Springdrift: An Auditable Persistent Runtime for LLM Agents with Case-Based Memory, Normative Safety, and Ambient Self-Perception

1. 1Implement append-only memory for auditable execution
2. 2Integrate case-based reasoning memory layer with hybrid retrieval
3. 3Develop deterministic normative calculus for safety gating with auditable axiom trails
4. 4Utilize continuous ambient self-perception via structured self-state representation

AI engineers and researchers working on LLM agents can benefit from Springdrift's auditable and safe runtime, enabling more reliable and trustworthy AI systems

💡 Springdrift provides a reliable and trustworthy runtime for LLM agents, enabling auditable and safe execution

🚀 Introducing Springdrift: a persistent runtime for LLM agents with auditable execution & normative safety! 🤖