By 2025, Everyone Should Learn to Develop AI Agents!
An Agent is not just an upgraded version of a chatbot. It not only tells you ‘how to do it’ but also ‘helps you do it.’ By 2025, AI Agents have become the ‘digital workforce’ for enterprises, capable of understanding instructions and planning tasks like humans, utilizing tools, remembering interactions, and completing full processes from ‘analyzing competitive reports’ to ‘automatically sending emails.’
Agent = Large Model + Memory + Proactive Planning + Tool Usage
DeepSeek Brings Technical Equality, Allowing Ordinary People to Master AI
The emergence of China’s large model DeepSeek-R1 has disrupted the industry with training costs at 1/70 and pricing at 3%, making AI development accessible from ‘high threshold’ to ‘popularization.’ This means that with low-code platforms like Coze and open-source models, even beginners can quickly build agents without expensive computing power.
Coze is an Agent Development Platform Launched by ByteDance, initially referred to as Bot, but renamed to Agent after the October 2024 update. The overseas version targets international users and markets, allowing access to foreign large models like GPT-4o, GPT-4-Turbo, and Gemini, while the domestic version can only access domestic large models such as 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 DeepSeek-R1 and DeepSeek-V3.
Coze is a very user-friendly, highly extensible, and vibrant Agent development platform, making it ideal for individuals with no programming background.“Zero-Basis Development of AI Agents – A Step-by-Step Guide to Creating Agents with Coze” uses the domestic version of Coze as the platform for Agent development, comprehensively introducing tips for using Coze’s various functions and case studies for 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, which typically involves three stages and ten steps to develop an Agent capable of production-level applications and commercialization.
(1) Planning Stage for the Agent.This stage includes defining the application scenarios for the Agent, sorting out business processes and pain points, and outlining the functional positioning and development requirements for the Agent.
(2) Design Stage for the Agent.This includes drawing the operational flowchart of the Agent, setting the large model and parameters, designing prompts, configuring Agent skills, and designing user communication interfaces with five steps.
(3) Launch Stage for the Agent.This includes testing and tuning, and publishing two steps.
Strategies for Developing Agents
By following the above development process, we can complete the development of the Agent step by step. However, merely mastering these steps is not enough. To develop an excellent Agent, one must adhere to good development philosophies and follow implementation principles. These philosophies and principles will guide us to fully leverage the Agent’s capabilities while understanding its current limitations.
Understanding Scenarios and Business is More Important than Understanding AI Technology
Developers need to realize that during the development of an Agent, understanding scenarios and business is far more important than understanding AI technology. AI technology can only truly function when closely integrated with business.
Currently, AI applications are still in their early stages. Most people view themselves merely as users of Agents, not participants, and certainly not developers. However, it is difficult for programmers alone to drive the comprehensive prosperity and in-depth development of Agents. The diagram below illustrates the three levels of AI technology application. The first level is Work + AI, where we utilize large models to enhance work efficiency and respond to life queries. 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 with business, transitioning our work from digitization 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 think like business experts and enhance their understanding of business and design capabilities, planning and designing Agents from the perspective of application scenarios and business analysis, thereby improving 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 powerful, one can look at its configuration in these four areas.
For example, a conversational role Agent without a knowledge base, plugins, workflows, databases, or memory, designed only with prompts, will not differ significantly from a ChatBot. Early Agent development platforms provided simple Agents that were essentially personalized ChatBots or only reached the level of Copilot, which strictly speaking cannot be considered true Agents.
Adhere to Small and Beautiful, Focusing on Specific Application Scenarios and Functions
Agents are lightweight applications targeting specific application scenarios and can be combined with RPA. Agents can interface with daily software through APIs or collaborate with other Agents. Therefore, Agent developers should adhere to the philosophy of small and beautiful, starting from the smallest granularity of application scenarios and functions to define the Agent’s application scenario and design it. The more specific the application scenario, the more focused the users are, the clearer the implementation path of the Agent becomes, leading to stronger feasibility and greater value. Conversely, if we approach it with software development thinking, delineating complex and broad application scenarios and functions, it may lead to technical infeasibility for the Agent or poor stability.
Consider the Agent as an Assistant, Not a Fully Managed Solution
Whether it is AI technology or the development of Agents, both are in an exploratory stage. We are still a distance away from AGI. Currently, Agents are transitioning from being ‘fun’ to ‘useful.’ Agents need improvements in terms of intelligence, automation, multifunctionality, and performance stability. Therefore, as Agent developers, we must clearly recognize this and be cautious of overly idealistic notions about Agents, as they may bring difficulties and risks to the development or promotion of Agents.
Additionally, as AI tools, the original intention of Agents is to assist humans in improving efficiency, not to replace human decision-making. Therefore, when using Agents, we should view them as assistants, not as 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 Agents: A Step-by-Step Guide to Creating Agents with Coze” is divided into three parts: Introduction, Tools, and Practice.
Introduction: Introduces the concept of Agents, their development, the differences between Agents, Prompts, and Copilots, the value of Agents to individuals and enterprises, and the basic knowledge required to develop Agents.
Tools: Provides a detailed introduction to the evolution of Agent development platforms, reviews mainstream domestic Agent development platforms, highlights the operational key points of the Coze platform, and proposes a general process for Agent development.
Practice: Focuses on five typical Agent usage scenarios, detailing the development processes of 11 Agents.
Now, you can follow this book and use the visual design and arrangement tools provided by Coze to quickly build various AI projects, agents, and applications based on large models with zero-code or low-code approaches!
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 today who do not know how to use smartphones. 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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Published by: Yang Zhongxing
Reviewed by: Chen Xinyi, Ji Lin
