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Why Read “History of Technology”? About 400 years ago, British philosopher Francis Bacon, a prophet of the scientific era, provided…
Everyone Should Learn to Develop AI Agents by 2025!
An Agent is not just an upgraded chatbot. It not only tells you “how to do” but also “helps you do it.” By 2025, AI Agents have become the “digital workforce” for businesses, capable of understanding instructions and planning tasks, invoking tools, remembering interactions, and completing full processes from “analyzing competitor reports” to “automatically sending emails.”
Agent = Large Model + Memory + Proactive Planning + Tool Usage
DeepSeek Ignites Technological Equality, Allowing Ordinary People to Master AI
The emergence of China’s large model DeepSeek-R1 has disrupted the industry with a training cost of 1/70 and a pricing of 3%, making AI development accessible to the masses. This means: no need for expensive computing power; with low-code platforms like Coze and open-source models, even beginners can quickly build their own agents.
Coze is the Agent development platform launched by ByteDance, originally referred to as a Bot, it was renamed to Agent after a revision in October 2024. The overseas version targets international users and markets, allowing access to foreign large models such as GPT-4o, GPT-4-Turbo, Gemini, while the domestic version can only access local large models like Doubao, Kimi, Baichuan 4, Tongyi Qianwen, GLM-4, etc.
As of February 6, 2025, Coze has supported the latest DeepSeek models, allowing you to experience models like DeepSeek-R1 and DeepSeek-V3.
Coze is a very user-friendly, highly extensible, and vibrant Agent development platform, making it very suitable for users with no programming background.“Zero-Basis Development of AI Agent: A Step-by-Step Guide to Creating Agents with Coze” is a book that uses Coze’s domestic version as the Agent development platform, comprehensively introducing the usage skills of Coze’s various features and cases of developing Agents based on Coze.
Designing an Agent from Scratch
The “3-10” Implementation Framework for Developing Agents
Based on practical experience in Agent development, we have summarized the “3-10” implementation framework, as shown in the figure, which typically involves 3 stages and 10 steps to develop an Agent with production-level applications and commercialization capability.
(1) Planning Stage for the Agent.This stage includes defining the application scenarios of the Agent, sorting out business processes and analyzing pain points, and clarifying the functional positioning and development requirements of the Agent in three steps.
(2) Design Stage for the Agent.Includes drawing the operational flowchart of the Agent, setting the large model and parameters, designing prompts, configuring Agent skills, and designing the user communication interface in five steps.
(3) Launch Stage for the Agent.Includes testing and tuning, and publishing in two steps.
Strategies for Developing Agents
By following the above development process, we can complete the development of an Agent step by step. However, merely mastering these steps is not enough; to develop an excellent Agent, one must adhere to good development concepts and follow implementation principles. These concepts and principles will guide us to fully leverage the Agent’s capabilities while understanding its current limitations.
Understanding the Scenario and Business is More Important than Understanding AI Technology
Developers need to realize that in the process of developing an Agent,understanding the scenario and business is far more important than understanding AI technology. AI technology can only truly play its role when closely integrated with business.
Currently, AI applications are still in their early stages. Most people view themselves as users of Agents rather than participants or developers. However, relying solely on programmers makes it difficult to promote the comprehensive prosperity and in-depth development of Agents. The following diagram illustrates the three levels of AI technology application. The first level is Work + AI, where we use large models to enhance work efficiency and answer life questions. The second level is Business + AI, where AI applications understand business and provide more professional responses based on business scenarios, becoming digital employees. The third level is Business × AI, achieving a more systematic and comprehensive integration of AI and business, transitioning our work from digitalization to intelligence.
In these three levels,understanding business and business capabilities become key factors driving the deep application of AI technology.Therefore, Agent developers must possess the mindset of business experts and improve their understanding of business and design capabilities, planning and designing Agents from the perspective of application scenarios and business analysis, thus enhancing the effectiveness of Agents in solving problems.
Using Tools to Expand Capabilities is Key to the Value of Agents
Agent = Large Model ×(Planning + Memory + Tool Usage + Action). To evaluate whether an Agent’s functionality is strong, one can examine its configuration in these four areas.
For example, if a role-playing chat Agent is not configured with a knowledge base, does not use plugins, and lacks workflows, databases, memory, etc., and only has prompts designed, then its capabilities will not differ much from a ChatBot. Early Agent development platforms provided simple Agents that were almost just personalized ChatBots or only reached the level of Copilot, which strictly speaking cannot be considered true Agents.
Adhere to Small and Beautiful, Focus on Specific Application Scenarios and Functions
Agents are lightweight applications targeted at specific application scenarios, which can be combined with RPA. Agents can connect to daily software via APIs and collaborate with other Agents. Therefore,Agent developers should adhere to the philosophy of small and beautiful, starting from the smallest granular application scenarios and functions, defining the application scenario of the Agent and designing it. The more specific the application scenario, the more focused the users are, and the clearer the path to implementing the Agent, thus increasing its feasibility and value. Conversely, if we use a software development mindset to define complex and broad application scenarios and functions, it may lead to technical challenges in implementing the Agent or poor stability.
Consider the Agent as an Assistant, Not a Fully Managed Solution
Both AI technology and the development of Agents are in an exploratory stage. We are still some distance from AGI. Currently, Agents are transitioning from being “fun” to being “useful.” Agents need improvements in intelligence, automation, multifunctionality, and performance stability. Therefore, as Agent developers, we must clearly recognize this and avoid overly idealistic views of Agents, which may bring difficulties and risks to the development or promotion of Agents.
Moreover, as AI tools, the original intention of designing Agents is to assist humans in improving efficiency, not to replace human decision-making. Therefore, when using Agents, we should view them as assistants rather than fully managed solutions.Users need to judge, filter, and process the content output by Agents, rather than blindly accept and use it.
“Zero-Basis Development of AI Agent: A Step-by-Step Guide to Creating Agents with Coze” is divided into three parts: Introduction, Tools, and Practical Application.
Introduction: Introduces the concept of Agents, their development, the differences from Prompts and Copilot, the value of Agents for individuals and enterprises, and the basic knowledge required for developing Agents.
Tools: Provides a detailed introduction to the evolution of Agent development platforms, reviews mainstream domestic Agent development platforms, highlights key operational points of the Coze platform, and presents a general process for Agent development.
Practical Application: Focuses on five typical Agent usage scenarios, detailing the development process of 11 Agents.
Now, you can follow this book and use the visual design and layout tools provided by Coze to quickly build your own various AI projects, agents, and applications with zero or low code based on large models!
AI Agents are not the future; they are the present! In the next decade, those who do not know how to use AI Agents will be like those who do not know how to use smartphones today. This book is your “first ticket” to embrace the intelligent era. Click the link below to start your journey as an AI Agent developer!
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