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Perplexity has open-sourced Numbat, a security suite that monitors AI coding agents running on employee laptops and workstations, detecting and blocking dangerous agent behavior.
A practical guide for running local AI on consumer GPUs by pairing a large cloud model as an architect with smaller local models as subagents, using tools like OpenRouter and Hermes.
DarwinX evolves LLM agent harnesses via natural-selection-style population search with frozen model weights, improving verified performance across multiple benchmarks without benchmark-specific patching.
LangChain releases Deep Agents v0.7, a leaner agent harness that cuts base input tokens by 65% through removing the default system prompt, trimming tool descriptions, and making TodoListMiddleware opt-in, with comparable performance validated across multiple models.
Discusses the best framework for building an agent harness currently available.
JarvisHub is an open harness for canvas-native multimodal creative agents that treats an editable canvas as the user workspace, enabling long-horizon creative automation with inspectable and editable state.
TRL now supports training on agent harnesses out of the box through OpenEnv integration, enabling training with harnesses like opencode.
Harness Handbook provides a behavior-level manual for AI agent harnesses, linking system behaviors to verifiable code evidence to make harnesses understandable, auditable, and editable.
The Harness Handbook is a behavior-centric representation synthesized from agent harness codebases using static program analysis and LLM assistance, helping developers and coding agents locate code implementing specific behaviors. It introduces Behavior-Guided Progressive Disclosure (BGPD) to guide agents from high-level descriptions to relevant implementation details, improving localization accuracy and edit-plan quality.
Cline's agent harness is now available in JetBrains Air via ACP support, allowing users to power coding tasks directly in the app. A new Air release also adds Java language support and the ability to add various agents.
Helix-agi is an autonomous agent harness that uses a background pulse system and micro-RAG for memory, aiming to run fully local on small models. The developer discusses challenges with tool calling and seeks collaboration.
This article discusses an opinionated harness for encoding domain-specific structure into agent systems, with code demonstrations showing performance gains.
The author discusses building six AI agent harnesses and emphasizes the need for a dedicated database to track agent execution, state, and learnings, beyond just observability tools.
OpenSquilla releases v0.5.0, achieving performance surpassing Fable5 and reducing costs by 67% through intelligent routing and multi-model integration; also adds MetaSkills and Coding mode features.
Glean's engineering blog details their new agent harness using 100% programmatic tool calling via code execution, which reduces token usage by 24% compared to standard tool calling. The harness manages context with tool truncation and a sandbox filesystem for long-running complex workflows.
A developer recounts how a cryptic hint from an ex-Anthropic engineer ('check your score') led him to create a harness of files and commands (e.g., CLAUDE.md, init.sh, feature_list.json, etc.) that assess and improve Claude AI agent performance, turning the hint into a practical tool.
Flask author Armin Ronacher found that the tool-calling ability of the new Claude models (Opus 4.8, Sonnet 5) is degrading. The root cause is that RL post-training over-adapts to Claude Code's own tool schema, making alternative tool schemas increasingly difficult to generate correctly. The article reveals the phenomenon of models performing worse rather than better on specific tool-calling scenarios, offering an important caution for agent development.
Looking for testers for a custom agent harness.
The author compares three open-source AI agent tools—Pi, Goose, and OpenCode—describing them as operating at different layers of the AI agent stack: Pi as an agent harness/toolkit, Goose as a local workbench/orchestration surface, and OpenCode as a coding-first agent.
A curated collection of resources on harness engineering for AI coding agents, including a course, a Python tool (tau-ai), and blog posts from Anthropic and LangChain.