CRIT Framework by Geoff Woods: The AI Prompting Method That Transforms How Law Firms Use AI
Master the Context-Role-Interview-Task framework to turn AI into your strategic thought partner and gain an unfair competitive advantage
Last Updated: December 11, 2025 • 12 min read
📑 Table of Contents
The CRIT Framework—Context, Role, Interview, Task—is a structured AI prompting methodology developed by Geoff Woods, author of The AI-Driven Leader, that transforms how professionals communicate with AI tools like ChatGPT, Claude, and Google Gemini. Rather than treating AI as a simple content generator, CRIT positions AI as a strategic thought partner capable of solving complex business problems in minutes rather than weeks.
With 31% of legal professionals now using generative AI at work—up from 27% in 2023—and 85% of those users engaging daily or weekly according to the 2025 ABA Legal Industry Report, the difference between mediocre and exceptional AI results often comes down to how you craft your prompts. The CRIT framework provides a repeatable system that 99% of AI users never discover.
For law firms looking to integrate AI into their practice—whether for mastering AI prompts for legal work, streamlining client intake, or developing marketing strategies—CRIT offers a practical framework that delivers immediate results.
What Is the CRIT Framework?
CRIT is a four-step prompting methodology that stands for Context, Role, Interview, and Task. Developed by leadership expert Geoff Woods, this framework emerged from his experience helping executives at companies ranging from $10 million to $60 billion in annual revenue leverage AI for strategic decision-making.
The fundamental insight behind CRIT is that most people treat AI as a content machine—asking it to write emails, summarize documents, or generate generic responses. They provide minimal context, get mediocre outputs, and then wonder why AI seems overhyped. Woods argues the problem isn’t the tool; it’s the prompt.
💡 Key Insight from Geoff Woods
“The unfair advantage comes from how you think before you type. AI has been trained on 200 to 500 million books worth of data. You can literally describe any type of expert, and it can simulate it at your fingertips.”
When you apply CRIT correctly, AI becomes what Woods calls a “thought partner”—similar to brainstorming with a brilliant colleague in front of a whiteboard, where one idea sparks another and one plus one equals eleven. This shift from AI-as-tool to AI-as-collaborator is what separates firms achieving transformative results from those seeing incremental improvements.
Who Is Geoff Woods?
Geoff Woods is the #1 international bestselling author of The AI-Driven Leader: Harnessing AI to Make Faster, Smarter Decisions, founder of AI Leadership, and host of the AI-Driven Leader podcast. His credentials make his insights particularly relevant for professional services firms.
As former Chief Growth Officer of Jindal Steel & Power—a 100,000-person global organization—Woods’ strategic leadership helped grow their market cap from $750 million to over $12 billion in just four years. Prior to his AI-focused work, he co-founded the training and consulting company behind The ONE Thing, where he advised companies ranging from $10 million to $60 billion in annual revenue.
What makes Woods’ perspective particularly valuable is his focus on strategic rather than tactical AI use. While many experts teach AI for task automation, Woods emphasizes using AI for the high-leverage decisions that drive 80% of business results—exactly the kind of thinking that distinguishes successful law firms from those struggling with lead generation and growth.
Breaking Down CRIT: Context, Role, Interview, Task
Woods recommends keeping a sticky note on your desk with these four words: Context, Role, Interview, Task. Each element serves a specific purpose in transforming generic AI outputs into strategic insights tailored to your specific situation.
🎯 C — Context: Give AI Your World
Context is the foundation of effective AI communication. You provide detailed background information about your situation, goals, constraints, and the specific challenge you’re addressing. The more context you give, the more relevant and useful the AI’s response becomes.
Example Context for a Law Firm:
“I’m a managing partner at a 12-attorney personal injury firm in Los Angeles. We currently generate 60% of our cases from referrals and 40% from digital marketing. Our average case value is $85,000, and we’re looking to increase qualified leads by 30% over the next 12 months while maintaining our case quality standards.”
This single paragraph of context sets the table. Now the AI knows your firm size, practice area, location, current marketing mix, financial benchmarks, and specific goals. Every subsequent response will be filtered through this lens rather than being generic advice that could apply to any business.
👤 R — Role: Assign Expert Identity
This is where you tell the AI to become a specific type of expert. Because AI has been trained on an enormous corpus of data—equivalent to hundreds of millions of books—it can simulate virtually any professional perspective with remarkable accuracy.
