Show HN: Springdrift – A persistent runtime for long-lived LLM agents (github.com)

Springdrift is a groundbreaking persistent runtime designed for long-lived LLM agents, enabling them to remember past interactions and learn from their experiences over extended periods. Unlike traditional AI assistants that reset every session, Springdrift equips agents with memory and self-awareness, allowing them to maintain continuity and actively manage their tasks. This shift transforms agent behaviors from mere execution of commands to proactive decision-making that reflects a deeper understanding of context and relationships, much like a professional retainer or a guide dog that offers domain-specific judgment. Significant for the AI/ML community, Springdrift integrates several advanced features including auditable execution (with append-only memory), structured self-state representation, and a normative calculus for safety. These elements ensure each decision is traceable and accountable, enhancing trust in autonomous AI systems. The design supports continuous improvement, where agents learn and adapt through interaction history, ultimately becoming more effective at serving their users. Built using Gleam on the Erlang/OTP environment, Springdrift's architecture signifies a substantial advancement in the development of persistent AI agents capable of sophisticated reasoning and self-diagnosis, marking a shift towards more reliable and accountable AI technology.