In the summer of 2011, Marc Andreessen published a seminal essay in the Wall Street Journal that defined the next decade of technology and business: “Why Software Is Eating the World.” His argument was as elegant as it was prophetic. He posited that we were in the middle of a fundamental economic shift, where software companies were poised to invade and overturn established industry structures. This wasn’t a cyclical tech bubble, he argued, but a tectonic change in how businesses are built and operated. Nearly every industry was becoming a software industry, and those that failed to adapt would be “eaten.”

He was right. Software did eat the world. We watched as Netflix, a software company, devoured Blockbuster. We saw Amazon, a software company with warehouses attached, consume traditional retail. The arc was clear: build a software-centric model and disrupt the incumbents.

That essay landed with particular force for me. My second daughter Brooklyn had just been born, and inspired by the dawn of the mobile era, I had quit my job to launch an augmented reality startup. It was a time of immense learning and, as my wife Sarah loves to remind me, questionable timing. We were building on the new wave, combining sensors on the new iPhones with marketing and gaming. While the startup ultimately didn’t go the distance, the experience was invaluable. It taught me about the immense weight of the word “disruption” and the grit required to survive it—whether you’re the one disrupting or the one being disrupted, both are incredibly difficult.

For over a decade, Andreessen’s thesis was the undisputed law of the digital jungle. But a new, apex predator has emerged. The cycle of disruption has accelerated to a dizzying pace, and in a deeply meta twist, the disruptors from the past two decades are now the ones being disrupted.

AI is now eating the software that is eating the world.

What Disruption Really Means

Andreessen’s essay heralded a wave of software-driven change that felt unstoppable. But what does it actually feel like to be on the receiving end of that disruption? It’s not just about a new competitor; it’s about the ground shifting beneath your feet.

1. Loss of Control Over the Value Chain: Disruptors rewire how value is delivered—removing steps, middlemen, or entire business models before you even notice.
2. Customer Expectations Shift Overnight: When a new player offers instant, personalized, cheaper, or more delightful experiences, your “good enough” becomes “not even close.”
3. Margin Compression Becomes Existential: Disruptive technologies often enable radically lower cost structures. Software doesn’t sleep, unionize, or take vacations. Your 20% margin looks quaint next to their 80%.
4. Your Competitive Moat Turns Into a Puddle: Scale, legacy systems, and brand used to be strengths. But disruption turns those into anchors, slowing adaptation while nimble upstarts sprint past.
5. Innovation Moves Outside the Building: Disruption often comes from adjacent industries or unexpected entrants. Amazon didn’t ask bookstores for permission; OpenAI didn’t wait for Google to modernize.
6. Talent Starts Leaving for the Cool Kids: The best engineers, designers, and product thinkers want to build the future, not maintain the past. When you’re being disrupted, your best people become a leading indicator of decline.
7. It Feels Like a Tech Problem, But It’s Actually a Culture Problem: Many incumbents respond by buying new software or hiring consultants. But the real challenge is rewiring how they think, decide, and act.
8. You’re Not Competing With Companies—You’re Competing With Capabilities: AI, APIs, open-source, no-code… disruptive tools are making individuals and small teams exponentially more powerful.

The Disruptors Disrupted: Modern Examples

Andreessen gave us the classic examples: Blockbuster falling to Netflix, traditional retail to Amazon, Kodak to digital photos. But the most fascinating part of this new wave is seeing the disruptors of that era facing their own existential threats.

Google vs. ChatGPT: The Search for Answers

Google built an empire on software that indexed the world’s information and presented it as ten blue links. SEO became the science of ranking on that list. But AI is eating that model. While Google still dominates the raw volume of search, a significant behavioral shift is happening faster than anyone predicted.

According to a recent Wall Street Journal article, AI-powered search is growing more quickly than expected, with traffic to leading AI chatbots like ChatGPT and Perplexity AI surging. One analytics firm, Similarweb, noted that combined traffic to the top 10 AI chatbots grew 34% in the first part of this year alone. This isn’t just a niche trend; it’s a mainstream migration for certain types of queries. Users are flocking to conversational AI for complex, informational tasks—research, brainstorming, coding help, and problem-solving. We see real-world examples of this constantly. A user on Quora recounted struggling to find a half-remembered book using Google; ChatGPT found it instantly from a vague, partially incorrect description. This is a fundamentally new type of search—one based on context and conversation, not just keywords. The game is shifting from Search Engine Optimization (SEO) to Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO). Users no longer just want a list of links to search through; they want the answer.

Uber vs. Waymo: The End of the Driver

Uber used software to disrupt the taxi industry by creating a massive, efficient marketplace for drivers. Their former CEO pushed hard into autonomous driving, recognizing the existential threat. But in a classic innovator’s dilemma, the new leadership divested from that costly, long-term bet to focus on near-term profitability. Now, companies like Waymo and Tesla are rolling out robotaxi services that threaten to eat Uber’s core business model by removing the driver—and their associated costs—entirely.

The IDE vs. AI: The Changing Nature of Code

The very process of building software is being consumed. For decades, developers have relied on Integrated Development Environments (IDEs) like Microsoft’s Visual Studio or JetBrains’ IntelliJ IDEA. These were the definitive software-building tools. Now, AI-native environments like Cursor and Replit are upending that. They don’t just help you write code; they write it with you and for you.

