Prologue

Companies don't buy software.

Companies buy productivity.

In this series I examine the evolution of knowledge work and its central role in business today. It’s clear that efficiency is the common thread tying these changes together. Software may have "eaten the world," but what it truly did was amplify our ability to innovate, automate, and scale. This series delves into the "why" and "how" of growth in business, exploring the profound connections between traditional business imperatives and the technological tools that make them possible.

Companies don’t buy software for its own sake; companies buy the productivity and efficiency software enables, which in turn fuels their ability to grow and compete. Companies don’t merely pursue growth because it’s expected; they do so to ensure long-term survival, adapt to shifting market conditions, and secure competitive advantages. This relentless focus on growth underpins not only how businesses operate but also how they adopt and leverage technology to meet these goals. Understanding this dynamic is crucial, especially in today’s rapidly transforming knowledge-driven economy.

This eBook is meant for the business crowd; I talk about how to think about technology investment in this series. The eBook is organized into 3 logical parts:

1. Part 1: "Framing Your Technology Investment Strategy"
2. Part 2: "Building Knowledge Work Platforms"
3. Part 3: "The Evolution of Knowledge Work"

This eBook presents a structured analysis of technology investment and how it affects the line of business. It is set distintively aside from the Patterson Consulting main technical blog because it has a different audience. This eBook is meant for the C-suite reader and is written from a business perspective.

This means I'm writing about how to think about where to invest in technology and artificial intelligence basesd on the size and industry of your organization. I'm also writing about how to think about the structure of knowledge work and data platforms, and how to compose them from all the different components available. Finally I address where knowledge work is headed with artificial intelligence and how to realistically evaluate what artificial intelligence systems are beneficial to your organization.

In this series I draw insights from over 20 years of industry experience. It distills key learnings from direct customer engagements, advisory roles with startups, and participation in market analysis conferences, where industry trends and competitive landscapes were debated with investors. Additionally, the content reflects due diligence conducted for venture capital firms on market segments and specific companies, as well as commissioned research and analysis for enterprise clients. This collective expertise provides a strategic perspective on the evolution of software markets and platform dynamics, offering valuable guidance for decision-makers navigating digital transformation.

The Evolution of Information Processing

Artificial intelligence has undergone multiple cycles of rapid advancement and stagnation, with the current wave—driven by large language models and AI agents—bringing both opportunities and challenges for executives. Many organizations struggle to contextualize the value of these technologies within their strategic priorities.

Artificial intelligence is increasingly framed as a driver of future cash flows, significantly influencing company valuations. However, the challenge remains in determining how to generate sustainable financial returns from AI investments. Recent market reactions, such as the sharp decline in technology stock valuations following the emergence of cost-efficient AI models, highlight the uncertainty surrounding AI’s economic impact. Investors and executives alike are grappling with how AI-driven efficiencies translate into competitive advantages and long-term profitability. This book examines AI not just as a technological breakthrough but as a fundamental lever for cost efficiency and business value creation, offering a strategic lens for executives to assess its real financial implications.

Knowledge work has been around for 5000 years, since the dawn of written symbols. In the last 100 years, structural transformation saw much of the written log data digitized into files, spreadsheets, and databases. In the last 50 years we've seen the advent of information processing radically change such that advantages in knowledge work became centered on technology investment and implementation.

In 2018 I wrote an Appendix chapter to our O'Reilly "Deep Learning" book "What is Artificial Intelligence?" I explored the themes that were concrete in different implementations of machine learning and deep learning, and also outlined the limits of those methods' abilities.

In 2023 I wrote about large language models and how they had the potential to transform information processing in the eBook "Introduction to Large Language Models". As I've had discussions with CEOs, COOs, and investors, there has been a consistent thread of "how are artificial intelligence and large language models new and different?" In this series, I make the argument that artificial intelligence and large language models are just the continuing evolution of information processing and knowledge work.

This online eBook is a continuation of the dialog I've had on the themes of real applications of artificial intelligence and how to think about your investment in associated technologies. It also provides the framing to understand how to evaluate any agent, platform, or tool in terms of how productive it makes your application, team, or organization.

Framing your Technology and Artificial Intelligence Investment

This series seeks to cut through the noise, providing a structured framework for evaluating technology investments. By examining the historical trajectory of tools that have enhanced productivity for over 5,000 years, this book explores how modern information technology aligns with the changing nature of knowledge work.

The central themes of Part 1 of this eBook are::

• Companies seek productivity and only invest in tools as a method to get it
• Knowledge work heavy companies need to process large amounts of information to realize goals and revenue
• There are only 2 ways to increase productivity in organizations: 1.) accelerate tasks, 2.) improve team coordination
• If we choose our tools poorly, productivity suffers, and we fall off the pace in this evolutionary race

Part 1 builds on those core themes to provide a structured approach to evaluating new technologies based on their tangible effects on business operations, ensuring that companies remain focused on the "why" behind their technology decisions.

This series focuses on how the line of business engages in knowledge work, and how technology is used to effciently transform information that creates value, increases growth, and makes cash flow more efficient. With that being said, let's dig into Why Does a Company Need to Grow?"

I've enjoyed writing this series and I hope you'll enjoy reading it and finding some value in understanding how technology enables growth and improves your core business. And just remember, technology is "mostly harmless" to your business — until it isn't.