AI-агенты
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.
How Replit Agent Solves User Loss Problem with a Single Prompt
Replit introduced automatic authentication integration for apps: the agent will create a login system in one prompt so apps no longer lose u
WorkOS Introduces auth.md — An Open Protocol for AI Agent Registration
WorkOS has released auth.md — an open standard that enables AI agents to register in applications via Markdown file without human interventi
Fintech Apps Dying Out: AI Assistants Will Replace Them Within a Decade
Investment apps will disappear within a decade, according to Atomic Invest CEO David Dindy. They will be replaced by AI assistants that mana
CopilotKit Redefines Architecture for AI Agents in 2026
Gemma 4 as an Agent: How to Teach a Model to Call Tools Independently
How Masha Leshchinskaya Saved Her Pet Project from Death: A Device Booking System for AI
Amazon Bedrock Helps Strands Create Agents for Dashboard Automation
OPLOG developed three BI-agents on Amazon Bedrock with Claude Sonnet
OPLOG developed three AI agents for automating business analytics tasks using Strands Agents SDK and Amazon Bedrock AgentCore.
Eight best authentication platforms for AI-agents and MCP in 2026
MCP reached 97 million SDK downloads per month. AI agents are massively transitioning from experiments to production environments, and choos
AWS AgentCore: A Framework for Multi-Tenant AI Agents in SaaS
Tencent Released a Local Memory System for AI Agents TencentDB
Replit Introduces AI Development Cycle: Agent Writes Code, Squidler Tests It
How a Manager Learned to Code in n8n and Claude Code — A Story of Breaking Free from Expensive Contractors
Agent Harness in LangChain: the architecture of autonomous AI assistants
Agent Harness turns AI models into autonomous workers through three key components: file systems for data access, isolated sandboxes for sec
LangChain Launches Engine — Automatic Diagnostics for Agent Errors
LangSmith Engine automatically monitors production agents, groups errors into named issues, and suggests targeted fixes instead of manual lo