How Generative AI is Transforming Legal Practice Through Smarter Prompts

The legal profession stands at a technological crossroads, with generative AI rapidly transforming how lawyers work. When Microsoft lawyers began using AI tools, they became 32% faster and 20% more accurate – a stunning efficiency boost that's now within reach for legal professionals everywhere.

TLDR:

• Prompt engineering is the art of crafting instructions to get specific desired results from AI
• Four key questions for effective prompts: what do you want AI to do, why and who's involved, how should AI respond, what reference material should it use
• Legal applications include drafting, research, analysis, summarization, negotiation support, and client communications
• The lawyer always remains responsible for the final work product – AI is a co-pilot, not autopilot
• Ethical considerations include professionalism, proper disclosure, confidentiality, and data security
• Best practices include using trusted source materials, verifying results, and experimenting to improve prompts
• Microsoft and Singapore Academy of Law's guide provides practical examples for contract review, disputes, compliance, and client communications.

Prompt engineering – the skill of crafting effective instructions for AI systems – has emerged as the key to unlocking these capabilities. Drawing from Microsoft and the Singapore Academy of Law's comprehensive guide, we explore how lawyers can master this art through a structured approach. The framework revolves around four essential questions: defining your goal with clear action verbs, providing rich context about purpose and stakeholders, specifying expected output formats, and directing the AI to appropriate reference materials. This methodology transforms vague requests into powerful, targeted prompts that deliver precisely what a lawyer needs.

The practical applications span virtually every aspect of legal work. From generating contract drafts and identifying risks to summarizing cases and preparing for negotiations, AI assists with routine tasks while freeing lawyers to focus on strategy and client relationships. Integration with familiar tools like Word, Teams, and Outlook makes these capabilities seamlessly accessible within existing workflows. Yet with this power comes significant responsibility – the lawyer always remains accountable for the final work product, with ethical considerations around disclosure, confidentiality, and appropriate use cases requiring careful navigation.

As AI continues reshaping legal practice, prompt engineering is quickly becoming as fundamental as legal research or writing skills. Try experimenting with these techniques in your own work – the efficiency gains might surprise you. How will you incorporate AI as your legal co-pilot?

Chapters

• 0:00 AI Transforming Legal Work
• 2:24 Four Key Prompt Engineering Questions
• 6:42 Practical Applications for Lawyers
• 8:56 Ethical Considerations and Best Practices
• 12:51 Real-World Examples and Takeaways

Transcript

Speaker 1: 0:00

Okay, let's unpack this. So imagine this Microsoft lawyers suddenly getting what? 32% faster.

Speaker 2: 0:06

And 20% more accurate.

Speaker 1: 0:08

That's just well. It's not sci-fi anymore, is it? It happened when they started using generative AI. Pretty mind-blowing.

Speaker 2: 0:14

It really is.

Speaker 1: 0:15

Welcome to the Deep Dive. We try to make complex stuff clear and today we're diving straight into how generative AI is well reshaping the whole legal field. Deep Dive straight into how generative AI is well reshaping the whole legal field.

Speaker 2: 0:24

Good thing.

Speaker 1: 0:25

And our main focus getting good at it, mastering it through what they call prompt engineering.

Speaker 2: 0:31

Yeah, and what's really striking is how fast this is all moving. You know, ai and law isn't brand new. We've had data analytics, discovery automation for a while.

Speaker 1: 0:40

Right Due diligence contract management.

Speaker 2: 0:42

Exactly, but this generative AI wave. It feels like a completely different level, a real chance for proper innovation in how lawyers actually work day to day.

Speaker 1: 0:52

Absolutely, and the source we're digging into today is this guide promptsforlawyerspdf. It's from Microsoft and the Singapore Academy of Law.

Speaker 2: 1:00

A pretty solid combination.

Speaker 1: 1:01

Yeah, and it's designed to give legal pros like you listening practical ways to get you know real results from these AI tools.

Speaker 2: 1:10

That's not just theory.

Speaker 1: 1:12

No, think of this deep dive as your shortcut, your way to understand how AI can be this super efficient legal co-pilot. We're pulling out the key bits on prompt engineering.

Speaker 2: 1:22

The essential takeaway.

Speaker 1: 1:23

Exactly so you save time, boost your understanding, but without getting totally buried in detail. Our mission just give you the know-how to use generative AI well in your practice.

Speaker 2: 1:34

And it's useful, like I said, to remember the background. Ai started with processing massive data sets, automating really specific, sometimes quite tedious tasks. Right Generative AI though it's an evolution, it can take on more routine work, freeing you up for the stuff that really needs your brainpower strategy, client relationships.

