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.
Denodo: autonomous AI systems depend on the quality of enterprise data governance
As AI becomes more autonomous, the weak point is not only the models but also the data: without a unified governance layer, systems are more
Huntley's take on Ralph loop: why Anthropic and Vercel approaches shouldn't be conflated
The term Ralph loop is already being used to lump together at least five agent architectures, and the analysis shows where the line between
Manus and AI agents are changing development: MVP code now appears in 20 minutes
Habr AI showed that reinforcement learning still trails classical optimization in logistics
KOMPAS-3D gets an AI agent that builds parts, drawings, and exports DXF on its own
Habr: according to Yandex Wordstat data, demand for "AI agents" trails bots and services
OpenClaw in China: why the buzz around the AI agent became a global market test
China has turned OpenClaw from a tool for enthusiasts into a mass experiment with AI agents: businesses are accelerating adoption, while reg
H Company introduces Holo3 — an AI agent for computer use with a record score on OSWorld-Verified
H Company has released Holo3, a model for computer use that scored 78.85% on OSWorld-Verified and was trained on synthetic enterprise scenar