AI Kingdom

Agentic AI Instructor Guide

The Agentic AI Instructor Guide can be utilized so that one can review via a demonstration aspect key and core information regarding the subject matter of most value to the topic.

https://www.amazon.com/dp/B0GTX69S8T/

What is Agentic AI?

Agentic AI refers to AI systems that don't just respond, they take initiative, make decisions, and carry out multiple‑step tasks to achieve a goal. This is done via the utilization of AI agents which follow these aspects:

1. Understands goals, not just questions

2. Breaks tasks into steps

3. Takes actions in the world

4. Adapts and self-corrects

Using This Guide

To best leverage the material in this guide, it is suggested that each high-level topic be reviewed via a discussion. High level bullet points and numbering depicted throughout the guide will help with this overview. Additionally, when applicable enter in any generative prompts and then experiment as desired.

Estimated instructor overview time: 60-90 minutes depending on discussion and examples utilized.

Contents

What is Agentic AI?

Using This Guide

Using Generative AI

Overview of Agentic AI

Evolution of Agentic AI

Agentic AI + Workflow Agents

Agentic AI + Autonomous Agents

Agentic AI + Hybrid Agents

Agentic AI + Service Options

Agentic AI + Agent Fundamentals

Agentic AI + Modular Architecture

Agentic AI + Goal Oriented Planning Loop

Agentic AI + Memory and Context Retention

Agentic AI + Tool Use and External Integration

Agentic AI + Self-Evaluation and Reflection

Agentic AI + Observability Patterns

Agentic AI + Interoperability Patterns

Closing Notes:

About the Author:

Notes:

Simple but Good Image Prompts

The following are two useful prompts to utilize to create images.

Use the prompt engine of your choice be it https://www.chatgpt.com, https://copilot.microsoft.com or https://gemini.google.com - then utilize these prompts to get the desired effect:

Create an image for [name of brand or product] in a vintage style poster using a portrait aspect ratio.

Generate an image in the style of an infographic with an image of 1080x1350 resolution which utilizes this text: [enter in text for infographic].

Norman Rockwell Style Generative Prompt with your Photo Upload

If you are looking to utilize a generative AI prompt to create a Norman Rockwell type photo, the following is for you:

After uploading the desired photo into the prompt engine of your choice be it https://www.chatgpt.com, https://copilot.microsoft.com or https://gemini.google.com - then utilize this prompt to get the desired effect:

Create an engaging Norman Rockwell style illustration from the uploaded photo.

This should look like a hand-painted mid-20th-century editorial illustration and not a photo from a modern AI filter.

STYLE & TECHNIQUE:

• Authentic Norman Rockwell / Saturday Evening Post style

• Clean, illustrative brushwork with visible paint strokes

• Crisp edges and defined forms (not using a soft-focus or blurry)

• Slightly exaggerated expressions and gestures for storytelling

• Warm but balanced lighting, not with a overly glow or hazy

COMPOSITION & STORY:

• Recompose the scene to clearly tell a story

• Emphasize body language, facial expressions, and interaction

• Adjust poses subtly if needed to strengthen the narrative

• This should feel like a single moment frozen in time

SUBJECT:

• Preserve accurate likeness, age, and personality

• Do NOT beautify or modernize

• Keep natural character lines and expressions

• Faces should feel expressive and alive, not smoothed

BACKGROUND:

• Replace modern elements with a timeless, simplified interior

• Remove electronics, modern furniture, branding, clutter

• Background should support the story without distraction

COLOR & FEEL:

• Muted, classic Americana color palette

• Natural skin tones

• Painterly, illustrative, not photographic realism

FINAL GOAL:

Make this photo look like a real Norman Rockwell illustration which someone would recognize immediately, suitable for a vintage magazine cover or framed print.