Example Role Assignments:
- “Act as a legal marketing consultant with 20 years of experience growing personal injury practices”
- “Become a CFO evaluating our marketing ROI and cost per acquisition”
- “Function as a skeptical board member challenging our growth assumptions”
- “Serve as a GEO specialist focused on AI search visibility”
The role assignment is massively powerful because it changes how the AI approaches your problem. A marketing consultant will focus on lead generation and brand positioning. A CFO will scrutinize numbers and ROI. A skeptical board member will stress-test your assumptions. You can even create an “AI board of advisors” by running the same question through multiple expert roles.
🎤 I — Interview: Turn the Tables
This is Woods’ secret weapon—the step most people skip entirely. Instead of immediately asking for a solution, you instruct the AI to interview you first. This deepens the context and often surfaces considerations you hadn’t thought to mention.
📝 The Exact Phrase Woods Uses:
“Interview me. Ask me one question at a time, up to three questions, to gain deeper context.”
This approach transforms the interaction from one-way instruction to collaborative dialogue. The AI might ask about your current client demographics, competitive landscape, or past marketing initiatives that succeeded or failed. Each answer refines the AI’s understanding and improves its eventual recommendations.
✅ T — Task: Define the Deliverable
Finally, you clearly specify what you want the AI to produce. This should be specific, actionable, and aligned with your actual needs. Vague tasks produce vague results.
Effective Task Specifications:
- “Create a 90-day marketing plan with specific milestones and KPIs”
- “Identify the top 5 risks in our current strategy and mitigation approaches”
- “Draft a competitor analysis comparing our SEO approach to the top 3 PI firms in LA”
- “Generate 10 questions a potential client would ask when evaluating our firm”
The task component prevents the AI from wandering into tangential territory. With clear context, expert role, interview-generated depth, and specific task, you get outputs that are immediately actionable rather than generic frameworks requiring extensive adaptation.
Why CRIT Matters for Law Firms
The legal industry is experiencing a profound shift in AI adoption. According to the Thomson Reuters Generative AI in Professional Services Report 2025, the share of legal organizations actively integrating generative AI rose from 14% in 2024 to 26% in 2025. Among in-house legal departments, trust in AI as a reliable resource nearly doubled—from 21% to 40% in a single year.
For law firms, this creates both opportunity and urgency. Firms that master AI communication gain significant competitive advantages, while those using generic prompts fall further behind. The CRIT framework specifically addresses challenges unique to legal professionals.
Strategic Decision-Making Over Task Automation
Woods emphasizes that AI delivers three types of value: making people more productive, making operations more efficient, and making products and services more valuable. Most law firms focus exclusively on the first category—using AI for drafting correspondence (54% of legal professionals), summarizing documents, or basic research.
CRIT elevates AI usage to strategic decision-making. Instead of asking AI to draft an email, you might use CRIT to stress-test your firm’s marketing strategy, identify blind spots in your growth plan, or simulate how potential clients evaluate competing firms. These applications address the 80% of results that come from strategic decisions rather than operational tasks.
Time Savings That Matter
Current data shows that 65% of legal AI users save 1-5 hours weekly, while 12% reclaim 6-10 hours. However, these savings often come from low-value tasks. CRIT helps firms capture time savings on high-value activities where the ROI compounds significantly.
📊 Real-World Application
In one case study Woods shares, a CEO used AI to solve a complex international debt restructuring challenge. What would have taken months of analysis with traditional consulting was accomplished in a single strategic AI session using the CRIT framework. The AI identified non-obvious restructuring strategies that saved the company from bankruptcy.
Competitive Differentiation
With AI adoption accelerating across the legal industry, the question is no longer whether to use AI but how effectively you use it. Firms that treat AI as a sophisticated thought partner—using frameworks like CRIT—will increasingly outperform competitors who use AI for basic automation.
This is particularly relevant for AI search optimization, where understanding how AI platforms evaluate and recommend law firms requires strategic thinking rather than tactical execution. The same CRIT framework that improves your AI prompts can inform how you position your firm for AI-driven discovery.
CRIT Framework Examples for Legal Professionals
The following examples demonstrate CRIT applied to common law firm scenarios. Each shows how the framework transforms generic AI interactions into strategic conversations.
