Paper: The Forgetting Problem — Why Perfect Memory Breaks AI Agent Identity

New Paper: The Forgetting Problem We've published a new preprint exploring a counterintuitive idea: the better an AI agent's memory, the worse its identity becomes. 📄 Read the paper on Zenodo (CC-BY 4.0, open access) The Memory-Identity Paradox Every major AI agent framework is racing to build better memory. MemGPT, Mem0, A-Mem, MemoryBank — all optimize for remembering more, longer, more accurately. But we identified a fundamental tension: The more faithfully an agent remembers its experiences, the more vulnerable its intended identity becomes to experiential contamination. We call this the Memory-Identity Paradox. It manifests as: Persona Drift — gradual deviation from intended behavior due to accumulated context Value Erosion — relaxation of behavioral constraints through repeated boundary-testing Identity Contamination — adopting interaction patterns from adversarial users This isn't hypothetical. PersonaGym benchmarks show that models scoring 90%+ on persona consistency in short