Agentic workflows are networks of autonomous GenAI agents that perform complex tasks with minimal human intervention, making decisions and taking actions on a user's behalf. Building an agentic workflow is essentially taking a componentized, modular approach to GenAI agents, bringing benefits such as greater accuracy, better performance, and improved reusability. Agentic workflows can be built easily using tools like Langflow, which enables visually composing, testing, and deploying complex GenAI apps from pre-built components, cutting development time down from weeks to days. These workflows can harness the power of large language Models (LLMs) themselves to assist in breaking down work, parceling out subtasks to agents that specialize in answering certain queries. Agentic AI is seen as a self-driving car for AI agents - an intelligent and flexible AI that can adapt its approach to different user queries and changing circumstances.