Example 1: Marketing Strategy Review
Context:
“I’m a marketing director at a family law firm with 8 attorneys in Dallas. We spend $15,000/month on Google Ads with a cost per lead of $180. Our conversion rate from lead to consultation is 45%, and from consultation to retained client is 30%. Average case value is $12,000.”
Role:
“Act as a CMO with 15 years of experience optimizing legal marketing funnels and improving marketing ROI for professional services firms.”
Interview:
“Interview me. Ask one question at a time, up to three questions, to understand our competitive landscape and marketing challenges.”
Task:
“After the interview, provide a prioritized action plan to reduce our cost per acquisition by 25% over 90 days while maintaining lead quality.”
Example 2: Contract Review Workflow
Context:
“I received a mutual NDA from a potential vendor. I’m a solo practitioner and need to review it quickly while ensuring it protects my client’s interests. My client is a software development firm concerned about IP protection and non-compete clauses.”
Role:
“Become a contracts attorney with expertise in technology transactions and IP protection.”
Interview:
“Interview me. Ask one question at a time, up to three questions, about my client’s specific concerns and the nature of the potential business relationship.”
Task:
“Review the attached NDA. Identify any provisions that are unusual, potentially unfavorable, or that warrant negotiation. Provide specific redline suggestions for any concerning language.”
Example 3: Firm Growth Strategy
Context:
“I’m managing partner of a 20-attorney personal injury firm in Houston. We’ve grown 15% annually for three years but are seeing increased competition from larger firms with bigger marketing budgets. We’re considering whether to expand our practice areas, open satellite offices, or double down on PI specialization.”
Role:
“Act as a skeptical board member with experience scaling professional services firms. Challenge my assumptions and identify risks I may be overlooking.”
Interview:
“Interview me. Ask one question at a time, up to three questions, to understand our competitive position, financial situation, and operational capacity.”
Task:
“After the interview, provide a SWOT analysis of each growth option and recommend which path offers the best risk-adjusted return. Include specific questions I should answer before making a final decision.”
Notice how each example uses CRIT to create a collaborative dialogue rather than a one-shot query. The interview component is particularly powerful—it often surfaces considerations the user hadn’t thought to include in their initial context, leading to more nuanced and actionable recommendations.
How to Implement CRIT Today
Woods recommends a simple starting point that creates immediate habits around CRIT usage.
Step 1: The Sticky Note System
Take two sticky notes and a thick marker. On the first sticky note, write: “How can AI help me do this?” On the second, write: “Context, Role, Interview, Task (CRIT)”. Stick these on your desk or monitor where you’ll see them daily.
The first note creates awareness—training yourself to identify opportunities where AI could add value throughout your day. The second note provides the framework for acting on those opportunities effectively.
Step 2: Start with High-Value, Low-Risk Applications
Begin using CRIT for strategic thinking exercises rather than client-facing work. Examples include reviewing your content marketing strategy, preparing for partner meetings, evaluating new technology investments, or analyzing competitor positioning.
This approach builds comfort with the framework in low-stakes environments while demonstrating its value before extending to client matters requiring more careful consideration of AI content risks and data security.
Step 3: Create Your AI Board of Advisors
Woods uses a technique he calls the “AI Board of Advisors”—running the same strategic question through multiple expert roles to gain diverse perspectives. For a major decision, you might use CRIT with:
- A marketing strategist focused on client acquisition
- A CFO examining financial implications
- A skeptical competitor identifying vulnerabilities
- A client evaluating your firm against alternatives
- An industry analyst predicting market trends
This multi-perspective approach surfaces blind spots and stress-tests assumptions in ways that single-role prompts cannot.
Step 4: Build Team Adoption
As Woods emphasizes, psychological safety is key when adopting AI. Team members who don’t feel safe to experiment, make mistakes, or ask questions won’t fully engage with the technology. Create learning opportunities, encourage peer support, and recognize that adoption will occur at different speeds across your team.
Consider integrating CRIT training into your firm’s professional development program. For firms investing in AI marketing automation or other AI tools, CRIT provides a foundational skill set that improves results across all AI applications.
Frequently Asked Questions About the CRIT Framework
What AI platforms work best with the CRIT framework?
CRIT works effectively with all major AI platforms including ChatGPT, Claude, Google Gemini, and Perplexity AI. The framework is platform-agnostic because it focuses on how you structure your communication rather than technical features of specific tools. Geoff Woods uses CRIT with various platforms depending on the task, and the methodology transfers seamlessly between them.
