Executive summary

As a leader of an organization, you're probably getting some questions about your AI strategy. Maybe you’ve gotten pressure from your board or investors to add new capabilities. Maybe employees are concerned you’ll fall behind peers who are adding generative AI (GenAI) to their tech stacks.

Over the last few years, large language models (LLMs) have become a layer of intelligence that you can integrate with a diversity of products, one that can reason out responses to complex queries, conduct lengthy conversations using natural language, and generate new material across a wide range of disciplines, from college essays to marketing campaigns to the code running this website.

Looking to get GenAI up and running in your organization? We're here to help! Read on to learn how.

Objective: Get up to speed quickly

The objective of this interactive guide is threefold:

First, we’ll provide the basics of what this technology is and how it works. We’ll give you a primer on where GenAI and LLMs came from, how they’re being used today, and where all this is headed in the future.

Second, we’ll cover the fundamental features and technologies required to add this technology to your offerings. We’ll examine the tools you’ll need, go through build vs. buy considerations, and discuss what kind of training or upskilling your employees might require in order to work with this new technology. You’ll learn about foundation models, vector databases, embedding, and retrieval-augmented generation (RAG). We’ll explain how to optimize your data quality and why a great knowledge base is important for AI. These systems abide by a simple rule—garbage in, garbage out—so you’ll want to ensure you’re feeding them the right stuff.

Last but not least, we’ll dive into the things you can’t forget: safety, privacy, bias, governance, and security. We’ll share our own journey building a GenAI stack and lay out the pros and cons of investing in this area right now. We’ll explore some of the AI initiatives we’ve been working on, as well as the new features we’re bringing to Stack Overflow and Stack Overflow for Teams that will help technologists find answers to their questions more efficiently.

This interactive guide is structured so you can control your own journey (choose your own adventure, if you will). If you’re just getting started, we’ll guide you step-by-step with considerations and explanations that don’t require a deep technical background. If your understanding of GenAI is more advanced, we offer lots of opportunities to dive deeper, exploring conversations with the folks building this technology at the world’s biggest companies and the startups innovating in the space. You can read front to back or choose the sections most interesting to you.

Ready to learn more? Check out the table of contents and dive into the chapters below.

  1. A brief history of AI
  2. Building your GenAI tech stack
  3. Key tools, technologies, and terms
  4. Our AI journey
  5. Building your AI knowledge foundation