This has profound implications. What happens when the cost to build software approaches zero?

• Explosion in Software Supply: Software is no longer a scarce, expensive resource—it becomes ubiquitous infrastructure.
• Margins Collapse for Custom Development: Dev agencies, especially those competing on cost, face commoditization unless they move up the value chain to strategy and architecture.
• Shift from “Build” to “Compose”: Software creation becomes more about orchestration and configuration than hard engineering.
• Rise of Citizen Developers: Domain expertise becomes more valuable than knowledge of syntax.
• Incumbent Software Vendors Get Eaten: Legacy vendors must reinvent themselves or be disrupted out of existence.
• Regulation Struggles to Keep Up: Governance models must evolve—fast.
• Software Becomes Embedded Everywhere: The world becomes hyper-personalized and hyper-automated.
• Engineering Roles Evolve: The “10x engineer” becomes the “10x AI collaborator.”
• Economic Leverage Shifts: Distribution, branding, and user insight become more valuable than the underlying code.
• Everything Speeds Up: Strategic agility becomes the only true competitive advantage.

The Crumbling Moats of Enterprise Software

Every traditional enterprise software vendor is seeing their moats dry up. For years, the high cost of replacement was a powerful defense. But that changes as monolithic platforms give way to a diverse ecosystem of best-of-breed SaaS players. Data is becoming more accessible through APIs, and workflows are easier to replace. Additionally, companies are getting wiser to the enterprise sales games. Just because a vendor bought a company doesn’t mean its technology is well-integrated into the platform. We will see the emergence of AI-native enterprise platforms that are built from the ground up to automate, predict, and advise—making their predecessors look like relics.

The Existential Question for Every Company

In 2011, Andreessen argued that every company needed to become a software company to survive. In 2025, the stakes are even higher. What happens to companies—even the software-savvy ones—that don’t evolve into AI-native organizations?

The bottom line is they risk becoming irrelevant, uncompetitive, or extinct. That isn’t a threat; it’s the emerging reality.

• They get outpaced by faster, cheaper, smarter rivals.
• Innovation freezes while bureaucracy expands.
• Knowledge work gets bottlenecked in human siloes.
• Margins shrink as defensibility moats evaporate.
• Top talent leaves for companies where AI is an amplifier, not a threat.
• Customers expect magic, but they deliver forms and call centers.
• Legacy infrastructure becomes an existential debt.
• Strategy becomes guesswork without the real-time data fabric to train and validate AI.

The imperative has evolved. In 2011, the call was to become a software company. Today, every company must become an AI company. This isn’t about buying a few AI tools or launching a chatbot. It’s about fundamentally re-architecting the business around data, intelligence, and automation. It means fostering a culture that thinks in terms of models, probabilities, and feedback loops, and embedding intelligent capabilities into the core of every product, service, and process.

Why Now? The Perfect Storm for Disruption

This isn’t happening in a vacuum. A confluence of factors has created a perfect storm for this AI-driven disruption. As I explored in my previous posts on Accelerating Returns and the Stochastic Era, we’ve hit a critical inflection point.

1. Foundation Models Changed the Game: General-purpose models like GPT can now write, debug, and refactor software, crossing a critical capability threshold.
2. OpenAI (and others) Made It Accessible: The interface to intelligence is now an API call, not a research lab.
3. Software Was Ripe for Disruption: Ironically, much of the software world had become bloated, slow, and ripe for a leaner, smarter alternative.
4. Cheap Cloud + Ubiquitous GPUs = Acceleration: The hardware finally caught up with the ambition.
5. We Finally Have Enough Training Data: The internet created the massive corpus of code, text, and images needed to train these models.
6. Human-Machine Collaboration Just Got Real: The technology is not just smart—it’s usable, amplifying human potential across every role.
7. Software Economics Just Collapsed: When AI can write the code, the cost to create software plummets, and the speed to ship skyrockets.

The Great Leapfrog Moment

One of the wildest things about this era? It’s a leapfrog moment. You don’t need to be the biggest, richest, or most established player anymore—you just need to be the fastest learner.

A scrappy team with a bold vision can outmaneuver giants. The stack is flatter, the tools are open, and the pace of change is brutal. Where you started matters less than how fast you move. This isn’t just for startups. Older companies can leapfrog, too. In fact, they might be in the best position—if they’re willing to change. They have the customers, the data, the brand, and the operational knowledge. What they often lack is urgency and imagination.

The age of the “5-year digital roadmap” is over. The game now is a chaotic, high-stakes parkour race.

Conclusion

In his 2011 essay, Marc Andreessen famously wrote that he was optimistic about the future growth of the economy, predicting it would be driven by these new software-based disruptors. He encouraged every company to embrace this change, to become a software company.

Today, I am also incredibly optimistic, but for a different reason. We are witnessing a second, more profound wave of disruption that is unlocking human potential on an unprecedented scale. The ability to create, to solve problems, and to build is being democratized by AI. Companies that embrace this new reality—that become AI-native at their core—will not only survive but will define the next era of innovation and value creation.

More and more major businesses and industries are being run on artificial intelligence and delivered as intelligent, automated services. The smart ones will be AI-first. The rest will be dinner.