Building successful AI agents involves significant iteration and a focus on quality, governance, and security from the outset. The article emphasizes the importance of integrating these elements into the development process to ensure effective deployment of AI agents. It highlights the need for the right tools and workflows, which are essential for navigating the complexities of creating agentic applications. Key insights include the definition of agentic applications and the necessity of observability for monitoring their performance. The article outlines a modern workflow for developing these applications and shares examples from companies excelling in this space. For instance, Square is enhancing its Square Assistant with new language models to improve conversational AI for businesses. Canva is utilizing Weights & Biases to streamline its MLOps processes, allowing its machine learning team to better support over 150 million active users. Leonardo.ai is scaling its Generative AI platform through AWS and Weights & Biases, which helps creators generate high-quality art assets across various industries. The whitepaper serves as a practical guide for teams, whether they are new to AI agents or looking to refine their existing strategies. By providing actionable insights, it aims to equip organizations to thrive in a rapidly evolving AI landscape.