GPT-6 Could Beat Fable 5.1. Would That Actually Mean AGI?

What would GPT-6 actually have to prove before anyone could call it AGI? A higher benchmark score is not a progress bar toward general intelligence. The real test is whether an AI system can succeed when the rules change, recover from mistakes, preserve constraints, handle interruptions, and produce work that survives independent inspection. In this video, we build a practical evaluation framework around a real-world scheduling challenge. We examine robustness, long-running tasks, coding, memory, scientific workflows, cybersecurity, permission design, safety, and oversight. The goal is not to report unverified GPT-6 results. It is to show what strong evidence would need to look like. You will learn how to separate a dramatic demonstration from a reproducible result, define success before testing, record human corrections, and decide whether an AI tool genuinely deserves a place in your workflow. Important: GPT-6 access and the capabilities discussed in this video are unconfirmed. The examples are proposed tests, not reported GPT-6 achievements. Do you think passing changed conditions would be enough to call a model AGI? Share your view in the comments. If this helped, please like the video and subscribe for more clear breakdowns of AI, emerging models, and the future of intelligence. #GPT6 #AGI #ArtificialIntelligence