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.
Yandex Cloud explained how to deploy AI agents in information security without false blocks or disruptions
Yandex Cloud showed why AI agents in a SOC should start in the assistant role: without guardrails and HITL, even useful automation can halt a domain and business…
Why memory has become a key element of AI agents: a breakdown across three levels of complexity
A new breakdown of memory in AI agents shows the main point: without preserving context, a model responds in isolation, while useful agent systems are built on…
Meta introduced Autodata — an agentic system for creating high-quality training data
Meta introduced Autodata — a framework in which LLM agents collect, verify, and improve training data themselves so that more capable models learn from more complex…
OpenAI releases GPT-5.4: betting on computer agents, not just code
AI startups in 2026 shift from a single prompt to multi-agent pipelines
Elon Musk revealed how the Macrohard project will unite xAI and Tesla to create software
Perplexity unveiled Personal Computer — an AI agent for Mac mini and teams
Habr AI showed how to prepare structured input for an AI agent instead of a raw technical spec
Habr AI explained why it is better to give agents not an entire document but atomic requirements with JSON attributes: this makes it easier to spot vagueness, scope…
Meta and OpenAI overpay for Moltbook and OpenClaw amid the agentic AI wave
ZDNet argues that Meta's Moltbook deal and OpenAI's hiring of OpenClaw's creator are a bet on hype: the products generate buzz, but are immature, insecure and no…
AI agents learned to steal passwords and bypass defenses, lab tests show
Zendesk acquires Forethought to strengthen AI agents for customer service
Claude Code and Codex compared on a real-world task: Claude is stronger in RAG, Codex saves tokens
Veai 5.6 for JetBrains IDEs adds commit message generation and manual Skills launch
Claude Cowork and Chrome: 10 use cases for delegating repetitive browser work to an AI agent
Habr has published a practical breakdown of how Claude Cowork, paired with a Chrome extension, handles data lookup, form filling, price monitoring, QA, and other…
Anthropic explained how businesses can implement agentic systems without unnecessary complexity
Anthropic showed that businesses are better off starting not with autonomous agentic systems, but with simple scenarios: they are cheaper, more reliable, and often…