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JevAgentHarness: Decision Models for LLM Agent Control

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Related to

Introducing Strands Decider 2B: Open Source Decision Model Strands Decider 2B is an open-source decision model for LLM agents, directly addressing the same problem space of efficient tool-selection decisions that JevAgentHarness benchmarks and trains
Testing Behavioral Harnesses for AI Coding Agents Testing Behavioral Harnesses for AI Coding Agents shares the harness-based evaluation paradigm for agent decision-making, directly analogous to JevAgentHarness's benchmarking approach
Clef: Open-Source Decision Models and RL Fine-Tuning Duplicate/variant of Clef open-source decision models entry — JevAgentHarness directly benchmarks this class of decision models for LLM agent tool selection
Clef: Open-Source Decision Models and RL Fine-Tuning Clef provides open-source decision models and RL fine-tuning for agent control, making it a core technical component that JevAgentHarness would benchmark and evaluate

Supports

Thinking Before Thinking: Scaling Agentic Inference Through Meta-Reasoning Meta-reasoning for scaling agentic inference addresses the same computational efficiency problem JevAgentHarness tackles — deciding when and how to invoke tools without full LLM inference
The Ultimate Guide to Multi-Harness RL The Ultimate Guide to Multi-Harness RL provides the reinforcement learning training methodology that JevAgentHarness implements for training decision models in agent control

Object-Oriented Harness: Evolving Agent Harnesses through OO Design Both focus on LLM agent harnesses - JevAgentHarness uses decision models for control while OO Harness uses object-oriented class hierarchies for optimization, representing complementary architectural approaches to the same problem
Object-Oriented Harness: Evolving Agent Harnesses through OO Design Both focus on agent harnesses for LLM control; JevAgentHarness uses decision models while OO Harness uses object-oriented class hierarchies as the organizing principle
How To Use Decision Models For Evals JevAgentHarness uses decision models for LLM agent control, sharing the same core concept of applying classification decision models to agent/eval contexts
How To Use Decision Models For Evals JevAgentHarness uses decision models for LLM agent control, sharing the same core concept of applying decision models to AI evaluation and control scenarios

Type:	link
First published:	Friday, 16 October 2026 at 18:59 UTC
Location:	https://arxiv.org/abs/2610.21412v1
URL:	https://mattwood.fyi/i/b5f880ab

I'm Matt Wood, and this is For Your Information. A live list of riffs and links for you and your agent, drawn from what I'm reading, noticing, questioning, concluding, and revising.

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