In-Depth Analysis of AI Agent Full-Stack Architecture

Hello everyone, I am Xuanjie.

First, let me interrupt with a message: the Double 12 Super Event has sold out the “3-Day AI Agent Project Practical Live Training Camp” originally priced at 199 yuan, and the reason is simple: the Double 12 event is very powerful, with a direct price drop to 19 yuan. The price has been slashed more than half, and today we are opening one more day for registration privileges, limited to 99 spots. At this rate, it is expected to be sold out soon, and once sold out, the price will immediately rise to 199 yuan!

Back to the main topic.

—1—

AI Agent Full-Stack Technology Diagram

The above image shows the technology stack of the AI Agent platform, divided into multiple modules, each with different functions and roles. Below is an interpretation of each module (analyzing from top to bottom):

First, Vertical Agents

• Includes AI agent companies focused on specific fields or tasks, such as: Perplexity AI search agents, Replit AI programming agents, Decagon agents, etc. These agents typically provide targeted solutions.

Second, Agent Hosting & Serving

• Provides platforms and APIs for hosting and running AI agents, such as: LangGraph, Letta, Amazon Bedrock Agents, etc. These services help developers deploy and manage AI models more conveniently.
• Its development direction will deploy agents as services on infrastructures and access them via REST APIs. The challenges include state management, security tool execution, etc. This level of development will make it easier to integrate AI agents into various applications, thus promoting their widespread use.

Third, Observability

• Observability tools are used to monitor and analyze the performance and behavior of AI agents, such as: LangSmith, Arize, etc. These tools ensure the reliability and efficiency of the system.

Fourth, Agent Frameworks

• Provides development frameworks for building AI agents, such as: LangGraph, AutoGen, LlamaIndex, Semantic Kernel, etc. These frameworks simplify the process of creating and training AI models.
• Agent frameworks are the foundation for building complex AI systems, each with its own characteristics in state management, context structure, cross-agent communication, etc.

Fifth, Memory

• Memory technologies are used to store and retrieve information generated by AI agents, such as: MemGPT, LangMem, mem0, etc. Similar to human memory, they help agents retain contextual information.

Sixth, Tool Libraries

• Includes commonly used development tool libraries, such as: Composio, Browserbase, etc., providing additional functional support.
• The tool definition method is based on OpenAI’s JSON schema, the tool ecosystem includes: LangChain, CrewAI, Composio, etc., tools give AI agents the ability to interact with the outside world, greatly expanding their application scope. As the ecosystem develops, AI agents will be able to handle an increasingly diverse range of tasks.
  Seventh, Sandboxes
• Safe testing environments used to simulate and test the behavior of AI agents, such as: E2B, Modal. This environment helps verify new features under safe conditions.
  Eighth, Model Serving
• Platforms used to deploy machine learning models for use, such as: VLLM, OpenAI, etc. Helps put trained models into production applications.
• Core components: LLM (large language model) key technologies: inference engines. Major providers: * Private models: OpenAI, Anthropic * Open-source models: Together.AI, Fireworks, Groq. Model serving is the brain of AI agents, determining their understanding and generation capabilities. Choosing the right model and service provider is crucial for the performance of the agent.

Ninth, Storage

• Data storage solutions for saving large amounts of data for AI systems, such as: Chroma, Pinecone, etc. Ensures efficient and secure data access.
• Main forms: vector databases. Popular choices: Chroma, Weaviate, Pinecone, Qdrant, Milvus. Special solutions: Postgres + pgvector. Storage solutions enable AI agents to have memory capabilities, allowing them to save and retrieve relevant information, achieving long-term learning and task continuity.
  Each module has its specific role in the overall system, collectively forming a complete and efficient AI agent ecosystem.

In summary, the technology of AI agents is so important, but how to systematically master it? My team and I have worked on large model projects for two years, helping over 60 companies implement nearly 100 projects. Based on our enterprise-level practical project experience, we have created a 3-Day AI Agent Project Practical Live Training Camp. As of today, 20,000 students have registered, which is incredibly popular! Originally priced at 199 yuan, during the Double 12 Super Event, to give back to our fans’ support, the price has dropped to 19 yuan, and we are opening registration privileges for one more day, limited to 99 spots. Once sold out, the price will immediately return to 199 yuan.

—2—

Why is AI Agent so important?