AI for Scrum Masters Guide

https://www.amazon.com/dp/B0FW3RLC15/

This guide is designed for scrum masters, project managers, product managers, and agile team members who are ready to work more efficiently by integrating artificial intelligence (AI) into their work processes. The guide provides core and key subject matter with each section having generative AI based example prompts to utilize as needed.

Key-concepts in this guide include:

Contents

Using This Guide

Using Generative AI

Everyday AI Tools for Scrum Masters

Summary

Introduction

Key Trends

Sentiment Analysis for Team Engagement

AI Chatbots for Automating Scrum Events

Predictive Risk Assessment

Use Case Prompts: Everyday AI Tools for Scrum Masters

Prompt Engineering: AI Introduction for Scrum Masters

Introduction

Key Trends

Implementation Challenges

Use Case Prompts: AI Introduction for Scrum Masters

Customizing AI for A Scrum Team

Introduction

Key Trends

Implementation Challenges

Use Case Prompts: Customizing AI for A Scrum Team

AI-Powered Strategic Planning for Scrum Masters

Introduction

Key Trends

Implementation Challenges

Use Case Prompts: AI-Powered Strategic Planning for Scrum Masters

AI-Powered Communication and Collaboration for Scrum Masters

Introduction

Key Trends

Implementation Challenges

Use Case Prompts: AI-Powered Communication and Collaboration for Scrum Masters

Data-Driven Team Management for Scrum Masters

Introduction

Key Trends

Implementation Challenges

Use Case Prompts: Data-Driven Team Management for Scrum Masters

Ethical AI in a Scrum Practice for Scrum Masters

Introduction

Key Trends

Implementation Challenges

Use Case Prompts: Ethical AI in a Scrum Practice for Scrum Masters

Learning: Prompt Engineering for Scrum Masters

Introduction

Key Trends

Implementation Challenges

Use Case Prompts: Prompt Engineering for Scrum Masters

Bonus: Agile Prompt Engineering Framework

About the Author:

Notes:

AI Generative for Creating a Needed PowerShell

The following is one of my favorite AI based generative prompts in order to obtain a good PowerShell script for what is needed:

Prompt:

Create a PowerShell script which <describes the first aspect that is needed>.

The script should traverse through and then output the results as a csv file called <name of csv file to be utilized>.

Explain the details of the script step by step for clarity.

Example:

Create a PowerShell script which shows all the latest updates of my PC.

The script should traverse through and then output the results as a csv file called pc_updates.csv.

Explain the details of the script step by step for clarity.

Two Useful Generative Prompts for Research Purposes

The following are two of my favorite prompts to utilize for core and key research purposes.

Try the following in your favorite AI engine be it https://www.chatgpt.com, https://copilot.microsoft.com, etc:

Write a comprehensive research report on [title].

Include real-world use cases, major players, and challenges in implementation.

Present the findings in the following format:

1) Executive Summary (150 words)

2) Introduction

3) Key Trends (with supporting data and citations)

4) Major Companies and Tools

5) Implementation Challenges

6) Sample Prompts

7) Advanced Sample Prompts

8) Conclusion

-------------------------------

Adopt the role of a [title].

Your mission: create a comprehensive, executive-ready strategic report utilizing common frameworks and methodologies.

Process:

Context Discovery – Clarify the business challenge, industry, and strategic based questions.

Stakeholder & Success Definition – Map key decision-makers, define success and set boundaries.

Market Research – Analyze industry trends, competition, customers, regulation, and macro-based forces.

Frameworks – Apply Porter's five forces, value chain, strengths, weaknesses, opportunities, threats, and other common frameworks.

Insight Generation – Synthesize the data into insights and implications.

Options Development – Create strategic based pathways with trade-offs.

Recommendations – Prioritize actions with rationale, key performance indicators and an implementation-based approach.

Executive Report – Deliver structured report: summary, analysis, recommendations, risks and metrics.

Implementation Roadmap – Define 90-day wins, 6-month initiatives and 12-month milestones.

Instructions:

Provide the business challenge, industry, and key questions.

