To adapt the framework to handle scenarios where task requirements or available agent expertise evolve over time, a continuous learning mechanism can be integrated into the framework. This mechanism would allow agents to update their knowledge and skills based on new information and experiences, ensuring they remain relevant and effective in changing task environments. Additionally, incorporating a feedback loop that captures the performance and outcomes of agents in real-time can help identify areas for improvement and guide the generation of new agents with updated expertise. By enabling agents to adapt and evolve alongside changing task requirements, the framework can maintain its effectiveness and efficiency in dynamic scenarios.