In 2023, AI large models have sparked an unprecedented wave of technology, injecting new momentum into many industries. However, the AI large models currently on the market are mainly basic models, which, although possessing general knowledge capabilities, lack professional understanding of the legal industry.
Many law firms and lawyers feel both eager and anxious, wanting to apply it quickly but not knowing how to start. Many lawyers report that during the use of AI, it is common to encounter issues such as irrelevant answers, inaccurate citations of laws, and contradictory logic.
The reasons are not complex. The essence of generative AI is to learn abstract data patterns through training on large-scale datasets and the relationships between relevant data and vocabulary, and to generate new data using the model. Therefore, it cannot “understand” human language like a human, nor can it comprehend the context and meaning behind legal texts and cases.
Understanding the working mechanism of generative AI and mastering the skill of writing precise prompts is evidently far from enough for legal practitioners. To lead 99% of peers, it is essential to achieve the goal of having one person lead an AI team to complete complex tasks—this is widely regarded as the norm in the legal field.
What you need is to build your own dedicated AI legal assistant, which is also referred to in the industry as “AI Agent”.
AI Agent = AI + Knowledge Base (RAG) + Workflow + Plugin Tools
On August 15 at 19:00, Chief Operating Partner of Beijing Zhide Law FirmTeacher Pan Yang will teach you step by step how to build your own “AI Agent”.
The AI large model is only responsible for input and output, while the AI Agent can achieve more complex functions. Workflow can break down complex tasks into smaller steps, reducing reliance on prompt techniques and model reasoning capabilities, allowing automation to be achieved in just a few simple steps; Knowledge Base can use RAG technology to reorganize replies using retrieved relevant content as context for model prompts.
In simple terms, the combination of the two can allow AI to accurately understand legal language like legal professionals, thus outputting content more suited to legal scenarios, helping legal professionals transform their expertise into legal services, easily achieving automation and scenario-based case handling, resulting in cost reduction, efficiency improvement, business innovation, and enhanced work experience.
Scan to Listen for Free
Listen to Get“60 AI Use Cases for Improving Case Efficiency (Prompt Words)”
✦ +
+
How Do Lawyers BuildTheir Own AI Assistant?
The integration of law and AI is not merely a simple tool application, but a revolution in thinking. It requires us to redefine the role of lawyers and rethink the essence of legal services.
When lawyers handle cases, they need to consult a large number of legal texts, case law, and academic articles. At this point, the role of “RAG” gradually becomes apparent.
RAG, short for Retrieval-Augmented Generation, is a hybrid model that combines information retrieval and text generation. Its workflow can be divided into two main steps:
Step One:
Information Retrieval, which involves retrieving relevant documents and data sources to obtain information related to user queries;
Step Two:
Text Generation, which involves using generative models to process and integrate the retrieved information to generate answers that meet user needs.
Accuracy, fluency, and timeliness are the biggest features of RAG—it not only helps users efficiently obtain vast amounts of information but also quickly generates accurate and detailed answers, greatly improving the efficiency of knowledge work.
In legal scenarios, RAG can help lawyers quickly find relevant legal documents and generate concise legal opinions.
For example, when lawyers prepare defense materials, they can input case-related information into the RAG system, which will automatically retrieve relevant legal texts and case law and provide targeted defense strategies.
The key point is that the RAG system is completely personalized and customized. So the question arises, how do lawyers build their own dedicated knowledge base and carry out RAG system operations?
First, you need to make your knowledge understandable by AI. This involves building a knowledge base, collecting and organizing knowledge, and crucially—updating and maintaining knowledge.
Second, how to quickly find the needed materials in the knowledge base? This involves efficient and precise indexing optimization to truly make the knowledge base useful for oneself.
Finally, designing for expression accuracy and optimizing prompts is also essential, as this determines the final output of the AI assistant—making it more suitable for real legal scenarios.
In addition, there is also the construction of AI workflows.
How to build a dedicated AI workflow for yourself in just a few simple steps, thereby identifying and analyzing repetitive tasks for automation?
Scan to Listen for Free
Listen to Get“60 AI Use Cases for Improving Case Efficiency (Prompt Words)”
Course Outline:
1. Common Application Scenarios of AI Assistants
1. Consultation Q&A
2. Document Retrieval
3. Handling Repetitive & Process Work
2. Building Knowledge Base and RAG Operations
1. Making Your Knowledge Understandable by AI
(1) Basics of Knowledge Base Construction
(2) Knowledge Collection and Organization
(3) Knowledge Updating and Maintenance
2. Techniques for Quickly Finding Required Materials
(1) Knowledge Base Index Optimization
(2) Content Text
3. Helping AI Express More Accurately
(1) Expression Accuracy Design
(2) Optimizing AI Prompts
3. Building Workflows to Simplify Repetitive Tasks
1. Processes That Can Be Done by AI
(1) Identifying Repetitive Work
(2) Analyzing Repetitive Tasks in Daily Work
(3) Optimizing AI Processes to Improve Efficiency
2. Achieving Automation in Just a Few Steps
(1) Choosing Automation Tools
(2) Designing Steps
3. Improving AI Assistant Performance
Instructor Introduction:
Pan Yang
Chief Operating Partner of Beijing Zhide Law Firm
Former Partner and Executive CEO of a Leading Legal Technology Company
With years of entrepreneurial background in the legal industry and experience in management and operations of companies and law firms, he has participated in several digital transformation projects for various enterprises.
He has led the founding of a law firm, served as executive director, and is familiar with the operational logic of online and offline legal services.
After joining Zhide, he focuses on the management and operation of law firms and the construction of digital capabilities.
Scan to Join Group
FreeCourse
Receive Learning Materials
