Time-series forecasting is undergoing a fundamental shift as traditional statistical models struggle to incorporate dynamic real-world context and counterfactual logic. This workshop explores the frontier of "Agentic Forecasting," focusing on how multi-agent architectures can augment numerical predictions with qualitative reasoning and dynamic scenario planning. We will deeply examine the systems engineering required to create continuous loops of analyzing multimodal data, simulating outcomes and calibrating predictions in real-time, with a major emphasis on designing robust "What-If" agents capable of parsing complex business interventions to output verifiable and narrative-driven forecasts. Translating these advanced predictive models from architectural research into real-world impact requires orchestrating complex and domain-specific ecosystems. To demonstrate this at scale, the workshop will also highlight how multi-agent frameworks are automating specialized workflows beyond predictive analytics—ranging from autonomous scientific discovery and end-to-end publication pipelines to creative cinematic video orchestration. Finally, to ensure the reliability of these autonomous systems in high-stakes production environments, we will address the practical bottlenecks of deployment through the lens of advanced agent security, automated red-teaming and formal verification, ultimately providing attendees with actionable blueprints for building robust, secure, and highly capable agentic ecosystems.