First, it is the trend of the times, we are experiencing a major technological transformation, unlike the rise of the internet back in the day. This is a disruptive change; falling behind means elimination, as all future applications will be rewritten by AI agents;

Second, we are currently in a dividend period, those who enter the market first will enjoy at least 4-5 years of dividends, earn high salaries, and have the initiative and choice in technology.

Third, there is a strong demand from enterprises, more and more companies have already implemented AI agent projects, providing us with abundant job opportunities and broad development space.

Fourth, major companies are strategically laying out, whether it is foreign companies like Microsoft and Google or domestic giants like Baidu, they are all strategically positioning themselves. 2025 will definitely be the year of AI agent commercialization.

My team and I have been researching large model application technologies for the past two years, and I want to say: the value of large models is immense, and the potential of AI agents is enormous! “All future applications will be rewritten by AI agents!” This is also the most heard statement this year. My team and I, especially this year, have helped over 60 companies implement nearly 100 AI agent projects. I have personally felt that more and more companies are indeed starting to implement AI agent projects.

Therefore, AI agents are important enough but also complex enough. My conclusion from practice over the past two years is that it is incredibly difficult to develop a reliable and stable AI agent application. The complexity of large model technology, the uncertainty of large model inference, performance issues with response speed, etc., have directly led many people to shy away from it or feel lost when encountering problems. It is indeed not easy for general technical personnel to master AI agents!

For this reason, I have specially created a 3-Day AI Agent Corporate Practical Training Camp: this training camp is developed by my team based on our enterprise-level practical project experience of two years.

The coursewas originally priced at 199 yuan, during the Double 12 Super Event, you can now get it for 19 yuan! At the end of this article, we will also give away 2 registration benefits! Once sold out, the price will immediately return to 199 yuan!

—3—

What will you gain from the 3-Day Live Training Camp?

In three days of live classes, you will quickly master the core technologies of AI agents and enterprise-level project practical experience.

Module One: Principles of AI Agent Technology

Completely dismantle the principles of AI agent technology, deeply grasp the three major capabilities of AI agents and their operating mechanisms.

Module Two: Practical Development of AI Agent Applications

In-depth explanation of AI agent technology selection and development practice, learn to develop the core technical capabilities of AI agents.

Module Three: Enterprise-Level Case Practice of AI Agents

Full process practice from demand analysis, architecture design, architecture technology selection, hardware resource planning, core code implementation, service governance, etc., deeply learn the key issues and solutions of enterprise-level AI agent projects.

In three days, what can you learn?

In real project practice, you will gain four hardcore abilities:

First, a comprehensive understanding of AI agent principles, architecture, and implementation methods, mastering the essence of core technologies.

Second, proficient use of Dify/Coze platforms, LangChain, AutoGen, and other development frameworks, laying a solid foundation for enterprise-level technical practice.

Third, through enterprise-level project practical exercises, you will be able to independently complete the design, development, and maintenance of AI agents, learning the ability to solve real enterprise problems.

Fourth, providing more possibilities for career development, whether it is for promotion, salary increase, or career change, enhancing core technical competitiveness.

Limited Time Offer:

Originally priced at 199 yuan, Double 12 Super Event, now registration is only 19 yuan!At the end of this article, we will also give away 2 registration benefits!This is a rare opportunity; let us embark on the journey of AI agent technology together and open a new era of technology!

—4—

Today, registering also comes with 4 exclusive benefits

Benefit One: AI Agent Training Camp Supporting Learning Materials, including: PPT materials, practical code, enterprise-level agent cases, and supplementary learning materials.

Benefit Two: AI Agent Training Camp Learning Notes, containing all the highlights of the 3-day live broadcast.

Benefit Three: 100 Real Interview Questions from Major Companies for AI Agents! Covering 100 real questions from major companies such as Baidu, Alibaba, Tencent, ByteDance, Meituan, Didi, the reference significance is significant for both job-hopping and promotion!

Benefit Four: 2024 China AI Agent Industry Research Report! AI agents are a new application form, the “APP” of the large model era, and the technical paradigm has also changed significantly. This research report explores the new generation of human-computer interaction and collaboration paradigms, covering technology, products, business, and enterprise implementation applications, and is very worth reading!

Double 12 Super Event, originally priced at 199 yuan, now 19 yuan!

After registering, add the assistant QR code below to immediately receive 4 benefits!

—5—

Add Assistant for Live Learning

After purchase, add the assistant for live learning👇

END