Understanding AI: Foundations for Strategic Application

A practical guide by Kelly "Curly" Ihme on implementing AI tools to enhance leader workflows, research, and training effectiveness.

*Created in collaboration with artificial intelligence tools

AI101 Module for self-learning

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What We're Focusing On

What We ARE Covering

  • Practical, useful tools (free/cheap/safe)
  • AI compatibility with systems
  • Data security considerations
  • Quality resources for further learning

What We're NOT Covering

  • Detailed explanations of AI types
  • AI boom, arms race, TechBros
  • "Cyber"
  • MATH

Understanding AI and the Rise of Generative AI

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Artificial Intelligence (AI)

AI is a technology that enables machines to mimic human intelligence, with 4 general categories:

numerical prediction, classification, robotic navigation, and language processing.

Generative AI

A subset of AI that creates new content like text, images, music, or code by learning patterns from existing data to generate realistic outputs.

Key Differences from Traditional AI:

• Traditional AI: Analyzes or classifies data

• Generative AI: Generates new content using learned patterns

Gen AI Common Models:

  • GANs (Generative Adversarial Networks): Create realistic images
  • GPTs (Generative Pre-trained Transformers): Generate human-like text)
  • Agentic AI (AI that can take actions and complete multi-step tasks on its own, not just answer questions).
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How Do They Work?

Basic Prompts

Custom Instructions

RAG: Retrieval Augmentation Generation

Custom GPTs (Gems, Agents)

RLM: Recursive LM

How Large Language Models Actually Work

Understanding the mathematics behind AI-powered language prediction

The Core Mechanism

Training Phase

Models analyze massive datasets (books, articles, websites, AI conversations) to learn statistical patterns in language syntax and word relationships

Mathematical Encoding

Text is converted into numerical vectors in high-dimensional space where similar concepts cluster together

Probability Calculation

Neural networks with billions of parameters compute probability distributions for what word should come next

Output Generation

The model selects words based on these probabilities, creating human-like text through pure mathematical prediction

Tokens & Vectors

Words broken into pieces and represented as numbers

Attention Mechanisms

Mathematical functions that weigh which previous words matter most

Parameters

Billions of adjustable weights fine-tuned during training

Understanding Context Windows: Why AI Conversations Degrade

The memory limitations that affect long AI interactions

What is a Context Window?

Fresh Conversation Start

Model has full context window available. All instructions and details are 'remembered' and influence responses.

Window Fills Up

As conversation grows, older messages get pushed out. The model can only 'see' the most recent exchanges within its token limit.

Context Loss Begins

Early instructions, key details, and nuanced context disappear from the model's view, even though you still see them.

Performance Degradation

Without access to earlier context, responses become less accurate, repetitive, or miss important constraints you established.

Forgotten Instructions

Initial guidelines and preferences established early in conversation become invisible to the model

Lost Continuity

References to earlier topics or decisions may be missed or contradicted

Reduced Coherence

Long conversations may feel disjointed as the model loses the narrative thread

AI as a Decision-Support Tool 💻

"By far, the greatest danger of Artificial Intelligence is that people conclude too early that they understand it." -Eliezer Yudkowsky, AI Researcher and Writer

Challenges in Working with AI

AI should support human decision making and judgment…not replace it!

Hallucinations & Inaccuracy

AI can generate false information confidently because of context window limitations and the predictive math that underlies LLMs.

Data Privacy & Security

Sensitive information can be exposed through prompts, risking operational security. Sovereign AI or closed models can mitigate risk.

Over-Reliance & Skill Degradation

Depending too heavily on AI can erode critical thinking and core competencies.

Bias & Ethical Concerns

AI models can perpetuate biases and raise ethical questions about appropriate use.

Gen AI: Relevance and Core Capabilities

Military Applications

  • Drafting: Quickly generate operational plans, OPORD fragments, or intel summaries for staff review
  • Scenario Generation: Prototype COAs, simulate adversary reactions, or generate wargame injects
  • Planning Support: Outline logistics concepts, terrain analyses, and pre-brief talking points

Generative AI extends traditional AI capabilities to new paradigms

  • Multi-modal input and output
  • Rapid content generation
  • Dynamic modeling and simulation
  • Creative ideation and innovation


Academic Applications

  • Research: Summarize doctrine, journal articles, and historical case studies
  • Writing: Draft outlines or discussion posts; generate thesis statements or counterarguments

AI Basics #1
Managing Your AI Workflows

Name Your Conversations

Rename AI conversations to your topic area for better organization; pin key conversations

Maintain Context

Return to the same conversation as you work on a project, update your context window

Reference Previous Discussions

Use prompts like "Using the previous discussion..." for continuity

Model Alignment

Each AI has specialty functionality, keep like functions with the same AI (images with Dall-E, code with Claude, videos with Veo and Nano Banana, research with Thesify, etc)

AI Basics #2
Prompt Design

The Answer is 42

Role/Persona

Assign the AI a specific role like "expert historian" or "UX designer" to shape response style.

