Relative difficulty of aligning consequence channels

Determine whether aligning the consequence channels that shape an adaptive drive is easier than specifying agentic harness logic.

Background

The proposed persistent architecture shifts part of behavioral control from externally specified objectives, verifiers, and stopping rules to environmental observations and consequences that shape adaptive persistence. The paper explicitly leaves unresolved whether securing and aligning those consequence channels is less difficult than hand-specifying the corresponding harness logic.

References

Three broader questions also remain open. The experiment does not establish that a transferable drive can be learned across heterogeneous agentic applications, that aligning consequence channels is easier than specifying harness logic, or that alignment remains stable under continued adaptation.

— Artificial Id: Drive and Persistent Alignment in Agentic AI  (2609.11911 - Shkolnikov, 10 Sep 2026) in Section 'Limitations'