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Introduces KoboldCpp Agent, a built-in agentic harness for easy code creation and general tasks with support for MCP tools and third-party backends, while also alerting to a fake phishing site targeting users.
This article shares a prompt and practical guidelines for improving the token efficiency of LLM agent harnesses, based on lessons learned at Cursor, aiming to reduce costs without sacrificing task quality.
Introducing Strands harness, a new open-source agent harness that delivers frontier performance with 28% lower token cost compared to other harnesses like Claude Code, supporting multiple AI models and easy deployment.
LangChain and Typesafe AI are hosting a live session on building an agent harness with Jev, scheduled for today at 11am PT / 2pm ET.
Google Research has started researching Recursive Self-Improvement for Agent Harness, focusing on automatically iterating prompts, tools, memory, and control flow without model retraining. This harness-level approach is seen as clearer and more practical than model-level RSI.
The author compares six agent harness projects, evaluating their strengths and ideal use cases with an honest, non-hype approach.
The article critically examines Jev, an AI model optimized for quick, structured outputs and cost-efficiency, while questioning the reliability of its judgments compared to larger models.
Omar Saroof shares excitement about integrating Jev into custom harnesses, emphasizing its potential to enable faster, cheaper, and more reliable AI workflows and agent experiences.
NVIDIA's SoL-Pi is an open-source agent harness that reduces token usage by 35-64% and API costs by 50-54% by automating the inspection and refactoring of AI workflows for efficiency.
The paper introduces SoL-Pi, an automated harness discovery method that reduces token usage by nearly half and cuts API costs by about a third while maintaining performance on benchmarks using models like GPT-5.6 Sol and Opus 5.
The article explains the Unified Harness Protocol (UHP) and HarnessRouter, which standardize agent execution across different runtimes like Codex and Claude Code, enabling products to avoid dependency on a single harness.
The tweet advises using MCP tools for building custom agent harnesses because frontier LLMs are highly familiar with MCP, making testing and integration easier, based on the author's positive experience.
SoL-Pi introduces a method for recursively scaling auto-research loops in coding agents, achieving significant token and cost reductions while maintaining performance on benchmarks.
LabAgent is an AI agent system designed to customize research hubs for scientific discoveries, enabling reproducible and continuous laboratory work across various biological domains and outperforming commercial generalist agents.
Perplexity launched Portable Computer on Windows RTX PCs, enabling local AI inference with an on-device agent harness, shifting the focus from inference cost to harness quality in the competitive landscape.
The author questions whether Git diffs remain adequate for human review as coding agents accelerate, suggesting a shift toward reviewing agent consequences and decisions with enhanced harnesses for better supervision.
The author shares insights from building an agent harness for GPT-3.5 Turbo, emphasizing that code-based verification and guardrails are crucial for reliable AI agent performance.
The study isolates the effect of harnesses versus models in agentic coding systems using a contamination-controlled private benchmark, finding no consistent advantage for vendor-native harnesses with variations in cost and performance across tasks.
HarnessVLN is a zero-shot, training-free framework for embodied navigation that unifies perception, retrieval, grounding, navigation, recovery, and termination through a unified tool interface, achieving state-of-the-art results on benchmarks like R2R and RxR.
The tweet emphasizes building custom AI agent harnesses to optimize performance, citing Pi's adoption and discussing self-improving algorithms and local models for better control and efficiency.