The tsunami is here. It's real. And it's not going away.

Large language models, vision models, and their counterparts have reached a level of maturity where they're no longer the domain of early adopters and enthusiasts. These are practical, production-ready tools reshaping how we work, create, and solve problems.

We have a moral imperative to understand how this changes economics

There's no question that AI is transforming everything from manufacturing to automotive to marketing and advertising. What remains unclear is the full impact on our workforce. If history is any guide, technological innovation eventually leads to net job creation—but we need to be honest about what "eventually" means and who bears the cost of transition.

The notion that displaced workers will seamlessly pivot into new tech roles oversimplifies a complex economic reality. A coal plant operator doesn't become a software engineer overnight, and pretending otherwise does a disservice to the people whose livelihoods are genuinely at risk. While we may see long-term job growth, the more urgent story is the sudden, heavy disruption to labor markets within an economic system that prioritizes profit above nearly everything else.

Our modern flavor of hypercapitalism has rarely seemed more inadequate than it does right now. We need serious conversations about transition support, retraining programs that actually work, and economic models that account for the humans in the system—not just the efficiency gains.

Creativity will continue to explode

Despite the hype cycles and the backlash, millions of people are using AI every day in genuinely valuable ways. Most of us are familiar with the low-quality outputs flooding social media—the generated images, the synthetic videos, the parade of self-proclaimed "AI Experts" on LinkedIn. For those of us who've spent decades in technology, the noise-to-signal ratio can be exhausting.

But here's what's easy to miss: the best craftspeople—artists, engineers, designers, 3D modelers, animators—are already using generative AI tools. You just don't notice, because they're still crafting. They're using AI as one tool among many, applying taste and judgment and years of hard-won skill to shape the output into something genuinely good.

That's exactly as it should be. AI amplifies capability; it doesn't replace craft. The gap between "AI-generated" and "AI-assisted by a skilled practitioner" is enormous, and that gap is where real value lives.

Energy concerns are valid—but we need realistic expectations

I spent two years living completely off-grid on my own 30-acre property in New Mexico. Solar panels, batteries, inverter, all of it—maintained by hand over time. I'm a genuine believer in clean energy. We have an extraordinarily bright star at the center of our solar system; using it just makes sense. It will outlast the carbon we're pumping from the ground by orders of magnitude.

But we need to be realistic about human behavior and energy consumption. Jevons Paradox emerged from patterns observed across multiple periods of technological innovation: when we develop more efficient technologies, we tend to increase overall energy usage because we're excited about what those efficiencies enable. The result is net growth in consumption, not reduction.

The uncomfortable truth is that we're unlikely to voluntarily reduce energy usage at scale. The genie doesn't go back in the bottle unless catastrophe forces it there—through lost infrastructure, lost knowledge, or lost capacity. That's not an argument against clean energy or efficiency; it's an argument for being clear-eyed about the trajectory we're on and planning accordingly.

The path forward requires both innovation and honesty about the systems we're building.