Double Your First Pass Accurcy & Cut Your Effort in Half for Individuals and Enterprises. Want to Learn More, Sign-Up for The Kendall Framework AI Leader Course or Create Foundationa AI Context with a Kendall Framework Team Workshop.
Reusable guided context components that help your team and your AI understand what matters most in your business.
Created in the Worlds Most Powerful AI Innovation Hub, Kendall Square, The Kendall Framework creates better, faster AI results. If you’ve ever worked with AI, you know the difference between a great response and a mediocre one comes down to one thing—how well you structure your input.
Vague or overloaded terms lead to misunderstood prompts LLMs fill in the blanks, often incorrectly.
Unstructured input creates uncontrolled variation Without a format, the same request gets phrased 10 different ways, making consistency impossible.
LLMs don’t know your business language Industry terms, internal acronyms, or role-specific context aren’t understood unless explicitly trained.
Ambiguity compounds with each pass Poor first outputs lead to prompting rework, token waste, and user frustration.
Help you clarify your thoughts before prompting AI Structure your request with purpose, so you get better, faster results.
Give you a repeatable method for using AI at work No more starting from scratch—build once, reuse often.
Make your role, challenges, and goals visible to AI So AI responds with answers tailored to what you actually do.
Save time by reducing back-and-forth with AI tools More accuracy, less guessing, and fewer wasted prompts.
Each Context Block captures structured knowledge in key areas:
Role Block — People and roles that are part of the AI solution you are creating
Problem Block — The Problem and challenge you needs solve
Capability Block — Company, organizations and solutions descriptions
Process Block — The processes used to work gets done
Software Creation Block — The scope and specifications needed to build great software solutions with AI.
Person Creation Block - The rules and descriptions needed to build great AI Personas.
With many more to come! Together, these form your AI Blueprint—context that powers AI with clarity and accuracy.
1. Download the Context Blocks You Need. Start by choosing the Context Blocks that match your goal — Role, Problem, Capability, Process, Software or Others. Each one captures a different dimension of enterprise context and helps your AI understand who you are, what you do, and what you need.
2. Fill Out the Context Block Form. Use the editable Kendall Context Block form to describe your situation clearly and completely. You don’t need to be perfect — just focus on giving structured information in plain language. The more accurate your inputs, the smarter your AI results.
3. Save & Upload to Your LLM. Export your completed Block as a PDF or text file. Then upload it directly into your AI tool of choice. Giving your promt "super context" enabling high response accuracy.
4. Use As Prompt Foundation, Start your next prompt by referencing your completed Context Block — or paste it in directly. This gives the AI the clarity it needs to understand your role, your goals, and the problem you’re solving. The result? Smarter, faster responses with less guessing and rework.
Turn team knowledge into structured, AI-readable input So your AI understands your roles, problems, and workflows — not just generic prompts.
Standardize how your organization communicates with AI Reducing ambiguity and improving accuracy across teams and tools.
Enable reusable context across hundreds of AI use cases From research to HR planning to process optimization — once built, blocks scale.
Accelerate team alignment and AI deployment Get faster first-pass results, less rework, and immediate traction with AI systems.
Kendall AI Leaders Course. For AI teams and, innovators, who want to put the power of AI to work.
Course Overview:
This course introduces the philosophy, structure, and power of the Kendall Framework. Participants learn how to identify ambiguous language, structure better AI inputs, and understand how problems, roles, processes, and capabilities come together to train AI.
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