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.
Z.ai releases GLM-5V-Turbo — native multimodal model for visual programming
Chinese lab Z.ai has released GLM-5V-Turbo — a model that recognizes architectural diagrams and screenshots, then immediately generates working code for agentic…
NVIDIA at GTC 2026 Shifts Focus From Chips to Token Factories and Agent-as-a-Service
At GTC 2026, NVIDIA showcased a bet not on individual GPUs, but on token factories, the modular Vera Rubin architecture, and AI agents as a service economics.
Habr: AI agents change delivery, and teams must rebuild the entire development cycle
Habr explains why with the emergence of AI agents, teams need to restructure not only code writing but the entire delivery: context, checks, execution rules and…
Arcee AI Released Trinity Large Thinking — Open Reasoning Model for AI Agents
Agentis Memory: Redis-Compatible Storage with Vector Search and Local Embeddings
Directum: Why Business Actively Discusses AI Agents but Hesitates to Deploy Them in Processes
Agent Coding as Addiction: Why Developers Can't Stop
PromptPilot: task scheduler for Claude Code and Codex that works while you sleep
A Russian developer created a task scheduler for AI CLI — PromptPilot accepts prompts from terminal, browser, or Telegram bot and executes them on schedule with…
Vulnerability in OpenClaw allowed silent privilege escalation to admin on exposed instances
A critical bug in OpenClaw allowed privilege escalation to administrator, and on thousands of internet-accessible installations, this effectively enabled full agent…
Luminarys AI Launches AI-Agent Platform with Skill Isolation and Cluster Deployment
Z.AI showed how to build production-ready agentic systems on GLM-5 with tool calling
Habr AI: Why Agent Systems Need New Control and Safety Metrics
Claude Code from Anthropic: How to Set Up an AI Assistant for Work Without Programming Skills
Claude Code and 11 Agents: How a QA Team Automated Up to 80% of Testing Routine
A QA team built a system of 11 AI agents based on Claude Code that converts Jira tasks into test cases, automated tests, and Merge Requests in hours instead of days.
Anthropic, OpenAI and LangChain explained why AI agents need a harness
Anthropic, OpenAI and LangChain are shifting focus from the models themselves to agent harness — an orchestration, memory and tools layer that makes AI agents…