What is an LLM?

2025-06-12

If you’re practicing law today, you’ve almost certainly encountered the term “LLM” in discussions about artificial intelligence. Not the Master of Laws degree that many of us earned in law school, but Large Language Models, the technology powering the AI revolution that’s transforming legal practice. Understanding what LLMs are and how they work is becoming as essential for lawyers as understanding how legal databases function.

Think of an LLM as the most sophisticated legal research associate you can imagine, one who has read virtually every case, statute, regulation, and legal treatise ever published, and can instantly recall and synthesize that information in response to your questions. But unlike a human research associate, an LLM’s knowledge isn’t limited to law; it spans literature, science, business, and virtually every domain of human knowledge that has been written down.

The Foundation: What Makes an LLM “Large”

The “Large” in Large Language Model refers to the enormous scale of these systems, both in terms of the data they’ve learned from and the computational complexity of their design. To understand this scale, imagine trying to create the most comprehensive legal library ever assembled. You’d want every Supreme Court decision, every circuit court opinion, every state case, every federal regulation, every law review article, and every legal treatise. That’s just the legal materials. An LLM has also “read” newspapers, books, websites, academic papers, and countless other sources of human knowledge.

When we say an LLM has “read” this material, we’re using a helpful analogy. What actually happens is more like a law student spending years absorbing legal principles, gradually developing an intuitive sense for how legal language works, what arguments are persuasive, and how different areas of law connect to each other. The LLM develops statistical patterns about how words and concepts relate to each other across all this text.

Just as a experienced lawyer develops a sense for what legal arguments will be compelling based on years of practice, an LLM develops patterns for generating coherent, contextually appropriate text based on its training. The difference is that an LLM can do this across virtually any topic, not just law.

The Language Model: Understanding Through Patterns

The “Language Model” part of LLM refers to how these systems understand and generate text. Think of it like this: when you’re writing a brief, you don’t consciously think about the probability that the word “therefore” should follow “the evidence clearly shows.” You’ve internalized the patterns of legal writing through years of practice. You know that certain phrases typically follow others, that legal conclusions flow from factual premises, and that persuasive arguments have recognizable structures.

An LLM works similarly, but with mathematical precision across billions of text patterns. It has learned that in legal contexts, certain words and phrases tend to appear together, that legal reasoning follows particular structures, and that different types of legal documents have characteristic formats and language patterns.

When you ask an LLM to help draft a contract clause, it’s drawing on patterns it has learned from thousands of similar clauses. It understands that indemnification provisions typically include certain elements, that warranty sections follow particular formats, and that the language needs to be precise and unambiguous. It’s not copying existing clauses; rather, it’s generating new text based on the deep patterns it has learned about how legal language works.

The process of creating an LLM is remarkably similar to how lawyers develop expertise, just accelerated and scaled dramatically. Consider how you became proficient in your practice area. You probably started by reading cases, statutes, and secondary sources. You observed how experienced lawyers approached problems, learned from their reasoning, and gradually developed your own legal instincts.

LLM training follows a similar pattern. The model is initially exposed to vast amounts of text and learns basic patterns about how language works. This is like a law student’s first year, absorbing the fundamental structures of legal reasoning. Then, through a process that’s analogous to mentorship, the model is fine-tuned to be more helpful, accurate, and aligned with human values, much like how junior associates learn from senior partners.

The remarkable thing about this process is its breadth. While a lawyer might specialize in corporate law or litigation, an LLM develops familiarity with virtually every area of legal practice simultaneously. It learns contract drafting, statutory interpretation, case analysis, and legal research as interconnected skills rather than separate specialties.

You’ve likely heard of several LLMs that have become household names. ChatGPT, powered by models like GPT-4, was the first to capture widespread public attention. Claude, developed by Anthropic, is known for its strong reasoning capabilities and safety features. Google’s Bard (now Gemini) and other models have joined the conversation. Each has its own strengths and characteristics, much like how different legal publishers (Westlaw, Lexis, Bloomberg Law) offer similar services with different interfaces and specialties.

What’s important to understand is that these are all variations on the same fundamental technology. They’re like different law firms, each with its own culture, strengths, and approaches, but all fundamentally practicing law. The underlying principles of how they work are similar, even if their specific implementations and capabilities vary.

When you present a legal question to an LLM, it doesn’t look up the answer in a database the way Westlaw or Lexis works. Instead, it generates a response by predicting what sequence of words would be most appropriate given the context of your question and all the patterns it has learned.

This is more like how an experienced lawyer approaches a new legal problem. You don’t just look up the answer, you draw on your accumulated knowledge, consider relevant precedents, think through analogous situations, and construct a reasoned response. The LLM does something similar, but it’s drawing on patterns learned from an enormous corpus of text rather than personal experience.

For example, if you ask an LLM about the elements of a breach of contract claim, it’s not retrieving a stored definition. Instead, it’s generating text based on all the contexts in which it has encountered discussions of breach of contract, including case law, legal treatises, bar exam materials, law school outlines, and practical legal documents. The result is typically a comprehensive response that synthesizes multiple sources and perspectives.

LLMs excel at tasks that require understanding context, synthesizing information, and generating coherent text. In legal practice, this translates to powerful capabilities across multiple areas.

