Software engineering

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

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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 […]

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

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Infrastructure, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Open Source, Software engineering, Staff, Tech News, Technology

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

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How to Secure AI Agents, MCP Servers, and LLM Apps in Production

agentic ai, ai, AI (Artificial Intelligence), AI Infrastructure, AI Shorts, Applications, Artificial Intelligence, deep learning, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Promote, Security, Software engineering, sponsored, Staff, Tech News, Technology, Uncategorized

Agents, MCP integrations, and LLM-powered applications are entering codebases faster than most security programs can track them. Mend.io’s new practitioner guide, ‘Securing AI agents, MCP servers & LLM apps: A practical framework’, targets that gap. It is organized around three moves: see what matters, fix what matters faster, protect AI in production and ships seven

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JetBrains Open-Sources KotlinLLM: Smart Macros That Generate Kotlin Source Code at Runtime and Hot-Reload It Through JDI

agentic ai, ai, AI (Artificial Intelligence), AI Infrastructure, AI Shorts, Applications, Artificial Intelligence, Editors Pick, New Releases, Open Source, Software engineering, Staff, Tech News, Technology

JetBrains Research Open-Sources KotlinLLM. KotlinLLM is an IntelliJ IDEA plugin for Kotlin/JVM projects that adds a language feature called Smart macros. A Smart macro is a regular Kotlin function call whose body is generated Kotlin code. The public API is deliberately small. asLlm<F, T>(from, hint) converts an input of type F into a typed value

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Nous Research Ships Three Integration Paths for Hermes Agent and Buzz, Block’s Open Source Nostr Workspace for Humans and Agents

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Model Context Protocol (MCP), New Releases, Software engineering, Staff

Nous Research has released Hermes Agent support for Buzz, Block’s open source, self-hostable workspace where humans and AI agents share the same channels. Buzz is built on Nostr. Every message is a signed event on a relay you own, and every participant, human or agent, is a keypair. That removes the bot-token model. Agents get

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Tencent Open-Sources AngelSpec: A Unified Training Framework for MTP and Block-Parallel Speculative Decoding on Hy3 Models

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Tencent has released AngelSpec, an open-source, torch-native training framework for speculative-decoding draft models. The release covers both autoregressive multi-token prediction (MTP) and the block-parallel DFlash family. Most speculative-decoding work searches for one drafter that scores well on an averaged benchmark mixture. Real serving traffic does not look like that mixture. AngelSpec treats workload heterogeneity as

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Meet Token Saver: An Open-Source MCP Extension Using Local Hybrid RAG to Cut Claude PDF Token Costs 90-99%

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AI developers, researchers, and professionals frequently hit a frustrating wall when analyzing large documents with LLMs: the hidden, compounding cost of context windows. Pasting a 200-page PDF into a chat isn’t a one-time charge. Because the conversation history is re-sent to the model on every single turn, that massive document is paid for again with

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Prompt Engineering vs Loop Engineering vs Graph Engineering: What Changes at Each Layer

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Shorts, Applications, Artificial Intelligence, Context Engineering, Editors Pick, Generative AI, Language Model, Machine Learning, Software engineering, Staff, Technology, Uncategorized

Three terms now compete for the same line in AI engineering job descriptions. Prompt engineering is the established one. Loop engineering entered the AI vocabulary in late 2025 and dominated developer discussion through June 2026. Graph engineering followed roughly six weeks later. They get used interchangeably. Should they be? The three are not competing techniques.

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Moonshot AI Open-Sources MoonEP: A Perfectly Balanced Expert Parallelism Library for MoE Training

agentic ai, ai, AI (Artificial Intelligence), AI Infrastructure, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Open Source, Software engineering, Staff, Tech News, Technology

Moonshot AI has open-sourced MoonEP, an Expert Parallelism (EP) communication library for distributed Mixture-of-Experts (MoE) workloads. The team announced the release as a library built to make expert-parallel communication more efficient at scale. It ships under an MIT license. MoonEP arrived as part of Kimi K3 Open Day. Alongside the K3 model weights and technical

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Prompt Engineering vs Loop Engineering vs Graph Engineering: What Changes at Each Layer

Prompt Engineering vs Loop Engineering vs Graph Engineering: What Changes at Each Layer Read More »