VoltMem didn't start because I kept hitting bugs in production agents.
It started with a conversation about how memory actually works — why some beliefs stick for decades while others evaporate in hours, and what triggers the audit when an old calibration stops matching present reality. That led to continual-learning research on the stability–plasticity tradeoff, and then to a structural parallel in agent memory: most layers treat every fact the same at write and search time.
The Berlin → Paris Problem
Most memory systems treat "I live in Berlin" (volatile) with the same protection as "I prefer concise answers" (stable). VoltMem differentiates them by domain.
Your AI assistant knows you live in Berlin. You moved to Paris three months ago. It still thinks you live in Berlin. Meanwhile, the fact that you prefer concise answers — stable for years — gets the same grip as "currently working on a database migration," which you finished last week.
