Keep your agent harness minimal, folks.

This paper from MIT CSAIL shows why.

(bookmark it)

While being very minimal it looks effective and promising for building self-improving agents.

They present JAZ, an agent framework with one primitive, invoke. The LLM writes code, can call invoke recursively, and sees all of its inputs and history as variables in the code environment.

With prompting only and no memory system, it beats Letta (MemGPT) by 8% at half the cost on the recall-heavy part of StuLife.

On AppWorld it beats ACE, a self-improvement method, by 4% at lower cost.

Memory and self-improvement are usually built as separate subsystems. Here both are code the agent writes inside the loop, and hooks handle the constraints and monitoring you want to enforce.

Paper: https://arxiv.org/abs/2609.26891

Explore Paper: https://academy.dair.ai/papers/harness-as-a-language-a-minimalist-agent-framework-with-maximal-expressivity-2609.26891