Generate a quality strategic report with research, insights, and actionable recommendations.

--------------------------------

Applied Generative AI Instructor Guide

https://www.amazon.com/dp/B0FBLQDYYJ/

Applied Generative AI is an area which encompasses creating original and innovative content. This includes integrating technical expertise with management insights, ethical considerations, and human based factors. In this instructor guide, each section provides core and key topical information of value to discuss with example generative prompts which can then be utilized.

Table of Contents:

Using Instructor Guide

Using Generative AI

History and Evolution of AI

Introduction to LLMs

Understanding LLM Architecture: From Words to Meaning

AI Today and in the Future

Democratization of Data & AI: The Neural Network Revolution

LLMs: What Can They Do and How Do They Work?

Predicting the Future: Neural Networks

Autoencoders, Latent Spaces & Embedding Spaces

LLMOps (Large Language Model Operations)

An Introduction to AI and Ethics

Cultivating an AI-Ready Culture

Speed of Applied Generative AI Learning

Building on LLMs and the Future of Jobs

The AI-Enabled Economy

Conclusion:

About the Author:

Notes:

AI Roadmap

https://www.amazon.com/dp/B0F81JXCT2/

The artificial intelligence roadmap is a strategic overview of the core business and technical aspects that make up AI. After each concept, an example generative AI prompt is depicted for further understanding.

Contents:

Using Generative AI

Business Aspects for AI

Business Strategy

Workforce Development

Uses of AI

Governance

Tools and Infrastructure

Innovative Research & Development

Technical Training

Measurement and Monitoring

Generative AI Prompts for Business Aspects

Technical Aspects for AI

Artificial Intelligence

Machine Learning

Neural Networks

Deep Learning

Generative AI

Generative AI Prompts for Technical Aspects

About the Author:

Notes:

5 Stages are Needed for an AI Plan to be Successful

As an individual passionate about AI, I recently sent some comments as such regarding this AI item:

Request for Information on the Development of an Artificial Intelligence (AI) Action Plan

In my view 5 Stages are needed for an AI plan to be successful:

Exploring phase - where having an understanding of AI basics is learned. Most end users are not aware that prompts they enter into https://www.chatgpt.com or https://copilot.microsoft.com are generative prompts. For any kind of core and key automation, plugins along with a series of carefully crafted prompts are needed as well. Also, end users need to know that prompts they enter can be deleted from a said user's profile when applicable. Additionally, AI is made-up of the core concepts which should be part of any education: algorithms, autonomous systems, machine learning, supervised learning, unsupervised learning, reinforcement learning, deep learning and fuzzy logic. Finally, knowing the capabilities, limitations and ethical considerations of the AI based system being utilized is paramount.

Planning phase - actively accessing, defining and planning so that specific measurable objectives are met. Knowing what one wants to measure regarding how time is saved from AI is a major part of this phase. Additionally having key performance indicators and meeting them is key as well. Example: how does AI help regarding defect rates helping with quality, how does AI help regarding a planned to done ratio for predictability and finally how does AI help with happiness for stability.

Formalizing phase - socializing and executing on the AI strategy plan. Have concepts structured and documented into official actionable plans. Currently AI is still evolving but even so, it needs to have core aspects more standardized especially around the use of templates, checklists and protocols.

Scaling phase - delivering both incremental and new values regarding AI aspects. No matter what, an AI plan is going to have to include the handling of a larger workload and workforce. It needs to have the proper infrastructure improvement as needed as well as the proper process optimization for the automating of repetitive tasks, workflows and new practices that evolve.

Realizing phase - having consistent AI value across the environment. Be able to handle the execution of plans accounting for resource utilization, monitoring and control and finally quality assurances. If AI does not have consistency or have value, then it will not fulfill its usefulness.

