Autonomous network has become an important direction for the digital transformation of global operators’ networks. Currently, Autonomous network is evolving from L3 conditional autonomous networks to L4 high autonomous networks, the most important of which is to improve the network’s analysis, decision-making and intent/experience capabilities. In the process of network operation and management, the sources of data are very complex and the amount of data is huge. Simple AI technology cannot directly process these data. The intelligent agent uses AI technology as its brain and uses technologies such as perception, knowledge base, tool chain and task planning to assist AI to complete more complex tasks. Therefore, intelligent agents are the key to the advancement of autonomous networks from L3 to L4. Specific cases and expected results include: 1.Fault Handling Agent: This agent can perceive the overall situation of the network in real time and comprehensively analyze large amounts of data to promptly detect and handle faults, greatly improving the operational efficiency of fault handling. 2.Wireless Network Optimization Agent: This agent can comprehensively perceive and analyze the actual situation and user needs, complete intelligent wireless network optimization tasks, save manpower and improve completion quality.