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AI Agent: The next technological revolution after big models?

Written by
Iris Vance
Updated on:June-22nd-2025
Recommendation

The AI ​​agent technology revolution is coming. How will it reshape the future of artificial intelligence?

Core content:
1. The core concept and five characteristics of AI agents
2. The collaborative relationship between agents and big models and their architecture
3. The closed loop of agent work and industry application cases

Yang Fangxian
Founder of 53A/Most Valuable Expert of Tencent Cloud (TVP)
After ChatGPT and other large models set off a new wave of artificial intelligence, AI Agent is becoming a new focus in the technology industry. What does this seemingly unfamiliar concept mean? How is it different from the large language models we are familiar with? This article will take you to explore the core concepts, working principles and practical application value of the agent.
The nature and characteristics of intelligent agents
AI Agent is an intelligent system that can autonomously perceive the environment, make decisions and perform actions. Compared with traditional AI, it is no longer limited to passive response, but has the ability to actively think and act.
Five core qualities of an intelligent agent
  • Autonomous decision-making: Able to complete tasks independently without human intervention
  • ‌Environmental Response‌: Real-time perception and adaptation to environmental changes
  • ‌Goal-driven‌: Proactively plan actions to achieve set goals
  • ‌Collaboration‌: Effectively interact with other agents or humans
  • ‌Continuous Evolution‌: Optimizing performance through experience accumulation
If traditional AI is a "knowledge base", then the intelligent agent is the "executor" - it can not only understand the needs, but also turn solutions into practical actions.

The collaborative relationship between the agent and the big model
To understand the relationship between the intelligent agent and the large language model, we can make an analogy:
  • Big Model: The "brain" that provides "thinking ability"
  • Intelligent body: "limbs" endowed with "ability to act"


The combination of the two creates a more powerful AI system with the following advantages:
  • Breaking through the limitations of pure text interaction
  • Get real-time updated information
  • Execute complex task processes
  • Realize scene customized services
‌Agent Architecture Formula‌ : Large Model + Memory System + Perception Reflection + Task Planning + Tool Calling

Core architecture of the agent
A complete intelligent agent system consists of four key modules:
  • Cognitive center: large language model responsible for understanding and reasoning
  • ‌Memory system‌: short-term memory maintains current context, long-term memory stores historical experience
  • ‌Planning Engine‌: Uses techniques such as thought chaining to break down complex tasks
  • ‌Execution Tools‌: Extending Capabilities through API Calls


The working loop of the intelligent agent
The operation of the intelligent agent follows the complete closed loop of "perception-thinking-decision-action-learning":
  • Environmental perception: receiving multimodal input data
  • ‌Analysis and Planning‌: Break down tasks and develop plans
  • ‌Optimal decision‌: Evaluate and choose the best path
  • ‌Action Execution‌: Calling tools to complete tasks
  • ‌Experience accumulation‌: Continuous optimization based on feedback
This iterative mechanism enables the agent to continuously improve task execution performance.

Ability classification of intelligent agents
According to the degree of intelligence, agents can be divided into:
  • Reflective: Simple response based on current input
  • ‌Model Type‌: Maintaining the environment state model
  • ‌Goal-oriented‌: Planning to achieve specific goals
  • ‌Utility‌: Optimizing decisions through value assessment
  • ‌Learning‌: Evolving autonomously from experience

Industry Applications of Intelligent Agents
Intelligent agent technology is creating value in multiple areas:
  • Customer service: 24/7 intelligent customer service, personalized recommendations
  • ‌Digital Marketing‌: Automated customer acquisition, precision email marketing
  • Talent management: intelligent resume screening, training and development
  • ‌Financial management‌: automated bookkeeping, smart auditing
  • ‌Cybersecurity‌: Real-time threat monitoring, vulnerability detection
  • ‌Medical health‌: remote monitoring, smart consultation
  • Smart logistics: route optimization, demand forecasting
For example: A domestic e-commerce platform achieved inventory optimization through intelligent entities and reduced warehousing costs by 20%.
Intelligent Agent Tools to Watch in 2025
Technology development tools


Tool Name
Differentiated value
Applicable scenarios
‌Huawei MindSpore Agent‌
End-cloud collaborative architecture, deep adaptation of domestic chips
Edge computing, Internet of Things
‌SenseAuto‌
Vision + Language Multimodal Fusion
Intelligent quality inspection, industrial inspection
‌Fourth Paradigm Prophet AutoAgent‌
Predictive maintenance algorithms lead the way
Equipment operation and maintenance, supply chain management


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