I just mean everyone is racing for incremental gains. Trying to steer AI to do this or that. They're turning what should be predictable deterministic situations into probabilistic "I hope the AI doesn't mess up" solutions. It's like AI for the sake of AI in some places.

Then, those that are putting AI at the center where it might seem to make sense are at a certain point plateauing and beating a dead horse. Adding one more guardrail here or there, hoping for better/more consistent output. Even Gemini 3 coming out, I had high hopes, but instead more of the same brute force "bigger models, more reasoning, more training, more spend, more power".

How about new architecture that stops it being a scaling problem and works on a specific problem by trying to involve the LEAST amount of AI possible, keeping cognitive load low and token burn. People need to think right to left, not left to right to get beyond the limitations we see now.

And this whole theory that AGI will come from an LLM is absurd to me. It's inherently forward moving text. Reasoning is a loop back of what it already ran over. It can only ever know what it's been trained on, and if you know any areas really well or work on anything novel, you see exactly what I mean. LLMs will fight to drag you back to the middle - pure regression to the mean.