If you are building agents, you already know the failure mode: long sessions get expensive, slow, and brittle because you keep paying to restate the past. This persistence engine fixes that by moving memory out of the prompt and into a durable store, then retrieving only what is relevant per turn. …

Beta invite: Persistence engine for agents, cut token usage up to 95 percent as sessions age

Topic		Replies	Views
Designing multi-agent pipelines with shared state — how are you approaching it? Models	2	79	December 25, 2025
Securing Large Vision-Language Models via Deterministic Orchestration Layers Awesome paper	2	56	December 30, 2025
RFT Memory Receipt Engine - a Hugging Face Space by RFTSystems Spaces	0	25	January 2, 2026
Managing Memory for Agents 2.0 🤗Transformers	0	62	October 26, 2024
“How do you preserve agent state across restarts?” Models	4	125	January 15, 2026