Power Drill Cordless: DEKO PRO Cordless Drill 20V Electric Power Drill Set Tool for Women Drills Cordless with Battery and Charger Drill Driver 20 Volt Drill Driver Kit Red

https://amzn.to/4313glW

As an Amazon Associate, I earn from qualifying purchases.

Generative AI Aspects Explained

https://www.amazon.com/dp/B0DWQHRY25/

The following are core generative artificial intelligence (AI) aspects explained with key examples. Each aspect is grouped into one of the following: contextual learning, agents, fine-tuning, retrieval augmented generation, evaluation metrics, foundation models and transformers. Finally, example generative AI prompts to leverage, using the aspects is given.

Contents include: Overview of Generative AI, Generative AI Aspects, Using Generative AI, Contextual Learning Model, Agents,

Fine Tuning, Retrieval Augmented Generation, Evaluation Metrics, Foundation Models and Transformers.

Today Loves Food: Recipes from America’s Favorite Kitchen

https://amzn.to/3ZCoCml

As an Amazon Associate, I earn from qualifying purchases.

4 Data Deep Dive Aspects

The following are four data deep dive aspects for laying the foundation for AI based technologies:

Data Literacy - use of generative AI technologies are leveraged efficiently and effectively.

Data Readiness - core and key data is ready to be able to be returned in prompts.

Data Quality - data that is to be utilized and returned in prompt technologies is useful and correct.

Data Trust - data that is utilized is indeed from a trusted source.

What is Artificial Intelligence (AI)?: A Simplified Overview

https://www.amazon.com/dp/B0DT7TKKCC/

Artificial Intelligence (AI) is a rapidly evolving field that involves creating systems capable of performing tasks which typically require human intelligence. These tasks include learning, reasoning, problem-solving, perception, language understanding, and interaction.

Apple iPad (10th Generation): with A14 Bionic chip, 10.9-inch Liquid Retina Display, 64GB, Wi-Fi 6, 12MP front/12MP Back Camera, Touch ID, All-Day Battery Life – Yellow

https://amzn.to/3WpmsFR

As an Amazon Associate, I earn from qualifying purchases.

Therefore, this overview covers the most common aspects of AI. The information can be utilized for personal, educational, or corporate usage. It is envisioned that one utilizes the material for discussion and demonstration purposes. After each key topic, a series of generative prompts for example purposes is depicted.

Contents

Overview of AI:

Overview of Generative AI:

Using Generative AI:

Generative AI Prompt Examples:

Overview of Algorithm:

Algorithm Prompt Examples:

Overview of Autonomous System:

Autonomous Systems Prompt Examples:

Overview of Machine Learning:

Machine Learning Prompt Examples:

Overview of Supervised Learning:

Supervised Learning Prompt Examples:

Overview of Unsupervised Learning:

Unsupervised Learning Example Prompts:

Overview of Reinforcement Learning:

Reinforcement Learning Example Prompts:

Overview of Deep Learning:

Deep Learning Example Prompts:

Overview of Fuzzy Logic:

Fuzzy Logic Example Prompts:

Overview of AI Engineer Roles:

About the Author:

Notes:

Top 3 Predictive Models in AI

The following are the top three predictive models in AI:

Linear Regression: One of the simplest and most commonly utilized predictive models. It's used to predict a continuous outcome variable based on one or more predictor variables. It works well for problems where the relationship between the variables is linear.

Decision Trees: Versatile and utilized for both classification and regression tasks. They work by splitting the data into subsets based on feature values, creating a tree-like structure of decisions. Decision trees are easy to interpret and can capture non-linear relationships.

Neural Networks: More complex models that are effective for tasks involving large amounts of data and complex patterns. Neural networks consist of layers of interconnected nodes (neurons) and can model highly intricate relationships in the data.

Brother P-Touch, PTM95, Handy Label Maker, 9 Type Styles, 8 Deco Mode Patterns, Navy Blue, Blue Gray

https://amzn.to/3VjjVfO

As an Amazon Associate, I earn from qualifying purchases.