The Disruptor’s Paradox: How Great Innovators Become Incrementalists…and What to Do About It

TL;DR: Every great disruptor eventually becomes the thing it once set out to destroy.

We celebrate the iconoclasts. We love those who break the rules, defy incumbents, and reshape industries. But give them time, and most suffer the same fate as those they displaced: innovation slows, agility decays, and relevance fades.

It’s tempting to blame this on leadership, vision drift, or a culture that got soft. But this isn’t a failure of will or intelligence: it’s what I call the Disruptor’s Paradox:

The very mechanisms that fuel early innovation, like speed, clarity, and risk tolerance, eventually harden into systems of control. Those systems, built to win the first game, are rarely designed to win the second.

We’ve seen this movie before. Clay Christensen gave us The Innovator’s Dilemma to explain why incumbents miss the future, and then Cory Doctorow gave us “Enshittification” to describe the rot that sets in at the end.

In my own previous piece, The Incumbent’s Dilemma, I detailed the “5 Cs” (like Comfort and Controls) that structurally prevent companies from acting even when they see the threat.

But neither fully explains the specific mechanics of how a company that knows how to disrupt itself slowly loses the ability to do so.

They don’t stop innovating because they forget how, the issue is the organization gets “heavier,” and gets better and better at playing the wrong game: risk management over risk-taking. Data over intuition. Optimization over reinvention.

The Disruptor’s Cycle Curve

This rise and fall is a structural pattern I call the Disruptor’s Cycle Curve. It is a five-phase arc that explains how an initial edge becomes inertia.

1. Disrupt: This is the insurgent phase. A new entrant attacks a neglected “job-to-be-done” with speed and clarity. They move with urgency and vision. Survival is the only KPI.
2. Ascend: Product-market fit takes hold. Growth compounds. The market notices. Use cases expand to fill the early void. But even now, “big company” thinking is the enemy.
3. Optimize: The business now needs to operationalize to scale. Margins matter. Predictability is prized to ensure dependencies align, and quarterly projections can be met. Process becomes the product and efficiency overtakes exploration. Innovation becomes incremental. Bold bets die in planning because the organization is now designed to protect the core, not expand it.
4. Overfit (The Incumbent’s Cliff): This is the inflection point. The system that once enabled growth now suppresses it. Roadmaps get longer and more intricate. Decks improve while momentum slows. Builders start optimizing for optics, not impact. Dashboards are green, while the product worsens: “enshittification” begins as value extraction replaces value creation.
5. Decline or Renewal: Here, the path bifurcates. In decline, to keep margins reorgs, cost cutting, set in, while M&A becomes the path to innovation, and the machine eats itself. Alternatively, renewal is when a structural reboot occurs, and there needs to be a return to “Founder Mode” to generate new ideas and make new bets.

The Mechanics of Decay

Why does this happen? Most leaders don’t realize they are in the “Overfit” phase until it is too late because the dashboard still looks green. Decay isn’t a failure of leadership; it is a system doing exactly what it was designed to do.

There are four invisible mechanics that push companies off the cliff.

1. Performance Management Theater: What starts as alignment becomes spreadsheet theater. OKRs and scoring systems are supposed to drive focus, but over time, they become a shell game. Managers begin to optimize for optics. Metrics become targets (Goodhart’s Law), and judgment atrophies. Soon, you are rewarding the best scorekeepers, not the best builders.
2. Org Architecture Creep: Early organizations are modular; teams move fast and break things. But as you scale, everything gets stitched together into shared infrastructure and centralized platforms. Eventually, nothing is isolated. Teams stop asking “What should we build?” and start asking “What can we build without breaking anything?”. The architecture becomes an invisible veto power.
3. Expected Lifetime Effort (ELE): We often look at churn, but we miss the leading indicator: Expected Lifetime Effort. ELE = Setup friction + (Ongoing effort x # of uses). Even when your product is “sticky,” your users might be getting tired. Optimization often adds complexity. As friction creeps up, loyalty creeps down. Users stay out of habit or lack of choice—until a competitor offers a lower-friction alternative, and then the collapse is sudden.
4. Sunk Cost Commitment: The longer you invest in a system—people, processes, infrastructure—the harder it is to walk away. You aren’t just protecting revenue; you are protecting your identity. This is why companies defend legacy “sacred cows” long after the market has moved on.

Case Study: The Trap of Optimization

We see the “Overfit” phase play out in real-time with some of the world’s most beloved brands.

Disney Parks: A textbook disruptor that revolutionized experience. But in the “Optimize” phase, they focused on yield management over guest magic. They introduced Genie+ and complex tiering to extract maximum revenue per head. The result? They optimized the dashboard perfectly, and in doing so, erased the product’s soul. This Trust Thermocline, is the point where loyal users suddenly decide the effort is no longer worth the reward.

ESPN: Once the ultimate disruptor of sports media with SportsCenter, ESPN entered the “Overfit” phase by obsessing over engagement metrics. Analytics showed that “debate” drove clicks, so they doubled down on have, clickbait, They optimized for outrage vs. insight and became the ultimate ads delivery vehicle than produce real content. While short-term engagement spiked, they burned the trust that made them the “go to” authority in sports.

Once you use this lens, you’ll look everywhere: such as B2B SaaS companies turning into the ERP predecessors, or movies studios, or content creators, and even celebrity chefs. This model holds time and time again.

Escaping the Trap: Designing for Reinvention

You cannot optimize your way out of decay. You have to design for reinvention.

1. Seed Second Curves Early: The best time to explore new growth curves is before you need them. But most wait until decline is obvious. You must incubate edge bets before the cliff, protect them from core KPIs, and treat them like a venture portfolio.
2. Rewire Incentives: Your organization doesn’t lack innovation; it lacks permission. Kill the KPI theater. Reward ambiguous wins and judgment, not just output. Bet on your best builders and free them from managing optics.
3. Embrace Product Mitosis: Most roadmaps are bloated because teams are afraid to break things apart. Let products split. Let teams specialize. Modular products lead to modular teams, which leads to faster evolution.
4. Incentivize Self-Cannibalization: If you don’t disrupt your golden goose, someone else will. Make it safe to kill sacred cows. Run shadow teams tasked with “what would kill us?”—and then let them build it.
5. Re-enter Founder Mode: This isn’t about hustle; it’s about org design. Fewer layers. Faster loops. Capital allocation that moves with conviction, not consensus.

Renewal isn’t a vibe. It’s a system built for clarity, speed, and the courage to bet again.

The Real Competitor Is Entropy

The most dangerous competitor isn’t the upstart. It is your own drift. Most companies don’t die from a lack of ideas. They die from organizational entropy—systems built for control & clarity, and reward motion over meaning. Disruption isn’t a one-time event. It’s a cycle. The real moat isn’t your brand, your cash, or your product. The real moat is your capacity to reinvent.

Appendix: The Canon

For those who want to dig deeper, these are the foundational texts that informed this essay.

• The Innovator’s Dilemma (Clayton Christensen): The blueprint for why incumbents miss disruption. Essential, but focuses on the “before”.
• Enshittification (Cory Doctorow): A sharp diagnosis of how platforms degrade from “user-first” to “shareholder-only”.
• The Trust Thermocline: A concept borrowed from oceanography describing how trust erodes slowly, then collapses suddenly.
• Goodhart’s Law: “When a measure becomes a target, it ceases to be a good measure.” The root cause of most KPI theater.
• The Incumbent’s Dilemma: my own post describing how organizations can’t get out of their own way even when they know what to do.
• Founder Mode: Paul Graham’s seminal essay describing when founders and leaders take hands-on direct leadership, rather than simply “managing”.