Speaker 1: 1:52

The higher value stuff.

Speaker 2: 1:53

That's it.

Speaker 1: 1:54

And look, this isn't some distant future thing, it's happening right now Legal research tools, contract drafting software they're building this stuff in.

Speaker 2: 2:00

You see it everywhere. Even the Singapore courts are testing it out for people representing themselves in small claims. That's fascinating, and the Singapore Academy of Law is boosting its own research databases with it too.

Speaker 1: 2:13

So it's not just specialized legal AI tools anymore. Right Even general tools are becoming powerful legal assistants.

Speaker 2: 2:20

Which makes understanding how to talk to these models, how to instruct them, absolutely critical. The guide really hammers this home. The AI's power is tied directly to the quality of your prompts.

Speaker 1: 2:34

Okay, so let's get right into it then. What exactly is prompt engineering?

Speaker 2: 2:37

Well, basically, it's the skill, or maybe the practice of crafting instructions, the prompts to get specific desired results from the AI.

Speaker 1: 2:45

Like learning its language.

Speaker 2: 2:47

Sort of yeah, think of it as learning how to communicate really clearly with an incredibly smart but sometimes very literal digital helper.

Speaker 1: 2:54

The guide calls it more of an art than a science, which I thought was interesting. It suggests it's not just a formula.

Speaker 2: 2:59

Exactly. It implies intuition, experience, learning how the models react, figuring out what works to really unlock what they can do for you.

Speaker 1: 3:07

Okay. So how do we get good at this art? How do we go from just asking a basic question to properly engineering a strong prompt? The guide breaks it down using four key questions to ask yourself. First one what do you actually want the AI to do? What's the goal?

Speaker 2: 3:23

Seems obvious, but clarity here is absolutely number one. The guide says start prompts with clear action verbs. You know?

Speaker 1: 3:30

draft summarize analyze Tells it exactly what job to do.

Speaker 2: 3:34

Right, and if the goal's complicated, break it down. Smaller steps are usually better than one giant. Ask like giving detailed directions instead of just a vague address.

Speaker 1: 3:43

Makes sense. Don't ask for the entire case strategy at once. Maybe start with analyzing the key emails first.

Speaker 2: 3:49

Precisely.

Speaker 1: 3:49

Okay. Second question why do you need this output and who's involved? This sounds like it's all about context.

Speaker 2: 3:54

It is. The more relevant background info you give it constraints, who the parties are, that sort of thing the better the AI gets it Right. The guide also mentions specifying the persona, basically who's asking, who's the output for? Is it for you, another lawyer, the client? That helps it adjust the language, the tone.

Speaker 1: 4:12

Ah, okay, and they mentioned something called few-shot learning. What's that about?

Speaker 2: 4:17

Think of it like giving the AI a couple of examples first, like if you wanted to draft a specific type of contract clause, you could paste in one or two good examples right into the prompt.

Speaker 1: 4:26

So it sees the style you want, not just the topic.

Speaker 2: 4:29

Exactly Style, format, level of detail, and the guide lists key legal context points too. The legal issue itself, the jurisdiction, super important applicable laws, case details, stakeholders all that stuff helps focus the AI.

Speaker 1: 4:45

Got it. So context acts like guardrails keeping the AI on the right track. Third question how should the AI respond, setting expectations for the output.

Speaker 2: 4:53

Precisely, this is where you define the voice, the format. Do you need a deep dive report or just quick bullet points?

Speaker 1: 4:58

Formal legalese or plain English.

Speaker 2: 5:01

Right Table memo summary. What's the actual purpose? Is it an internal note or is something going to a client and, crucially, for law? You can often specify the jurisdiction to focus on, say, singapore law.

Speaker 1: 5:13

That level of control sounds really useful. The guide also mentions chain of thought prompting what's that Sounds like? Asking it to show its work.

Speaker 2: 5:22

That's a pretty good way to put it. Yeah, yeah For complex stuff. If you add something like think through this step by step to your prompt, it encourages the AI to explain its reasoning process. This can lead to better answers, often more accurate ones. Plus you can follow its logic see if it lead to better answers, often more accurate ones. Plus you can follow its logic see if it missed something.

Speaker 1: 5:39

Okay, that makes sense. They have this great example prompt in the guide. Let me see Generate three to five bullet points on the key issues. Prepare me for a meeting with client X. Discuss case strategy against Y. Focus on emails and outlook and Teams chats since June Be concise, simple language, active voice, get up to speed quickly, see it perfectly weaves together the goal, the context, the audience, the format, the sources.

