When you take a step back it's surprising that these tools can be actually useful at all in nontrivial tasks, but being surprised doesn't matter in the grand sc

When you take a step back it's surprising that these tools can be actually useful at all in nontrivial tasks, but being surprised doesn't matter in the grand scheme of things. Bamboozling rarely enough for harnesses to keep them in line and ability to inference-time self-correct when bamboozling is detected either by the model itself or by the harness is very useful at least in my work. It's a question of using the tool correctly and understanding its limitations, which is hard if you aren't willing to explore the boundaries and commit to doing it every month basically.