technology in smarter ways...

Most AI gadgets are either overhyped, half-baked, or just not worth the money. In this video, I break down 10 AI-related gadgets that are actually worth buying — the ones that offer real utility, save time, improve convenience, or are genuinely fun enough to keep using.   We're covering everything from smart glasses and AI note-taking wearables to smart rings, translation devices, robot vacuums, s...

AWS, Microsoft, and Google built their cloud empires on scale, but in AI, scale is starting to look like overhead. In this video, David Development Income breaks down why the hyperscalers may be pricing themselves out of the AI market just as demand is exploding. The core issue is simple: when the same class of AI workload can run on a neo-cloud, private cloud, sovereign cloud, or even on-prem inf...

AI is no longer just a workplace upgrade—it's becoming a workplace battleground. Across the U.S., U.K., and Europe, nearly 29% of workers admit they've actively sabotaged their company's AI strategy, revealing just how deep the resistance runs. And the biggest surprise? Gen Z, often seen as the most tech-native generation, is leading the rebellion, with 44% saying they've pushed back against AI ro...

These news reports document a disturbing pattern in modern policing: facial-recognition systems are often presented as investigative tools, but in practice a bad algorithmic match can quickly become the basis for handcuffs, jail time, and lasting personal harm. In the publicly known U.S. cases below, people were identified by AI face recognition, that identification was wrong, and police action st...

AI PCs are the tech industry's attempt to rebrand premium laptops as the future of computing by stuffing them with AI messaging, dedicated NPUs, and promises of smarter everyday experiences. In theory, these machines combine CPUs, GPUs, and neural processors so tasks like transcription, image generation, search, translation, and webcam effects can run locally instead of entirely in the cloud. In p...

Everyone's selling "AI will replace your job" like it's already done. This video drags that hype back to Earth. We break down why flashy demos, viral tweets, and billion‑dollar valuations don't equal reliable systems in the real world. You'll see where today's models shine—drafting, summarizing, brainstorming—and where they still faceplant: hallucinations, brittle agents, security landmines, and t...

Consulting firms have turned AI into a default prescription: lead with a glossy demo, label it "transformation," and let the client's budget absorb the experimentation. But most organizations don't need more complexity—they need clearer processes, cleaner data, stronger controls, and leaders who will make hard operational decisions. When consultants push AI into problems that are fundamentally abo...

Everyone's talking about AI—but not everyone actually understands it. In this episode, we take a humorous (and slightly savage) look at the rise of "AI posers": people who sprinkle buzzwords like confetti, post hot takes with absolute certainty, and somehow land influencer status or even executive roles without the fundamentals to back it up. The problem isn't that AI is hard (it is). The problem...

This video takes a hard look at the spectacle surrounding this week's Nvidia conference and asks the question too many people in tech refuse to ask: where is the real innovation? Instead of breakthrough ideas, what we keep seeing is bigger branding, louder promises, recycled narratives, and the same AI talking points wrapped in more expensive marketing. The industry keeps calling this disruption,...

This video breaks down a new paper,  Remote Labor Index: Measuring AI Automation of Remote Work , and why it challenges the biggest claims in the AI hype cycle. Instead of scoring AI on narrow tests, the researchers evaluated frontier systems on 240 real freelance projects across 23 categories of paid remote work, using actual briefs, input files, and human-created deliverables as the benchmark. T...

In this video, I dive into McKinsey's headline-grabbing claim of employing 25,000 AI "agents" as if these bits of software are somehow interchangeable with human employees. Let's be blunt: this reveals how little McKinsey—and much of big consulting—actually understands about what AI agents are, what they  aren't , and where their real value lies. What we're seeing is not a revolution in talent str...