In the evolving landscape of software development, AI systems are increasingly playing a pivotal role in automation and task management, as demonstrated by the rise of remote agentic environments. These environments employ AI agents to autonomously manage complex, multistep tasks within cloud-based development settings, enabling developers to focus on strategic oversight rather than implementation details. This shift is facilitated by advanced tools that allow these agents to understand natural language instructions, maintain context, and interact with codebases to plan and execute tasks such as migrations and integrations. While offering scalability, standardized tooling, and enhanced security, these systems also present challenges such as the need for human oversight to ensure code quality and address security risks. Additionally, organizational adaptation is crucial to support developers in their transition to roles as AI orchestrators. To aid this transition, runbooks serve as essential guides, capturing and refining knowledge and execution patterns, thereby enhancing collaboration and accountability in AI-driven workflows.