LLMs are already more capable than +50% of the population at information tasks, and work so fast that if you're willing to accept a relatively modest dip in quality, you can get things done 10~20x faster than any human could do things, and that's mostly because the human prompting the machine is the bottleneck that stops it from being +100x.

Even if it never meets whatever arbitrary definition of"AGI" you want to come up with, it's extremely useful, and as long as there is deterministic feedback that helps point in the direction of a solution, it's damned close to AGI, because several of these systems can absolutely iterate onto a solution.

That's part of why these things are getting so good at agentic coding: even if they hallucinate, the compiler/interpreter says "nope, not a thing", and the LLMs says "well that's my objective source of truth, so I'll try something different", and it just keeps going until it gets something done.
If the model starts freaking out and deleting stuff, RL pushes it away from that basin.

People growing too accustomed to things too fast is a problem, but I think you fully appreciate how much it applies here. If we went from the Attention is all you need paper to an agent like Claude Opus 4.6 in a year, people would have fully accepted that AGI was here and had the most epic existential crises.

We've seen the LLMs grow up, with all the growing pains, so while top tier LLMs are doing real work, we'vegor people saying "I remember when you didn't know how many 'r's are in 'strawberry'", like parents saying "I remember when you used to shit you pants" to their children who are grown and on their own.

We'll slide right past some version of AGI, and people will never accept it.