Maestro is an advanced system designed to optimize task execution and improve the performance of language models by allowing users to explicitly define requirements separate from instructions. This approach provides enhanced control and visibility over the output generation process, as Maestro validates outputs against set requirements, offering feedback and iterative improvements. With its dynamic planning capabilities, Maestro efficiently utilizes computational resources to plan and execute tasks, employing techniques like Best-of-N and Generate and Fix to refine results. Evaluations demonstrate Maestro's effectiveness in surpassing traditional methods and achieving high-quality outcomes across various benchmarks, including complex RAG systems and requirement-following datasets, where it significantly improves requirement satisfaction and accuracy rates. By focusing on planning and validation, Maestro empowers developers to achieve better results with less effort in prompt engineering and workflow design, offering a promising tool for enhancing the capabilities of existing language models.