Keep your agent harness minimal, folks. This paper from MIT CSAIL shows why. (bookmark it) While being very minimal it looks effective and p…

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

// Model or Harness // Great paper if you are building with agents in production. (bookmark it) It organizes 41 agent failure modes by the i…
Nice little survey on Terminal Agents. It provides good information on what exactly is a terminal agent, and why do harness comparisons keep…
Progressive disclosure in agents doesn't scale. And its benefits seems agent harness dependent. (bookmark this one) Finally there is a prope…
Great paper on self-evolving agent harnesses. Self-evolving agent harnesses have two practical problems: 1. Search is slow, because every ca…

Source: DAIR.AI (X) | 2026-09-26

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