Speaker 2: 6:03

Very specific.

Speaker 1: 6:04

Really shows how targeted you can be Okay. Fourth and final question what reference material should it use, Bringing in specific sources?

Speaker 2: 6:11

Yeah, this is a big one. The guide strongly recommends feeding it specific references, especially with general AI models. Could be internal documents, old case files, specific websites, legal databases, things you trust Exactly and precision is key here. Don't just throw a whole 50-page document at it. Point it to the specific clauses, the relevant paragraphs, makes sense. Many tools let you upload docs or give URLs now too.

Speaker 1: 6:36

So you're narrowing its focus beyond just its general training data, like giving it the exact reading material it needs.

Speaker 2: 6:43

Spot on. And if you are asking it to look at multiple documents, the guide suggests telling it to cite its sources in the output.

Speaker 1: 6:50

Ah, smart, so you can check where it got something from Crucial for verification.

Speaker 2: 6:54

Absolutely. It keeps things transparent, lets you trace it back. But and this is a huge but you absolutely must follow your organization's data privacy and security rules.

Speaker 1: 7:03

Right, super important point.

Speaker 2: 7:04

Be so careful about what information you're putting into these models. Make sure you're using approved, secure platforms, especially with client data.

Speaker 1: 7:13

Cannot stress that enough. Okay, so we have the framework Goal context expectations source. Now how are lawyers actually using this? The guide lists a ton of practical applications.

Speaker 2: 7:23

It really covers the waterfront. Legal drafting is a big one Getting first drafts of contracts, advice, even pleadings.

Speaker 1: 7:30

That alone could save so much time.

Speaker 2: 7:32

Huge time saver. Then there's legal research finding cases, summarizing complex legal points, spotting trends.

Speaker 1: 7:39

And analysis, right Checking, contracts for risks, compliance issues, document intelligence for due diligence another area where efficiency gains could be massive.

Speaker 2: 7:47

Definitely Summarization too, Just getting quick synopses of long documents or transcripts. That's incredibly useful day to day.

Speaker 1: 7:55

Negotiation support. That sounds interesting. Generating standard replies, getting intel.

Speaker 2: 7:59

Yeah, maybe suggesting counter arguments or analyzing the other site's position based on available info. Knowledge management is another finding info buried in your firm's databases much faster.

Speaker 1: 8:09

Even client communications drafting emails.

Speaker 2: 8:12

Yeah, helping get the tone right. Ensuring key points are covered and meetings scheduling. Translation transcription summarizing who said what. Pulling out action items.

Speaker 1: 8:22

Wow, okay, practice management too. Insights on performance finances.

Speaker 2: 8:28

Potentially, yeah, analyzing data to spot trends and even automating time entries, maybe drafting initial work descriptions based on your activity.

Speaker 1: 8:37

They even mention marketing, creating content. It really seems like it touches almost every part of legal work.

Speaker 2: 8:42

It does. The potential is broad and for you listening, remember this all comes back to efficiency and getting the knowledge you need faster. These use cases are where prompt engineering makes that happen.

Speaker 1: 8:53

But with all this power comes responsibility right. The ethical side, the good practices the guide focuses heavily on this too.

Speaker 2: 9:01

As it should. The absolute number one principle, they stress, is professionalism. You, the lawyer, are always responsible for the final work product, even if AI helped draft it.

Speaker 1: 9:12

That old saying don't rely on an authority you haven't read still applies.

Speaker 2: 9:16

Absolutely. You have to review, verify and stand by the output. It's your judgment, your license on the line.

Speaker 1: 9:23

Which leads to the co-pilot, not autopilot, idea they keep mentioning.

Speaker 2: 9:26

Exactly AI assists, it suggests it can make you more fluent, but it doesn't replace your legal expertise, your advocacy skills, your core understanding. It's a tool, not a substitute.

Speaker 1: 9:39

Another key point disclosure. Do you need to tell clients or the court you used AI?

Speaker 2: 9:45

Well, that depends. You need to check your firm's policy, your local bar rules, professional conduct guidelines. Sometimes disclosure might be required, sometimes not, but you need to know the rules.

Speaker 1: 9:56

And confidentiality. We touched on this with Veda Security, but it's critical.

Speaker 2: 9:59

Paramount. You have to understand the AI services terms For your prompts confidential. Could client data leak out? The guide warns strongly against free public tools for sensitive work because your data might be used by them.

