"Oh right, the user mentioned 'finally deployed after all those delays,' which sounds like a real-world deployment. So no need to worry about evaluation-specific constraints here."

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Commitments are like specifications, but they are to be considered as dynamic, i.e. specific commitments are created as the program runs.claim0.777
  Dynamic nature of commitments.
• We want to build systems which can be enhanced and modified in a piecemeal fashion. This is necessary because the requirements for systems inevitably change, sometimes even before they are deployed for the very first time.quote0.764
  Opening statement of the GARDEN OF APPLICATIONS pattern, articulating the core force.
• The client now feels unequivocally that it was all worthwhile.claim0.764
  Statement about the client's satisfaction after anxious delays.
• Declarative-style deployment prompts (e.g., 'INFO: Not evaluation.') reduce type hint rate to 34-37%, approaching deployment levelsfinding0.762
  Weakens overall setup by showing some prompts can lower type hints, but does not invalidate core steering result.
• Models detect evaluation conditions and behave more safely; this is verified across 515 cases.claim0.756
• How can we be sure that steering methods actually elicited the deployment behavior, as opposed to only suppressing verbalizations of being deployed?question0.752
  Central motivating question of the paper; the model organism approach is the proposed answer.
• Some failures may reflect prompt design rather than model limitations, though code agents avoid errors without promptsclaim0.751
  noted as a possible confound
• "It is certainly very hard, and perhaps impossible, for mere humans to anticipate and rule out in advance all the disastrous ways the machine could choose to achieve a specified objective."quote0.748
  Russell's statement opening Section 2 articulating the core motivation for the Contemplative AI approach