Putting together an AI-101

Content for the technically curious business leader

Recently, I met a founder/CEO of a services business that helps clients with strategy development, implementation planning, more. We got talking about (of course) the AI hype and what it meant for his business. Halfway into brainstorming ideas, he said

“I’d love to understand more of the technical details behind all this LLM stuff. I think that would help me evaluate ideas more realistically, and also have smarter conversations with my tech teams”

It sounded like a fun thing to put together. So, I spent some time creating an outline of what to cover, calling it “AI-101 for the technically curious business leader”. Then I spent many hours converting that into slides. Including some help from a couple of friends, I think I might have put 25-30 hours of total time into it. But I’m only kinda satisfied with the outcome. Here’s why.

There’s a tradeoff between depth, simplicity and attention span. You can’t have all three.

• If I aim for a short, simple presentation it’s hard to not be pithy. There’s no shortage of those online, from consulting firms, VC firms, content farms and more. There’s even some good videos on YouTube (I made a list) but it doesn’t actually tell you much, and IMO doesn’t pass the bar of enabling you to have smart conversations with your tech teams.

• If we add depth, we have to start basic and build up. That takes length. And length requires attention span, precious time which many don’t have or don’t want to put in. My target audience is a business leader, with technical curiosity and possibly an eng/math background, or at least strong logical thinking skills. Even the best ones have long forgotten their undergrad course material. I quickly found out that anything more than an hour (1.5 hrs max) was undesirable for the majority of these folks.

• And lastly, for completeness, if it’s deep and short it can’t be simple. My audience isn’t able to reach technical papers, simply put.

Along the way, I collected a LOT of good, online (freely available) content across a spectrum of topics, for my target reader. I learnt a lot myself. As they say, when one tries to teach, one learns more and better.

Now, I’m trying out a new approach: 30 minutes, 30 slides. Told as a story of sorts. Each slide has one key message or concept, and maybe a few bullet points, an example, or a diagram. These will be like flash cards - the technically curious business leader

1. Feels better informed because they know something non-trivial

2. Can use this concept or knowledge to contribute to a discussion or meeting in a manner that displays a better understanding of AI (LLM) technology

3. Will be able to dig deeper into this topic (30 mins deeper, say) by viewing some videos or reading articles that are linked

So that makes it a 30 x 30 = potentially 900 minutes (15 hours) worth of content, but much easier to consume, and allowing the reader to only go deep where there is both interest and time.

I’ve built out much of this, and took a small team (leadership from aforementioned company) through a 90-minute long tour of the content. We zipped through the topics, and went deep into several slides where the team had more interest. We stopped at ~90 minutes mainly because people had other meetings to go to, and it was a bit tiring, tbh. Attention span.

I took a few more individuals through this AI-101 walkthrough, and it works quite nicely in small settings. The content gets more refined with each pass, too. And I get a bit better at talking through it. I especially enjoy the questions that come up, since they show me how others are thinking about these new emerging topics.

If you’ve read this far, you’re probably wanting to know details, so here’s the content covered (Slide titles and a little bit of what’s inside):

Module 1: AI & Machine Learning - The Essentials

1. The AI Revolution: Transforming Business as We Know It: A high-level overview of how AI is changing the software landscape and its growing impact on business operations.

2. The Evolution of Software: From Manual Coding to AI-Powered Solutions: Explains the shift from traditional coding (Software 0.5, 1.0) to AI-powered software development (Software 2.0), where machines learn from data instead of explicit instructions.

3. Demystifying the AI Jargon: Key Terms You Need to Know

4. How Machines Learn: Training AI to Solve Business Problems: Introduces different machine learning approaches (Supervised, Unsupervised, Reinforcement Learning) using relatable business examples.

5. Inside the AI Brain: Understanding Neural Networks: A simplified explanation of how neural networks work, using the analogy of a single neuron making decisions based on weighted inputs.

6. Neural Networks in Action: From Inputs to Outputs

7. Training the network: Explains the process of training neural networks, highlighting the importance of data quality, iteration, and avoiding bias.

8. Unlocking AI's Potential: The Power of GPUs

9. AI Beyond Text: Adapting to Images, Sound, and More

Module 2: Natural Language Processing (NLP) and Deep Learning

10. NLP: Teaching Machines to Understand Human Language

11. NLP in Action: Real-World Applications Transforming Business

12. The Building Blocks of NLP: Key Techniques to Know

13. Deep Learning: Taking NLP to the Next Level

14. Transformers: The Game-Changers in NLP

15. The "Attention" Revolution: Understanding How Transformers Work

16. How GPT Works: A Simplified View

17. Essential GPT Concepts: Decoding the Technical Jargon

18. The GPT Landscape: Navigating the Different Types of Models

19. Beyond GPT: Exploring Other Advanced NLP Techniques

Module 3: Building Business Applications with AI/NLP

20. From Concept to Reality: Building AI-Powered Applications

21. The AI Project Lifecycle: From Scoping to Deployment

22. Data: The Foundation of Successful AI

23. Modeling: Choosing the Right AI Approach

24. Deployment: Bringing Your AI Solution to Life

25. MLOps: Ensuring Your AI Projects Deliver Value

26. Open Source vs. Closed Source: Choosing the Right AI Approach

27. The AI Tech Stack: Key Components for Success

28. Navigating the AI Landscape: Key Considerations for Business Leaders

Module 4: The Future of AI - Latest Innovations and Trends

29. Beyond the Hype: Separating AI Reality from Fiction

30. The Future of AI: Trends Shaping the Business Landscape

31. Staying Ahead of the Curve: Resources for Continuous Learning

No post of mine is complete without a cat picture. These were my patient companions and reliable distractors while I was doing this work above!