AI Agents
AI agents are LLM-powered systems that don't just answer — they plan steps, call tools and drive a task to completion: writing code, searching the web, booking, analyzing. 2026 became the year of agents, from coding agents to autonomous researchers. This page gathers all our coverage of agentic AI: launches, protocols (MCP, A2A), reliability and real-world use.
Small Language Models in Agents: Five Use Cases Reshaping AI System Architecture
Five concrete scenarios where SLMs are already replacing frontier models in agents: from task routing and local inference to drafting for GP
MCP and AI Agent Security: How the Protocol Created a New Attack Surface
Model Context Protocol standardized AI agent connections to tools — but each MCP server is now a trust point, vulnerable to tool poisoning a
Turing startup receives investment from AMD Ventures and transitions to AMD accelerators
How to build an AI harness for SaaS development: combining Orca, Pi Agent, and GitHub
A Reinforcement Learning tutorial without the math: just code for programmers
Page Agent from Alibaba Manages Web Interfaces via DOM Without Screenshots and Multimodal Models
Anthropic Launches Claude Science Beta: Multi-Agent Environment for Genomics and Proteomics
On June 30, 2026, Anthropic opened beta access to Claude Science — a multi-agent platform for reproducible pipelines in genomics, proteomics
NVIDIA Introduces ASPIRE — Self-Learning Robotics Framework Achieving 31% Zero-Shot Success on Complex Tasks
NVIDIA released ASPIRE — a robotics framework that writes and improves control programs, accumulates verified solutions in a skill library,