AI Agents

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Microsoft Open Sources code-testing-generator: a Polyglot Unit-Test Agent That Hits 92.1% Task Completion Versus 78.9% for Stock Copilot

Microsoft has open sourced code-testing-generator, a polyglot agent that writes unit tests and then proves they work. It ships in the dotnet-test plugin inside the MIT-licensed dotnet/skills repository. The agent targets a gap that coding assistants usually leave open. A prompt like ‘generate unit tests’ does not say which framework, file location or assertions to […]

Microsoft Open Sources code-testing-generator: a Polyglot Unit-Test Agent That Hits 92.1% Task Completion Versus 78.9% for Stock Copilot Read More »

Cloudflare Introduces Kitesurf: An Agent-First Web Browser That Runs Entirely in V8 Isolates on Cloudflare Workers

Cloudflare has released Kitesurf, a stateless web browser built specifically for AI agents. It runs entirely in V8 isolates on Cloudflare Workers, with no Chromium underneath. Browser engines like Chromium were built for humans, and their memory and compute overhead makes one-browser-per-agent prohibitively expensive. Agents do not need tabs, extensions, or pixel-perfect 60-fps rendering. They

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Prime Intellect Releases Prime Agent: An Open-Source RLM Harness Where Sub-Agents Are Function Calls Inside Persistent IPython Kernel

Prime Intellect has open-sourced Prime Agent, a self-improving coding harness designed around two abstractions, the Recursive Language Model (RLM) and Continual Harness. Fixed tool schemas and context compaction force a model to work around its own scaffolding. Prime Agent replaces both with a persistent Python REPL and a rewritable harness. With Opus 5, it reports

Prime Intellect Releases Prime Agent: An Open-Source RLM Harness Where Sub-Agents Are Function Calls Inside Persistent IPython Kernel Read More »

Microsoft’s SkillOpt Shows Optimized Agent Skill Artifacts Transfer Across Model Scales and Between Codex and Claude Code Harnesses

SkillOpt is a text-space optimizer developed by a team of researchers from Microsoft, Shanghai Jiao Tong University, Tongji University, and Fudan University. SkillOpt trains a single natural-language skill document while the target model stays frozen. An optimizer model reads scored rollouts and proposes bounded add/delete/replace edits. A held-out selection split accepts an edit only when

Microsoft’s SkillOpt Shows Optimized Agent Skill Artifacts Transfer Across Model Scales and Between Codex and Claude Code Harnesses Read More »

Meta AI Releases Muse Code (Beta): A Terminal Coding Agent Powered by the New Muse Spark 1.2 Model

Meta AI has released Muse Code (in beta), a terminal coding agent in beta, powered by its new Muse Spark 1.2 model. Meta positions the pair as its next step toward the frontier, with larger models on the way. Muse Code targets complex software engineering across large repositories: it plans changes, writes code, and validates

Meta AI Releases Muse Code (Beta): A Terminal Coding Agent Powered by the New Muse Spark 1.2 Model Read More »

agentic platforms

The 9 Best Agentic SDLC Platforms for Engineering Teams in 2026

Ask most AI development tools to do something, and they wait for a prompt. That works for a developer sitting at a keyboard. It does nothing for the bug filed at 2 am, the security finding that sat untriaged for a week, or the pull request comment nobody followed up on. The work that slows

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CopilotKit Open Sources Channels SDK: An MIT Licensed Library That Runs Any AG-UI Agent Inside Slack And Microsoft Teams

CopilotKit has just released the Channels SDK. It is an open source library that puts an existing agent inside a messaging platform. The core assumption is focused and verifiable. You already have an agent. It already has a model, tools and business logic. Channels gives it a place to work with people, without a rewrite

CopilotKit Open Sources Channels SDK: An MIT Licensed Library That Runs Any AG-UI Agent Inside Slack And Microsoft Teams Read More »

Agent Harness vs Loop vs Graph Engineering: A Technical Guide

One of your colleagues asserts that “we require improved loop engineering,” yet the fundamental issue lies within the harness itself. Others may create graphs with 40 nodes before they observe how the agent executes a given task at a single time. Does this sound like something you have encountered before? This ongoing confusion surrounding agent

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Building an Advanced AI Skill Security Auditing Pipeline with NVIDIA SkillSpector, LangGraph, YARA Rules, SARIF, and CI Policy Gates

In this tutorial, we build a workflow for evaluating the security posture of AI skills with NVIDIA SkillSpector. We create a synthetic skill marketplace containing clean, risky, malicious, and MCP-based examples, then scan each skill through SkillSpector’s LangGraph inspection pipeline. We examine risk scores, categorized findings, confidence levels, analyzer completeness, and executable-script indicators before organizing

Building an Advanced AI Skill Security Auditing Pipeline with NVIDIA SkillSpector, LangGraph, YARA Rules, SARIF, and CI Policy Gates Read More »

Y Combinator Open-Sources QM: An MIT-Licensed Multiplayer Agent Harness That Runs In Slack And The Web

Y Combinator team has open-sourced QM (quartermaster), the multi-agent harness it uses internally. QM is described as a multiplayer agent harness for work, running in Slack and on the web. YC team runs QM across accounting, legal, events, and engineering, including building QM itself. The whole project ships under the MIT license. YC frames the

Y Combinator Open-Sources QM: An MIT-Licensed Multiplayer Agent Harness That Runs In Slack And The Web Read More »