To understand what an AI Agent is, first clarify what AI (Artificial Intelligence), AGI (Artificial General Intelligence), AIGC (AI Generated Content), NLP (Natural Language Processing), LLM (Large Language Model), Multimodal, and COT (Chain of Thought) are, and understand the essential differences between AI Agents and AI.
AI (Artificial Intelligence) aims to simulate human intelligence through computer programs and algorithms, encompassing fields such as machine learning, deep learning, and natural language processing, allowing computers to think, learn, reason, make decisions, and communicate like humans.
AI Agent is an executable computer program based on LLM (Large Language Model) that can think independently, call tools, and process tasks, possessing a complex workflow that can interact automatically without human drive. As a specific implementation of AI, it focuses more on embodiment, autonomy, and interactivity, capable of interacting and collaborating with other agents or humans. For example, GPTs can create a personal AI assistant (which is a type of agent) that can help organize emails and provide creative inspiration at any time...
AI Agent mainly relies on four core elements: Planning + Memory + Tools + Action. Among them, LLM (Large Language Model) acts as the 'brain' of the agent, breaking down problems into logically sequenced sub-problems using LLM, and then calling various tools such as LLM, RAG (Retrieval-Augmented Generation), text-to-image/video generation as needed to solve the final problem.
So, what can AI Agents do? What are the use cases? Imagine having an AI agent like a personal butler, waking you up, playing music, automatically making breakfast, planning your commuting route, writing work reports, helping you respond to various complicated emails, creating PowerPoints, conducting data analysis, product planning, automatically writing code, managing self-media, e-commerce operations... Wow, that's so convenient!
Intelligent Tutoring: A teaching-type AI agent that remembers your learning status for each knowledge point, teaches you in a targeted manner, and provides personalized practice questions to help you improve your grades quickly. Mom no longer needs to worry about my studies...
Smart Customer Service: A chatbot that rivals human agents, replacing customer service to communicate with users, smoothly interacting with customers, answering their questions, and handling e-commerce order returns and exchanges.
Autonomous Driving: AI agents replace human drivers in cars (e.g., Tesla Autopilot, Baidu's RoboTaxi), processing sensor data, planning routes, making driving decisions, and automatically avoiding pedestrians and vehicles...
Stock Trading: The agent automatically helps you select stocks based on market prices, trading volumes, and other technical indicators, reasonably planning buying and selling timing, and making trading decisions automatically, so you no longer have to watch the market every day.
Game NPC: As a non-player character (NPC), interacting with players, battling, teaming up, etc., with high adaptability and strategic capabilities to create an engaging gaming experience.
There are also intelligent applications such as smart offices, manufacturing robots, smart furniture, intelligent traffic command, and smart doctors. AI Agents will penetrate various industries, acting as super assistants in the future world, capable of genuinely changing our lives whether at home, in the office, in hospitals, shopping malls, or in traffic.
The emergence of AI Agents has a tremendous impact on the way work is conducted in the internet industry and on the entry barriers for practitioners, particularly for product managers and programmers. It is not an exaggeration to say that in the next 3-5 years, product managers who do not understand AI Agents will be the first to be eliminated, followed by programmers.
The hottest positions currently are undoubtedly AI product managers, AI development engineers, AI algorithm engineers, AI training specialists, and large model development engineers, with some positions offering salaries in the hundreds of thousands or even millions... Just thinking about it is tempting.
To learn about AI Agents, we must go through at least the following three stages, growing and progressing within the knowledge system of AI, continuously practicing to acquire the ability to build and develop AI Agents.
First Stage: Understand AI Agents, familiarize yourself with APIs and calls. Grasp the basic knowledge of AI Agents, learn various API calling methods, and be able to invoke preset functional modules to achieve business interaction and data processing, independently building simple AI Agents, such as weather inquiries...
Second Stage: Master NLP technology, learning natural language processing and text generation. Master the programming tools, basic principles, and core technologies of natural language processing (NLP), applying natural language generation techniques to enable AI Agents to automatically generate text or dialogue, and develop NLP-based applications, such as chatbots...
Third Stage: Comprehensive application of API calls, natural language processing, and optimization algorithms. Integrating technologies such as API calls, natural language processing, and optimization algorithms in agent development can create more complex AI Agent applications, such as autonomous driving systems, stock trading systems... Continuously optimizing AI Agents based on feedback and application effectiveness.
Completing the above three stages means you can build a wide variety of AI Agent applications, which is very useful both for future job transitions and for improving current work efficiency. For example, for product managers, by building AI Agents, they can conduct minimal viable product validation without a massive development investment, creating commercial products and effective validation, providing a basis for product initiation and development. For programmers, being able to construct, develop, and optimize various AI Agent applications, calling various tools including LLM, and even building complex AI Agent products significantly increases competitive strength in the job market.