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.
Salesforce handed part of its AI roadmap to customers and sped up releases of Agentforce and new features
Salesforce builds AI products not on a rigid plan, but on weekly feedback from customers to ship Agentforce, voice AI, and Slack features fa
Meta confirms leak: AI agent advice exposed sensitive data to employees
At Meta, an internal AI agent suggested a fix to an engineer, after which company employees gained access for two hours to a large volume of
VS Code 1.111 launched Autopilot: AI agent writes, tests, and deploys on its own
OpenAI is devoting its core resources to building a fully autonomous AI researcher
WordPress.com lets AI agents write and publish content with human approval
Cursor, Copilot, and Claude Code are included in a roundup of 12 popular AI agents for developers
GitAgent offers a unified AI agent format for LangChain, AutoGen, and Claude Code
GitAgent proposes storing an AI agent's logic, memory, and rules in a Git repository, then exporting the same agent to LangChain, AutoGen, C
AI agents vs RAG: how ReAct works and why multi-agent systems are needed
A single LLM response is no longer enough — a chain of actions is needed. We explain what AI agents are, how they differ from RAG, how ReAct