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.

Flant: How a Go Developer Turned Zed and Gemini into a Useful AI Agent
A Go developer from Flant described the path from slow IDE plugins to a combination of Zed, Gemini 3 Flash, and gopls-mcp, which provides an

MarkTechPost Demonstrates How to Build a Lightweight VLA Agent with Latent World Model and MPC
In a new tutorial, MarkTechPost breaks down how to build a simplified embodied agent: it operates on RGB frames, learns a latent world model

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

Habr AI: Why Agent Systems Need New Control and Safety Metrics
As organizations transition from chatbots to autonomous AI agents, they must evaluate not only response quality but also planning, tool call

Claude Code from Anthropic: How to Set Up an AI Assistant for Work Without Programming Skills
A Claude Code guide shows how to transform Anthropic's tool from a developer assistant into a system for notes, knowledge bases, research, a













