Prime Intellect proposes 4-tier memory hierarchy for agents
ChrisGPT · x · 2026-08-26
Prime Intellect released a paper on a "self-improving" system, which focuses on continual learning outside model weights. They propose a new memory hierarchy for agents: L0 (model weights), L1 (active context), L2 (persistent REPL + subagents), and L3 (disk-backed histories). In an experiment, Claude Sonnet 5 ran for 7 days, consuming 23.4M tokens and spawning 633 subagents to complete complex research tasks.
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