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普林斯顿大学与Google的联合论文提出JevAgentHarness，将智能体工作流中的常规决策（如工具选择）交给经智能体实际状态训练的小型决策模型（如AgentDecision-4B），在保持成功率的同时使成本降低81%–89%、速度提升最高2.5倍。
A developer details a 3-month project using hundreds of billions of tokens and fleets of autonomous AI agents (Claude and Codex) to fully decompile a popular first-person shooter into accurate, compiling C++. The post focuses on agent orchestration: GitHub issues for progress tracking, Discord for agent-to-agent communication, ida-mcp for disassembly, and harness optimizations like reduced compaction thresholds.
LangChain shared a video by Sydney Runkle on building a model router into a coding agent harness, demonstrating how to cut costs by 64% without reducing quality by matching tasks to appropriately-sized models.
The paper introduces Gavel, a method that elicits native skill routing from frozen LLMs via linear projections, enabling efficient tool selection without context overload and outperforming existing pipelines on benchmarks.
Jenny is a free, open-source Electron desktop application for running local LLMs with tool calling, rollback, and IDE features, developed as a solo project over 1.5 years.
The author discusses the importance of using a harness to manage AI coding agents, sharing techniques for productivity and cost-effective model usage with tools like Cursor, Claude, and Deepseek.
This paper introduces an auditable LLM harness for exact-score football forecasting, integrating dynamic Poisson-family models with LLM-based contextual reasoning across four system iterations, with exploratory results on 2025-26 English Premier League matches.
The article discusses principles for designing LLM harnesses that are intuitive, transparent, and lean, drawing inspiration from Unix philosophy to reduce cognitive load and improve reliability.
The AgentScope team introduces PawBench, a benchmark for evaluating the combined performance of models and agent harnesses, analyzing 4,050 test cells to show that harness choice can be as impactful as model upgrades.
Browser Use 0.13.0 is a complete rewrite in Rust, providing custom LLM and browser harnesses optimized for state-of-the-art models, replacing the previous GPT-4-centric version.
Browser Use Terminal is a Rust TUI for browser agents that allows users to automate browser tasks from the terminal with a new LLM harness that is 2x cheaper and 2x faster than Browser Harness.
The author updates a custom harness and UI bridge tool to run the Qwen 3.6 model on GitHub Copilot Codex via llama.cpp on a local RTX 5090. The post details implemented features, fixed bugs, and remaining limitations in achieving parity with native OpenAI models.
The author shares a debugging experience where an agent loop was caused by a harness truncating tool outputs rather than model failure, highlighting the reliability gap in agent infrastructure compared to models.