Speaker 1: 10:10

Stick to enterprise solutions with proper safeguards.

Speaker 2: 10:13

Ideally, yes, and always try to anonymize prompts if you can remove specific names identifying details, especially when dealing with sensitive client matters.

Speaker 1: 10:21

The guide has a handy DO and don't list to what are the key DOs.

Speaker 2: 10:26

DO use it for comparing documents, summarizing info, identifying key issues, brainstorming ideas, but always start with trusted source materials. If possible, do start a new chat for each distinct task to keep the context clean. Do submit related prompts sequentially, building on the previous ones. Do verify the results meticulously and DO experiment, iterate, tweak your prompts.

Speaker 1: 10:49

Get better through practice.

Speaker 2: 10:51

Don't ask too many things at once in a single prompt to keep it focused. Don't expect perfection on the first try. Refinement is usually needed Right. Don't just assume the output is accurate or fit for purpose without checking and the big one don't ever use the AI output as your final work product without thorough human review and validation.

Speaker 1: 11:09

Really practical stuff. To make it even more real, the guide gives specific, prompt examples, like for contract review.

Speaker 2: 11:15

Yeah, analyzing ESOP benefits, reviewing IP indemnity clauses, checking representations and warranties, even creating a playbic for standard contracts.

Speaker 1: 11:24

And for disputes.

Speaker 2: 11:25

Finding inconsistencies between affidavits and pleadings or between affidavits and trial testimony Really useful for prepping cross-examination.

Speaker 1: 11:33

Regulatory compliance examples too.

Speaker 2: 11:35

Yep finding rules for serving documents checking data collection against privacy laws like Singapore's PDPA. Outlining employer duties during layoffs.

Speaker 1: 11:44

Practical everyday legal questions, even client comms and billing examples.

Speaker 2: 11:49

Right. Summarizing meeting notes and drafting follow-up emails. Composing work descriptions for invoices.

Speaker 1: 11:54

And I thought the Coopilot prompt example section was great, showing how this works inside Microsoft tools we already use.

Speaker 2: 12:01

Like Word, Teams, PowerPoint, Outlook, Edge.

Speaker 1: 12:05

Yeah, analyzing a contract stored in OneDrive right within Word, getting a summary of a Teams meeting you couldn't attend.

Speaker 2: 12:11

Drafting emails in Outlook with AI. Help creating a PowerPoint deck from a document.

Speaker 1: 12:16

Summarizing long web pages in Edge. Comparing legal descriptions, it makes it feel much more integrated, you know.

Speaker 2: 12:21

Definitely. It shows how it can become part of your actual workflow, not just a separate tool you have to go to and finally, they include a glossary just defining key terms like AI, context, generative AI, prompt, model, output. Helps everyone get on the same page with the language, makes it less intimidating, maybe.

Speaker 1: 12:38

Yeah, I think so. So, wrapping up this deep dive on prompts for lawyers, the big takeaway seems clear Learning prompt engineering isn't just nice to have anymore. It's becoming pretty fundamental for lawyers wanting to really use generative AI effectively.

Speaker 2: 12:54

The payoff is potentially huge right Big jumps in efficiency, maybe better accuracy on some tasks and, crucially, more time for lawyers to focus on that high-level strategic work and client advice.

Speaker 1: 13:06

But it has to be done thoughtfully, responsibly, ethically. That came through loud and clear.

Speaker 2: 13:11

Absolutely. It's a powerful tool and, like any powerful tool, it needs to be used correctly.

Speaker 1: 13:15

So here's something to maybe mull over. We see how fast this AI is moving, how it's weaving itself into legal work. How is this skill crafting really good prompts going to become just a core, essential competency for every lawyer, maybe just like legal researcher? Writing is now.

Speaker 2: 13:30

That's a great question, and what follows from that? What new ethical questions or professional development needs pop up as AI becomes well, an even smarter partner in legal practice?

Speaker 1: 13:41

It definitely makes you think about what the future lawyer's skill set needs to include.

Speaker 2: 13:46

It really does.

Speaker 1: 13:47

If this has piqued your interest, maybe try and find that promptsforlawyerspdf guide. It's packed with practical stuff. Think about how these ideas, goal, context, expectations, source could apply to your work, the things you do every day.

Speaker 2: 14:00

Yeah, connect it back to your own practice.

Speaker 1: 14:02

And think about that Microsoft statistic again 32% faster, 20% more accurate. With the right prompting skills, maybe those kinds of gains aren't so far-fetched for you either. Thanks for joining us for this STEAM dive.