RESEARCH · RESEARCH · #945
JAZ: a minimalist LLM agent framework with an 'invoke' primitive (arXiv:2609.26891v1)
The paper proposes JAZ, a minimalist LLM-agent framework that exposes a single LLM-based primitive, invoke, plus hooks for constraints and monitoring. With only prompting and no external memory or tool systems, recursive invoke lets the model write and execute code; JAZ outperforms Letta (MemGPT) by 8% at half the cost on the recall-heavy portion of StuLife and outperforms ACE by 4% at lower cost on AppWorld.
KEY POINTS
- The paper proposes JAZ, a minimalist LLM-agent framework that exposes a single LLM-based primitive, invoke, plus hooks for constraints and monitoring.
- With only prompting and no external memory or tool systems, recursive invoke lets the model write and execute code; JAZ outperforms Letta (MemGPT) by 8% at half the cost on the recall-heavy portion of StuLife and outperforms ACE by 4% at lower cost on AppWorld.
- It suggests a single, language-like primitive can replace specialized external systems for long-horizon recall and self-improvement, simplifying agent design and lowering costs.
WHY IT MATTERS
It suggests a single, language-like primitive can replace specialized external systems for long-horizon recall and self-improvement, simplifying agent design and lowering costs.