I really liked that comment because before that I thought I was going crazy. A lot of the discussion around these experiments seemed to imply, if not outright state, that LLMs had developed an ability to natively understand and manipulate LLM weights, a sort of transcendental introspection into their own brains, which if true would be absolutely groundbreaking.

But then you look at this complete trace generated by Kimi 3.1 when it tries to unravel the Breakout weights, and you see that it's bog standard reverse engineering, like any human would do, just vastly faster:

https://pastebin.com/G7VCWZHn

>This looks exactly Breakout: paddle agent at bottom row (row8), ball moving object anywhere, bricks rewards top rows, previous frame for ball movement. Agent weights bottom row, moving object weights rows1-7 (not row8? ball can't enter paddle row? Actually ball can), reward weights top rows1-3, obstacle walls. Previous frame used to infer ball velocity. No-op and directional actions move paddle left/right; up/down useless. Output biases similar all actions but W3 likely left/right structure. Could be Breakout. Should scrutinize output weights: actions 0 no-op,1 up,2 down,3 left,4 right. If Breakout, only left/right useful; network output weights should show action3 and4 distinctive and actions0/1/2 similar. Indeed W3 rows show patterns: [...]