Large Language Models (LLMs) are evolving from passive text generators into autonomous agents capable of planning, executing tasks, and collaborating with other agents. In this session, Vahagn and Aram will demonstrate this evolution step-by-step: from structured tool calling and the Model Context Protocol (MCP), to autonomous agents that coordinate and collaborate to complete complex workflows. Through live demos, they will build a recruiting agent that can discover candidates, make decisions, and autonomously apply to job portals via a browser, demonstrating how modern AI agents execute tasks, use tools, and collaborate to complete end-to-end objectives.