For legal research, an LLM can quickly understand complex legal questions and provide preliminary analysis. If you’re researching whether a particular contract provision is enforceable, an LLM can outline the relevant legal standards, identify key factors courts typically consider, and suggest lines of inquiry for deeper research. It’s like having a research associate who can instantly provide a comprehensive overview of any legal topic.

In document drafting, LLMs can generate first drafts of various legal documents based on your specifications. They understand the structure and language patterns of contracts, briefs, motions, and other legal documents. While you’ll always need to review and refine their work, they can significantly accelerate the initial drafting process.

For document review and analysis, LLMs can quickly identify key provisions, flag potential issues, and summarize complex documents. They can compare multiple versions of a contract and highlight changes, or review a brief and identify the key arguments and supporting authorities.

Understanding the Limitations

Like any powerful tool, LLMs have important limitations that legal professionals need to understand. The most significant is that LLMs can generate plausible-sounding but incorrect information, a phenomenon researchers call “hallucination.” An LLM might confidently cite a case that doesn’t exist or misstate a legal rule.

This is somewhat like having a brilliant research associate who occasionally makes confident but incorrect statements. The solution isn’t to stop using the associate, it’s to verify important information and maintain appropriate oversight. In legal practice, this means treating LLM output as a starting point for research and analysis, not as a definitive authority.

LLMs also have knowledge cutoffs. They were trained on data up to a certain point and don’t have access to information published after that date. They can’t browse the internet in real-time or access current case law databases. This is like having a research associate with an excellent but static law library.

Additionally, LLMs can struggle with highly specialized or niche areas of law where there may be limited training data. They work best in areas where there’s substantial written material for them to learn from.

How Engineers Address These Limitations

The technology industry has developed several approaches to address LLM limitations, and understanding these can help lawyers use these tools more effectively.

For the hallucination problem, engineers use techniques like “retrieval-augmented generation” (RAG), which connects LLMs to reliable databases of information. Instead of relying solely on their training data, the LLM can reference authoritative sources when generating responses. In legal contexts, this might mean connecting an LLM to current legal databases to ensure citations are accurate and current.

To address knowledge cutoffs, engineers integrate LLMs with real-time information sources and search capabilities. This allows the model to access current information while still leveraging its trained knowledge for analysis and synthesis.

For accuracy improvements, engineers use techniques like “constitutional AI” and “reinforcement learning from human feedback” to train models to be more truthful and helpful. They also implement multiple validation layers and confidence scoring to help users understand how reliable a particular response might be.

The Future of LLM Development

LLM technology continues to evolve rapidly. Current research focuses on making models more accurate, more efficient, and better at reasoning through complex problems. For legal applications, this means we can expect LLMs to become better at legal reasoning, more accurate in their citations, and more capable of handling specialized areas of law.

We’re also seeing the development of more specialized legal LLMs, models trained specifically on legal texts and fine-tuned for legal applications. These models understand legal language and reasoning patterns even more deeply than general-purpose LLMs.

Another important trend is the development of “multimodal” LLMs that can process not just text but also images, audio, and other types of data. For legal practice, this could mean LLMs that can analyze contracts in image format, transcribe and analyze depositions, or review evidence that includes multiple types of media.

It’s helpful to understand how LLMs differ from the legal technology tools lawyers have used for decades. Traditional legal databases like Westlaw and Lexis are essentially sophisticated search engines. They help you find relevant cases, statutes, and secondary sources, but they don’t analyze or synthesize that information for you.

LLMs, by contrast, can both find relevant information and provide analysis. They’re more like having a conversation with a knowledgeable colleague than conducting a database search. You can ask follow-up questions, request clarification, and engage in back-and-forth dialogue to refine your understanding.

This conversational interface is one of the most powerful aspects of LLMs for legal work. Instead of formulating precise search queries and sifting through results, you can describe your legal problem in natural language and get a comprehensive response that addresses multiple aspects of your question.

Understanding what LLMs are is the first step toward using them effectively in legal practice. The key is to think of them as sophisticated tools that augment your legal capabilities rather than replace your judgment.

LLMs are excellent at generating first drafts, providing comprehensive overviews of legal topics, and identifying relevant considerations you might not have initially thought of. They’re like having a research associate who never gets tired, can work on multiple projects simultaneously, and has an encyclopedic knowledge of legal materials.

However, they’re not substitutes for legal expertise, careful analysis, and professional judgment. The most effective approach is to use LLMs to enhance your efficiency and thoroughness while maintaining the critical thinking and verification processes that are essential to good legal practice.

Conclusion

Large Language Models represent a fundamental shift in how we can interact with legal information and analysis. They’re not just better search engines; they’re tools that can understand context, generate coherent analysis, and engage in sophisticated dialogue about complex legal issues.

For lawyers, understanding LLMs is becoming as important as understanding how to use legal databases or research legal questions. These tools are already transforming legal practice, and their capabilities will only continue to grow.

The lawyers who thrive in the coming years will be those who understand how to leverage LLMs effectively while maintaining the professional standards and critical thinking that define excellent legal practice. LLMs are powerful assistants, but they’re assistants to lawyers, not replacements for them.

As this technology continues to evolve, staying informed about its capabilities and limitations will be crucial for any lawyer who wants to provide the most effective and efficient service to their clients. The legal profession has always been about using the best available tools to serve clients well. LLMs are simply the newest and most powerful tools in that tradition.