Agents

5 milestones in AI history

ProductThe Agentic Era

The Rise of AI Agents

By 2025, frontier models were being wrapped in systems that could browse the web, call tools, edit files, execute code, manage state, and carry multi-step tasks forward with limited supervision. Claude Code, OpenAI's Operator, Google's Project Mariner, OpenClaw, and a wave of agent frameworks turned 'AI agent' from a research label into a practical product category.

AnthropicOpenAI
Google Gemini logo
ProductThe Agentic Era

Gemini 2.0: Google's Agent Platform

Google launched Gemini 2.0, designed from the ground up for the agentic era — with native tool use, code execution, and multi-step reasoning. Deeply integrated into Google's ecosystem (Search, Workspace, Android), it brought AI agent capabilities to billions of users.

Google DeepMind
GitHub Copilot logo representing the AI coding agents era
ProductThe Agentic Era

AI Coding Agents Transform Software Development

AI coding agents like Claude Code, Cursor, GitHub Copilot's agentic workflows, and OpenClaw-linked remote coding loops pushed beyond autocomplete into delegated engineering work. These systems could inspect repositories, run tests, edit files, use terminals and browsers, and iterate on tasks over multiple turns.

AnthropicCursor
OpenClaw GitHub organization avatar
Open SourceThe Agentic Era

OpenClaw: The Personal AI Assistant Goes Open Source

The `openclaw/openclaw` repository launched on GitHub, framing itself as 'your own personal AI assistant' that ran on users' own devices across the channels they already used, from WhatsApp and Telegram to Slack, Discord, and iMessage. Instead of keeping the assistant trapped in a single app, OpenClaw combined messaging integrations, voice, tools, browser control, local skills, and device-side control into an always-on personal agent.

Peter SteinbergerOpenClaw
CulturalThe Agentic Era

AI Agents in the Workforce: March 2026

By March 2026, AI agents were being used in day-to-day operations for coding, research, support, scheduling, and internal automation. Rather than replacing whole teams outright, the clearest pattern was AI taking over narrow but valuable chunks of knowledge work and operating as an always-available teammate inside existing tools and channels.

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