How can agents improve their competency over time?

Agents can improve their competency over time through techniques like reinforcement learning, active learning, and feedback loops from user interactions. By leveraging user feedback, agents can adapt their responses and strategies to better meet user needs. Additionally, continuous training on updated datasets and incorporating new tool capabilities help agents stay current and effective in varied contexts. The use of meta-learning frameworks can also allow agents to quickly learn how to tackle new tasks based on previously acquired knowledge.