Specificity

Include precise details about format, length, and tone. Vague prompts yield vague results.

Example Output

Show the AI what success looks like with sample formats or structures.

Context

Provide relevant background information to help the AI understand your needs.

Feedback

Refine results by telling the AI what worked and what needs improvement.

Bad Prompt: “Write a plan for training”

Good Prompt: "You are a military training officer assigned to develop a two-day urban warfare training exercise for Task Force Alpha in the fictional city of Fortwood. The primary objective is to train on building clearing, coordination between infantry and armored units, and communication with air support. Please provide a structured plan, including a timeline, key tasks, and expected outcomes for each phase. You may use examples of past urban training operations for context. If you need more details about the unit’s composition, available resources, or exercise limitations, ask clarifying questions before proceeding."

AI Basics #3
Efficient AI-to-Document Workflow

GenAI.mil output

Generate Content

Use a GPT or other AI tools to create initial content

Copy and Format

Copy AI output and paste into Excel for table manipulation or Word for documents

Integrate and Finalize

Embed the formatted content into your articles, outlines, or other materials

AI Basics #4:
Converting Handwritten Notes to Text

Capture Handwritten Notes

Take a clear photo of your handwritten notes or sketches

Upload to a GPT

Create memos, notes, images

Summarize and Convert

Capture brainstorming sessions from whiteboards or multiple notetakers

Create summaries, MFRs, and reports

AI Basics #5
Research and Source Generation

Specialized AI Tools

Use purpose-built research tools like Elicit AI, Thesify, and AI Agenics to find sources and generate literature reviews with proper citations.


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Quality Prompting

Craft detailed prompts for general LLMs or GPTs to develop comprehensive source lists and research summaries.

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Verification Process

Always verify AI-generated sources and cross-reference information for accuracy before including in any work.

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Use Specialized Models

Deep Research models without GenAI.mil (CAC required) and commercial platforms provide the "thinking" and logic steps along with citations, links, and other sources as prompted for detailed answers.

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Advanced AI Incorporation
Enhancing Engagement

Generate Discussions

Create realistic conversation scenarios for student practice

Summarize Content

Condense complex discussions into key takeaways

Address Learning Styles

Adapt content to different learner modalities

Promote Critical Thinking

Develop thought-provoking questions and scenarios

Socratic Tutor

Streamlining Training Development

Lesson Planning

Generate structured lesson outlines and objectives

Content Creation

Develop engaging materials and activities

Assessment Design

Create varied assessment tools and rubrics

Refinement

Improve based on outcomes and feedback

ChatGPT

ChatGPT - 6-Week Peak Mind Syllabus

Shared via ChatGPT

The Future of AI

Exponential Growth

AI capabilities continue to follow Moore's Law, with processing power doubling approximately every two years.

Creative AI

Video and song creation tools now produce professional-quality content with minimal human input.

Intelligent Gaming

Games feature increasingly sophisticated AI opponents and companions that adapt to player behavior.

Human-Machine Teaming

The future workforce will blend human creativity with AI efficiency in seamless partnerships.

Questions?

Ethan Mollick on LinkedIn & Substack

Follow for updated opinions on which AI tools to use and practical applications in education. Visit: https://www.oneusefulthing.org/p/which-ai-to-use-now-an-updated-opinionated

Andy Stapleton on YouTube

2Excellent tutorials and demonstrations of AI tools in action. Watch: https://www.youtube.com/watch?v=QDZDPnTYOZg&t=624s&pp=ygUKbm90ZWJvb2tsbQ%3D%3D

How AI Works on YouTube

8 minute video explaining large language models. Watch: https://www.youtube.com/watch?v=LPZh9BOjkQs

19 minute video on neural networks. Watch: https://www.youtube.com/watch?v=aircAruvnKk&t=2s

Additional Learning Materials

Explore books, courses, and other resources to deepen your understanding of AI applications in education.

AI in PME article by Ihme and Rasmussen

AI in OSINT article by Ihme