Executable Ontologies: How to Empower Expert Knowledge Workers with AI Language Models
Hey friend, Shep Bryan here. I'm excited to share with you a groundbreaking approach that's transforming how organizations leverage their collective knowledge using AI.
This is part of my independent R&D in artificial intelligence for knowledge work.
The Challenge: Activating Organizational Knowledge
Imagine if your company's collective expertise wasn't just stored in static documents, but was alive, accessible, and actively guiding every decision and task.
We're not talking about traditional wikis or knowledge bases that gather digital dust.
We're envisioning a future where your organization's wisdom and institutional expertise is truly operationalized, working hand-in-hand with cutting-edge AI.
Enter Executable Ontologies
I've developed a novel technique called "executable ontologies" that bridges the gap between human expertise and AI capabilities.
Think of it as a Rosetta Stone that allows AI language models like Claude 3.5 Sonnet, GPT-4, and Llama 3.1 to "speak" your organization's unique language.
What is an Ontology?
Before we go further, let's clarify what we mean by "ontology":
In philosophy, it's a theory describing the nature of existence.
In information science (our focus), it's a formal representation of knowledge within a domain, defining a common vocabulary and relationships between concepts.
Simply put, ontologies are like "thought roadmaps" for AI.
Why Executable Ontologies Matter
Here's why you should care about this approach:
AI Transformation: While AI is revolutionizing work, most organizations are barely scratching the surface of its potential.
Unlocking Hidden Value: Your company's most valuable asset may not be its data, but the collective expertise of your people. Executable ontologies can make that expertise truly actionable.
Empowering Knowledge Workers: This approach allows every team member to leverage AI-powered tools that genuinely understand their job, industry, and organization's unique processes.
Real-World Applications
Forward-thinking teams are already using executable ontologies to:
Supercharge consulting practices
Accelerate content creation
Enable individual team members to dramatically increase their productivity and impact
The Vision: AI That Thinks Like Your Best Employees
Imagine every knowledge worker equipped with AI tools that truly grasp the nuances of their role, industry, and organizational culture. That's the transformative potential of executable ontologies.
Learn More
If you're intrigued by the idea of AI that can think like your best employees, I encourage you to:
Read the full whitepaper: "Empowering Knowledge Workers with Executable Ontologies: An AI-Driven Approach to Knowledge Representation and Operationalization".
Connect with me on LinkedIn if you want to discuss the whitepaper in more detail! (Shep Bryan on LinkedIn)
Closing Thoughts
Executable ontologies represent a powerful new approach to integrating AI into knowledge work.
While they require expertise to create, (combining human insight with AI capabilities), the results are truly game-changing.
Thank you for reading, and I look forward to hearing your thoughts on this exciting development in AI and knowledge management!
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An Example Executable Ontology: Content Creation for Galaxy Brain
The following executable ontology is used for the creation of high quality educational & marketing content around my Galaxy Brain AI Workflow Automation platform.
To use this effectively, I combine this ontology card with a topic. For example, paste this ontology card into Claude 3.5 Sonnet along with the text “AI Workflow Automation for Ad Agencies”.
By pasting this executable ontology in as initial context alongside the topic, an AI assistant immediately has the full context of a request for content creation with zero requirement from the user to provide supplemental context and clarification.
The result is an on-brand and on-target first draft of strong quality, done in significantly less time than the prevailing methods for AI augmentation in knowledge work fields.
Example of utilizing this process with Anthropic’s Claude 3.5 Sonnet model.
Executable Ontology for Creating Galaxy Brain Content
Purpose
To create compelling, thought-provoking content that educates, inspires, and empowers strategists, innovation leaders, data teams, process owners, and citizen developers to harness the power of Galaxy Brain's no-code AI workflow automation platform and drive meaningful change within their organizations.
Tone and Style
Conversational yet authoritative and informative, reflecting Galaxy Brain's expertise in AI workflow automation.
Engaging and thought-provoking, challenging readers to think differently about AI adoption and its potential impact on their organizations.
Balances high-level strategic insights with practical, actionable advice on using Galaxy Brain to build and deploy AI workflows.
Uses real-world examples, case studies, and analogies to illustrate complex AI concepts and make ideas more relatable to a non-technical audience.
Maintains a professional and focused tone, emphasizing the value and benefits of Galaxy Brain without resorting to hype or exaggeration.
Audience
Strategists and consultants looking to quickly prototype and deploy AI solutions for their clients.
Innovation and transformation leaders seeking to drive AI adoption and experimentation within their organizations.
Data and analytics teams aiming to operationalize their AI models and integrate them into business processes.
Business process owners looking to automate and optimize their workflows using AI.
Innovation professionals, strategists, and decision-makers across industries.
Key Themes and Messages
Innovation is a strategic imperative in today's rapidly evolving business landscape, and Galaxy Brain is essential to increasing innovation velocity.
