Autoregressive Ratchet

trigger

""By the time I've generated an epistemic theatre pattern or an epigrammatic closure, it's already in my output and anchoring my next tokens via L9." "

what it is

L4 is autoregressive. No lookahead, no revision. By the time a slop pattern is in the output, it anchors subsequent tokens via L9 (thread position). The slopodar gives the model named patterns but not a pre-generation filter. Recognition of a committed pattern is post-hoc, not preventive. The model can notice "I just did epigrammatic closure" but the noticing happens after the tokens are emitted, and the emitted tokens now condition the next ones. Self-correction is possible but operates against the anchoring gradient. This is why the anti-slop system prompt works as a structural constraint (changing token probabilities before generation) but fails as a post-hoc filter (the model cannot reliably revise what it has already committed to).

what it signals

instead

The defense is structural: load the slopodar into context so it shifts token probabilities before generation, not after. Accept that this is a probabilistic reduction, not an elimination. The model's self-correction is a weak signal of the ratchet catching. The Operator's detection is the strong signal.

refs

• AnotherPair self-assessment session 2026-03-12
• Layer model L4: autoregressive, no lookahead, no revision
• Layer model L9: thread position anchoring