AI Security
Security researchers demonstrate how hidden prompt injections in code repositories can hijack AI coding agents like Cline, exposing critical vulnerabilities in agentic AI systems.
Agentic AI
New research proposes proxy state-based evaluation for multi-turn tool-calling LLM agents, addressing the challenge of scalable reward verification in complex agentic workflows.
Alibaba
Alibaba unveils Qwen3.5, positioning its latest AI model for the emerging era of autonomous AI agents with enhanced reasoning and task execution capabilities.
AI Safety
New research examines how AI communities are splitting on human control approaches for autonomous agents, finding significant divergence in oversight philosophies that could shape the future of AI governance.
Agentic AI
New research framework bridges traditional ML explainability methods with emerging agentic AI systems, proposing action-based interpretability for autonomous AI agents.
AI Research
A new benchmark suite evaluates how well AI agents can perform frontier research tasks, measuring capabilities from literature review to hypothesis generation and experimental design.
Agentic AI
A technical deep-dive into constructing enterprise-ready AI agents with hybrid retrieval systems, provenance tracking for citations, self-repair mechanisms, and persistent episodic memory.
Agentic AI
A comprehensive guide to evaluating AI agents covering benchmarks, testing frameworks, and metrics for measuring autonomous system performance in real-world applications.
OpenAI
In a remarkable timing coincidence, OpenAI launched its new agentic coding model just minutes after Anthropic released its own, signaling intensifying competition in AI-powered software development.
Anthropic
Anthropic releases Claude Opus 4.6 with major improvements in coding and agentic task handling, advancing autonomous AI capabilities for complex multi-step workflows.
LLM research
New research explores how smaller language models can power AI agent systems while dramatically reducing computational costs and environmental impact without sacrificing capability.
Reinforcement Learning
LinkedIn shares practical insights from training agentic reinforcement learning systems for GPT-OSS, covering infrastructure challenges, reward modeling, and lessons learned from real-world deployment.