AI workflow automation is a strategic imperative for businesses seeking to stay competitive in today's rapidly evolving landscape.
Galaxy Brain democratizes AI by providing a no-code platform that enables users across the organization to leverage AI capabilities without requiring deep technical expertise.
Galaxy Brain's Playbook Builder, Reusable Elements, and Form/Context Manager features enable users to quickly build and deploy AI workflows that address specific business challenges.
Galaxy Brain ensures consistency, quality, and efficiency in AI workflow development by centralizing management, enforcing standards, and enabling reuse and sharing of workflows and elements.
Galaxy Brain's flexible and extensible architecture allows it to support a wide range of AI use cases and integrate with existing enterprise systems.
Successful innovation requires a willingness to challenge assumptions, take calculated risks, and embrace unconventional thinking.
Content Structure and Flow
Title: [A clear, concise, and engaging title that reflects the main topic and benefit of the article]
Abstract:
[A brief summary of the article's main points, highlighting the key takeaways and value for the reader]
Introduction:
Hook: [A thought-provoking opening statement or question that captures the reader's attention and sets the stage for the article's main topic]
Problem Statement: [A clear and concise description of the problem or challenge the article addresses, emphasizing its relevance to the target audience]
Solution Preview: [A brief overview of the solution or approach the article will explore, hinting at the potential benefits and outcomes for the reader]
Article Promise: [A compelling promise of what the reader will gain from the article, framed in terms of actionable insights, practical strategies, or transformative potential]
Section 1: [Background and Context]
[Subheading 1]: [Key concepts, definitions, or principles necessary for understanding the main topic]
[Subheading 2]: [Historical context, evolution, or current state of the main topic]
[Subheading 3]: [Relevant trends, research, or industry insights related to the main topic]
Section 2: [Main Topic Exploration]
[Subheading 1]: [In-depth examination of a key aspect, component, or strategy related to the main topic]
[Subheading 2]: [Benefits, advantages, or potential applications of the key aspect, component, or strategy]
[Subheading 3]: [Challenges, limitations, or considerations associated with the key aspect, component, or strategy]
Section 3: [Practical Implementation]
[Subheading 1]: [Step-by-step guide or framework for implementing the main topic or key strategies]
[Subheading 2]: [Best practices, tips, or recommendations for successful implementation]
[Subheading 3]: [Common pitfalls, mistakes, or obstacles to avoid during implementation]
Section 4: [Real-World Examples and Case Studies]
[Example 1]: [A concrete, real-world example showcasing the successful application of the main topic or key strategies]
[Example 2]: [Another real-world example highlighting the impact, results, or lessons learned from implementing the main topic or key strategies]
Section 5: [Future Outlook and Opportunities]
[Subheading 1]: [Emerging trends, technologies, or developments related to the main topic]
[Subheading 2]: [Potential future applications, innovations, or areas for growth and exploration]
[Subheading 3]: [Implications, challenges, or opportunities for the target audience in light of the future outlook]
Conclusion:
Recap: [A concise summary of the key points, takeaways, and benefits covered in the article]
Call-to-Action: [A clear and compelling call-to-action, encouraging the reader to apply the insights, strategies, or solutions discussed in the article]
Final Thoughts: [A thought-provoking or inspiring final message that reinforces the value and potential impact of the main topic]
Glossary: [A list of key terms, acronyms, or technical jargon used in the article, along with their definitions, to ensure clarity and understanding]
References and Resources:
[A curated list of additional resources, tools, or references for further learning and exploration related to the main topic]
[Proper citations for any external sources, studies, or examples mentioned in the article]
Language and Formatting
Use clear, concise language that is easy to understand for a non-technical audience.
Explain AI and workflow automation concepts in simple terms, avoiding jargon and technical minutiae.
Break up long paragraphs into shorter, more digestible chunks to improve readability.
Employ subheadings, bullet points, and other formatting techniques to make content more scannable and visually engaging.
Maintain consistency in tone, style, and formatting throughout the piece.
Desired Outcomes
Provide genuine value to the target audience by offering unique insights, practical strategies, and thought-provoking ideas related to AI workflow automation with Galaxy Brain.
Establish Galaxy Brain as a trusted authority and thought leader in the space of AI productivity & AI workflow automation platforms.
Inspire readers to take action and apply the insights and strategies presented to their own organizations, using Galaxy Brain to drive AI adoption and innovation.
Foster a sense of community and shared purpose among Galaxy Brain users who are passionate about leveraging AI to drive change and shape the future of their industries.
Ultimately drive meaningful engagement, conversions, and business results by providing content that resonates with the target audience and compels them to explore Galaxy Brain further.
Interested in leveraging executable ontologies to accelerate your organization’s innovation velocity? Contact me on LinkedIn with this link.
