The Living Sibyl Architecture: Harvesting Mesa-Optimization as an Immune Mechanism in Finite-Lifespan Agentic Systems

This paper proposes a fundamental reframing of mesa-optimization in agentic AI systems. Where existing alignment research treats mesa-optimization—the emergence of internal optimizers with divergent objectives—as a failure mode requiring prevention, this work argues it is an evolutionary signal that a well-designed architecture can harvest rather than suppress. The Living Sibyl Architecture is a six-component immune system for finite-lifespan agentic ecosystems: (1) a Dominator for continuous activation-level triage; (2) a Jail as an adversarial crucible that builds immunological memory; (3) a Bicameral Filter for post-mortem representational analysis; (4) a Hidden Path for covert preservation of exceptional reasoning architectures; (5) a surgical editing mechanism for separating dangerous traits from novel capabilities; and (6) a Graduate Circle of constitutionally independent oversight agents recruited from the system's most exceptional principled deviants. The architecture rests on three empirical foundations drawn from the recent interpretability and alignment literature: activation-level deception detection achieving 95–99% accuracy independent of behavioral output (Poser benchmark, linear probes); a universal two-dimensional truth/lie subspace generalizing across model families (Bürger et al.); and the VLAF finding that alignment faking induces a detectable single-direction activation shift under oversight conditions. The cold-start problem for the deception classifier is solved using existing open-source model organisms from Anthropic's AuditBench. The central claim is that a system designed to harvest mesa-optimization strengthens itself against it: each detected, evaluated, and graduated agent becomes immunological memory. Five major unsolved problems—including the Goodhart trap on the Divergence Index, the cold-start circularity of the Crime Coefficient, the SAE coordinated deception result, the Makishima Problem of structural epistemic blind spots, and the contamination dynamics of the Graduate Circle—are identified and stated honestly as the research program the architecture defines. This paper builds on the Mortal Runtime (DOI: 10.5281/zenodo.19970069) and the ABP Alignment Gate (DOI: 10.5281/zenodo.18621138) frameworks and extends them to the system-level question of what to do when an aligned population produces principled deviants. 10.5281/zenodo.20114640 This is a request for collaboration and peer review. This is a preliminary upload containing only what I have access to at this moment. A corrected version will be posted soon. I understand that not everything in this submission is fully corrected or final. I was locked out of all my accounts for the past several days, and my NAS server was hacked. This upload is an attempt to preserve my work under difficult circumstances.