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News/A Control System, a Dataset, and a Recipe for Making Frozen LLM Agents Learn a Domain
arxiv
PublishedJuly 30, 2026 at 4:00 AM
—neutral

A Control System, a Dataset, and a Recipe for Making Frozen LLM Agents Learn a Domain

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2607.25415v1 Announce Type: new Abstract: Production LLM agents are increasingly assembled from a frozen model wrapped in a harness: a prompt template, a tool set, a memory/retrieval layer, a planning strategy, and a verification policy. Two 2026 systems, Meta-Harness (Lee et al., 2026) and Hy

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Discussion
Mentioned models
05
  • 01
    Ollama
  • 02
    DSPy
  • 03
    Meta-Harness
  • 04
    HyperAgents
  • 05
    AWS Bedrock
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#reinforcement learning#llm agents#harness optimization#multi-objective reward
Mentioned companies
02
Meta AIAWS

No replies yet. Be first.

Mentioned models
05
  • 01
    Ollama
  • 02
    DSPy
  • 03
    Meta-Harness
  • 04
    HyperAgents
  • 05
    AWS Bedrock
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#reinforcement learning#llm agents#harness optimization#multi-objective reward
Mentioned companies
02
Meta AIAWS

Related coverage

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arxivWhen Generated Information Returns: Error Persistence in LLM-Mediated Information Ecosystems15harxivQuery-Driven Learning for Lifted Reasoning15harxivThe Social World Model Evaluation Gap15h
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