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Welcome back to Part 2 of our Intelligent ATS project using CrewAI! Now that we have explored the entire codebase and architecture in the previous video, it is time to put everything into action. In this session, we move from the static code to a live, breathing application. This is where you see the real power of multi-agent orchestration as we trigger the system to process data, analyze resumes, and deliver results in real-time. In this walkthrough, we focus entirely on the implementation and execution phase. I will show you how to properly initialize the environment, kick off the CrewAI tasks, and monitor the agents as they collaborate to evaluate candidates. Watching the system run live allows us to observe how the agents handle different resume formats and how the scoring logic applies to various job descriptions. We will also look at the terminal logs to understand the "thought process" of our AI agents, providing a rare behind-the-scenes look at how Agentic AI makes decisions. GitHub: https://github.com/nithishkumar86/Application_tracking_system.git