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HarnessBridge: Learnable Bidirectional Controller for LLM Agent Harness

BACKGROUND
2 SIGNALSFIRST DETECTED 12 June 2026
Narrative synthesis pending — 2 signals collected.
How the story developed
28 Sept
12 Jun
Other feeds and industry voices
25 Apr
The Last Harness You'll Ever Build

arXiv:2604.21003v1 Announce Type: new Abstract: AI agents are increasingly deployed on complex, domain-specific workflows -- navigating enterprise web applications that require

REPORT · WHAT · ArXiv CS.AIOPEN STORY
11 May
CASCADE: Case-Based Continual Adaptation for Large Language Models During Deployment

arXiv:2605.06702v1 Announce Type: new Abstract: Large language models (LLMs) have become a central foundation of modern artificial intelligence, yet their lifecycle remains

REPORT · WHAT · ArXiv CS.AIOPEN STORY
22 Apr
ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward System

arXiv:2604.18789v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) is central to aligning Large Language Models (LLMs), yet it introduces a critical

REPORT · WHEN · ArXiv CS.AIOPEN STORY
2 May
In-Context Prompting Obsoletes Agent Orchestration for Procedural Tasks

arXiv:2604.27891v1 Announce Type: new Abstract: Agent orchestration frameworks -- LangGraph, CrewAI, Google ADK, OpenAI Agents SDK, and others -- place an external orchestrator

REPORT · WHAT · ArXiv CS.AIOPEN STORY
2 Oct
Measuring the Microtask Eligibility Gap: When Is an Off-the-Shelf SLM Enough for an Agent Harness?

arXiv:2610.00025v1 Announce Type: new Abstract: Agent harnesses increasingly want to run small language models (SLMs) on the microtasks around a frontier large language model

REPORT · WHEN · ArXiv CS.AIOPEN STORY
13 Apr
DRBENCHER: Can Your Agent Identify the Entity, Retrieve Its Properties and Do the Math?

arXiv:2604.09251v1 Announce Type: new Abstract: Deep research agents increasingly interleave web browsing with multi-step computation, yet existing benchmarks evaluate these

REPORT · WHAT · ArXiv CS.AIOPEN STORY
27 Apr
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond

arXiv:2604.22748v1 Announce Type: new Abstract: As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment

REPORT · WHAT · ArXiv CS.AIOPEN STORY
12 May
When Agents Overtrust Environmental Evidence: An Extensible Agentic Framework for Benchmarking Evidence-Grounding Defects in LLM Agents

arXiv:2605.08828v1 Announce Type: new Abstract: Large language model agents increasingly operate through environment-facing scaffolds that expose files, web pages, APIs, and logs.

REPORT · WHEN · ArXiv CS.AIOPEN STORY
Sources
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