Are AGI timelines extrapolating the wrong axis?

Most AGI timelines extrapolate capability curves, which is reasonable if you believe the current architecture can in principle reach general intelligence by scaling. There is a different reading in which the architecture is good at one thing and bad at another, and what AGI actually requires lives on the bad side. The good side is computation inside a delineated frame. The bad side is moving across frames, recognizing when the world has shifted, and reorienting. Calling both intelligence runs them together. Separating them changes the timeline question entirely, including which kind of evidence should update the forecast. I recently gave a talk at the 6th International Conference on Philosophy of Mind in Porto arguing that AGI requires rationality on top of intelligence. You can watch it [here](https://youtu.be/D6hjtY0cm3s?si=5oI1HHg2iB7CKner). Three pieces carry the load. First, Savage's distinction between small worlds (delineated problem spaces) and large worlds (reality itself, with endless context, unknowable even in principle). Current AI systems are extraordinary inside small worlds and structurally limited in large worlds. Second, the frame problem from Dennett, which scaled models have not addressed: any system trying to reason in the world has to filter infinite irrelevant features, and pure algorithmic relevance-classification just inherits the same problem one level up. Living agents cut this with what Vervaeke calls relevance realization, a self-organizing process tied to having stakes in a world. Third, the empirical separation: Stanovich and colleagues show intelligence and rationality share only around thirty percent variance, with attention control shrinking the overlap further. If AGI requires the rationality side, scaling LLMs is climbing the wrong axis. If the axis claim is right, the singularity question shifts from when to whether and how. Artificial autopoiesis, embodied robotic agents with vital stakes, hybrid systems with grounded sensorimotor loops are the most-named alternatives, though none of them are close to current capability. Which of those bets do you think has the best decade-scale chance, and what observable result would change your view that the axis matters more than the scale?