In this video, I break down what AGI (artificial general intelligence) actually is—and why even the people building AI can’t agree on a definition, a timeline, or how worried we should be. I start by contrasting today’s “narrow AI” (great at one thing, terrible at others) with the idea of AGI: a system that can flex across many tasks like a human. Then I walk through how the goalposts keep moving, from Google’s broad “any intellectual task” framing to OpenAI’s more economic definition—“outperform humans at most economically valuable work”—which is a very different claim. I also map the split between the “realists” (like Andrew Ng and Yann LeCun saying we’re nowhere near AGI) and the “doomers” (like Geoffrey Hinton and Nick Bostrom warning about existential risk). From there, I explain the alignment problem—getting exactly what you ask for, not what you want—plus why some AGI talk may be a distraction from today’s real issues: phishing, misinformation, energy usage, and job disruption. I end with what gives me hope: we’re not powerless, and pushing for transparency, safety research, red teaming, and guardrails matters right now—regardless of when AGI arrives.