How long does it take to learn the CRIT framework?
The basic framework can be learned in minutes—it’s simply Context, Role, Interview, Task. However, mastery develops through practice. Most professionals see immediate improvement in AI output quality from their first CRIT prompt. Within 2-3 weeks of consistent use, the framework becomes second nature. The sticky note system Woods recommends accelerates this learning curve by creating constant visual reminders.
Is CRIT appropriate for client-facing legal work?
CRIT can be applied to client matters with appropriate safeguards. Woods emphasizes using enterprise versions of AI tools that don’t train on your data for confidential work. Many firms begin with internal strategic applications before extending to client work. For client matters, always verify AI outputs, maintain attorney oversight, and ensure compliance with your jurisdiction’s ethics rules regarding AI use in legal practice.
What makes the Interview step so important?
The Interview step is what most people skip, yet it often produces the most value. When you instruct AI to ask clarifying questions, it surfaces considerations you hadn’t thought to mention in your initial context. This deepens the AI’s understanding and typically improves output quality by 50% or more. The interview also transforms the interaction from one-way instruction to collaborative dialogue, which aligns with AI’s strength as a thought partner rather than just a content generator.
How does CRIT compare to other prompting frameworks?
Various prompting frameworks exist, but CRIT distinguishes itself through the Interview component, which creates genuine dialogue rather than one-shot queries. While other frameworks focus primarily on structuring initial prompts, CRIT acknowledges that AI works best when it can gather additional context through conversation. For law firms already developing AI prompt frameworks, CRIT provides a complementary methodology focused on strategic applications.
Can CRIT help with law firm marketing specifically?
Absolutely. CRIT is particularly valuable for marketing strategy development, competitive analysis, content planning, and campaign optimization. By assigning AI roles like “legal marketing consultant” or “potential client evaluating law firms,” you gain perspectives that inform everything from local SEO strategy to client communication. The framework helps firms move beyond generic marketing advice to strategies specifically tailored to their practice area, geography, and competitive landscape.
Where can I learn more about Geoff Woods and The AI-Driven Leader?
Geoff Woods’ book The AI-Driven Leader: Harnessing AI to Make Faster, Smarter Decisions is available on Amazon in print, Kindle, and Audible formats. He also hosts the AI-Driven Leader podcast and offers executive programs through AI Leadership. For those interested in applying AI strategically to law firm growth, the book provides detailed case studies and additional frameworks beyond CRIT. Emailing your purchase receipt to Geoff’s team unlocks a bonus PDF containing 40 strategic AI prompts.
Ready to Transform How Your Firm Uses AI?
InterCore Technologies helps law firms implement AI-powered marketing strategies that deliver measurable results. Learn how frameworks like CRIT can accelerate your firm’s growth.
📞 (213) 282-3001 • ✉️ sales@intercore.net
13428 Maxella Ave, Marina Del Rey, CA 90292
Key Takeaways: Implementing CRIT in Your Practice
The CRIT framework represents a fundamental shift in how professionals approach AI—from treating it as a content machine to engaging it as a strategic thought partner. For law firms navigating the accelerating AI revolution, this distinction increasingly separates market leaders from those falling behind.
As Geoff Woods emphasizes, the leadership skills that got us here won’t be enough to get us where we need to go. With 82% of legal AI users reporting increased efficiency and trust in AI among General Counsel doubling in a single year, the question is no longer whether to adopt AI but how to use it effectively.
CRIT provides a repeatable framework that anyone can implement immediately. Start with the sticky notes. Begin with strategic rather than operational applications. Build your AI board of advisors. Create psychological safety for your team to experiment. Most importantly, recognize that the unfair advantage comes not from the tool itself but from how you think before you type.
For firms seeking to extend AI capabilities beyond internal applications to client-facing marketing, Generative Engine Optimization (GEO) represents the next frontier—ensuring your firm is visible and recommended when potential clients use AI platforms to research legal services.
The firms that thrive in the AI era will be those that master both internal AI usage through frameworks like CRIT and external AI visibility through strategic optimization. The time to develop these capabilities is now.
Scott Wiseman
CEO & Founder, InterCore Technologies
Scott founded InterCore Technologies in 2002 and has spent over two decades helping law firms leverage emerging technologies for competitive advantage. He specializes in AI-powered marketing strategies and Generative Engine Optimization, working with personal injury, family law, criminal defense, and estate planning practices nationwide.