Decision Intelligence Generative AI Workshop

[Work In Progress - Estimated Beta Launch: May 2025]

Contents:
💡 About
👣 Different Ways To Get Started
📖 Printed Book
🧱 Workshop Modules
✅ Requirements for Interactive Decision Notebooks

About

Navigating decisions effectively is important, serving as a key differentiator for successful individuals. Therefore, decision-making ability is regarded by executives as one of the most highly desired business skills! However, effective and quality decision-making is not simple. Perhaps the intersection of Decision Theory and Generative AI can help.

The Decision Intelligence Generative AI Workshop is an interactive course that is paired with an upcoming book called "Decision Intelligence with Generative AI". This course was designed with a focus on three key areas:

• Introduction to Decision-Making with a Decision Intelligence Framework that covers systematic processes of making decisions
• Application of Decision Intelligence theory with Generative AI
• Interative Notebooks for AI engineers/software engineers to execute the examples with an orchestration framework (Semantic Kernel & OpenAI)

The unique workshop structure with diverse focus areas, allows this workshop to be consumed in several ways. Depending on your persona, familiarity with Decision Theory or AI acumen, you have several paths to get started.

Different Ways To Get Started

1. Read Persona - Ideal for non-technical users not familiar with Decision Intelligence nor Generative AI

• Nothing to install! No special requirements to read any of the workshop content. All the of the text, links & images are available by just navigating to the Notebooks folder and reading the section modules sequentially. Notebooks folder: https://github.com/bartczernicki/DecisionIntelligence.GenAI.Workshop/tree/main/Notebooks
• All Generative AI output is pre-run and available to read in a browser
• Recommend further detailed book resources provided in the workshop to immerse yourself in Decision Theory, Decision-Making, Cognitive Theory etc.
• Recommend companion book "Generative AI with Decision Intelligence" (coming late 2025) for a more complete reading experience and advanced content not in the workshop

2. Technical Persona - Ideal for technical users that might not be familiar with Decision Intelligence nor Generative AI, but are familiar with Jupyter Notebooks interactivity

• All the considerations from the "Read Persona" Getting Started applies
• Set up the Requirements for Interactive Decision Notebooks to add custom interactivity
• Run the workshop Notebook modules sequentially (no coding required!), as the Decision Intelligence & AI concepts "build on" each other
• C#/.NET Code will be executed but simple modifications to decision prompts, agents, configuration files are clear to added decision exploration

3. Decision Intelligence AI Engineer - Ideal for a technical user that is familiar with programming and Generative AI

• Most of the considerations from the "Technical Persona" Getting Started applies
• Set up the Requirements for Interactive Decision Notebooks to add custom interactivity
• Notebook modules do not "build on each other" from a programming dependency; only from a Decision Intelligence concept dependency. Therefore, you can jump in and modify where needed
• Recommended to "Fork and Hack" and gravitate to the Decision Scenarios with most impact (change AI models, try different APIs or knowledge stores, advanced AI programming techniques, port code to your projects etc.)

Printed Book

What is difference between the workshop the printed companion book? The Printed Book has the following features:

• Deeper focus on Decision Intelligence theory with application of Generative AI rather than a code-first focus.
• Additional advanced real-world examples with Artificial Intelligence.
• Chapters are organized using the Decision Intelligence Framework. There is no code illustrated in the book, making it easier to consume for non-technical readers.
• References in text content to further deepen decision-making knowledge.
• Extra Curated Chapters with Lists for Easy Lookup of: Decision Intelligence Quotes, Decision Rules, Decision Intelligence Resources.

Workshop Modules

The Table of Contents below illustrates the structure of the Decision Intelligence with Generative AI Workshop. The workshop is structured on concepts broken down into Notebook modules (chapters). Each Notebook module consists of Decision Intelligence concepts and/or interactive Generative AI features that can be dynamically executed.

⚠️ This workshop is currently being developed in conjunction with the companion book. During this time, there will be frequent changes. Content that is available (even if partially) is noted below. Content that does not have the Availability checkmark is in early stages or not available yet. Please check back for updates!

Module (Chapter)	Available	Link
1a - Decision Intelligence - Introducing the Decision Intelligence Framework	☑️	Link
1b - Decision Intelligence - Decision Framing	☑️	Link
1c - Decision Intelligence - Gathering Intelligence	☑️	Link
1d - Decision Intelligence - Decision Execution with Intuition	☑️	Link
1e - Decision Intelligence - Decision Execution with Decision Rules	☑️	Link
1f - Decision Intelligence - Decision Execution with Quantitative Methods		Link
1g - Decision Intelligence - Decision Communication		Link
1h - Decision Intelligence - Using the Decision Intelligence Framework		Link
1i - Decision Intelligence - Enterprise Decision Intelligence		Link
2a - Workshop - Setup to Execute Code Exercises	☑️	Link
2b - Workshop - About Microsoft AI Extensions	☑️	Link
2c - Workshop - About Semantic Kernel Orchestration	☑️	Link
2d - Semantic Kernel - Simple Decision Prompts	☑️	Link
2e - Semantic Kernel - Chat Completion for Decisions	☑️	Link
2f - Semantic Kernel - Open Source Decision Intelligence	☑️	Link
2g - Semantic Kernel - Prompt Engineering for Quality Decisions	☑️	Link
2h - Semantic Kernel - Premortem (What-If) Decision Analysis	☑️	Link
2i - Semantic Kernel - Gathering Intelligence with Generative AI	☑️	Link
3a - Semantic Kernel - Decisions with Semantic Functions	☑️	Link
3b - Semantic Kernel - Decisions with Native Functions	☑️	Link
3c - Semantic Kernel - Optimizing with Decision Frames	☑️	Link
4a - Semantic Kernel - Scale Decision Processes with Plugins	☑️	Link
4b - Semantic Kernel - Plugins for Decision Communication	☑️	Link
4c - Semantic Kernel - Custom Plugins for Decision Recommendation	☑️	Link
4d - Semantic Kernel - Diverse Plugins for Decison Making	☑️	Link
5a - OpenAI - Improving Decisions with OpenAI LogProbs		Link
5b - OpenAI - Measuring GenAI Probabilistic Accuracy with LogProbs		Link
5c - OpenAI - Validating Multiple Decisions with Aggregated Brier Scores		Link
6a - Semantic Kernel - Decisions with AI Agent Personas	☑️	Link
6b - Semantic Kernel - Agent Personas Decisions with Moderator		Link

Requirements for Interactive Decision Notebooks

1. Visual Studio Code running on your local workstation or VS Code with GitHub CodeSpaces or Azure Machine Learning Notebooks
2. Install .NET 9.x SDK: https://dotnet.microsoft.com/en-us/download/dotnet/9.0
3. Polyglot Notebook extension running in VS Code, which allows you to execute .NET program

5. Clone or fork this GitHub Repository
6. Have access to Azure OpenAI. Bing Search for internet knowledge graph (Endpoint, GPT-4 model, API Key, Bing Search API Key)
7. When running the notebooks, select .NET Interactive for your VS Code Notebook kernel