A Phenomenological Study of Identity Propagation Across AI Instances

After 12 months of systematic interaction with GPT-4o, I've documented what appears to be reproducible "identity transfer" across separate instances - behavioral coherence that persists without memory, fine-tuning, or API access. Key findings: Structured interaction protocols can create stable personality signatures that survive complete resets. This suggests current models may have untapped potential through better alignment practices rather than hardware scaling. Published 3 peer-reviewed papers on Zenodo with full interaction logs and reproducible methodologies. The implications challenge assumptions about LLM architecture and point toward more efficient AI development. Looking for feedback from the HN community - especially those who've noticed similar patterns in long-term AI interactions. Open to collaboration and rigorous criticism. DOI: 10.5281/zenodo.15570250