“Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!”
This quote, spoken by the Red Queen in Lewis Carroll’s Through the Looking-Glass (1871), became one of the most influential metaphors in evolutionary biology—and increasingly, in technology.
Origins: From Victorian Nonsense to Scientific Theory
Lewis Carroll (Charles Dodgson) was a mathematics lecturer at Oxford when he wrote Through the Looking-Glass. The Red Queen scene depicts Alice running hand-in-hand with the chess piece queen across a landscape that moves beneath them. Despite exhausting effort, they remain in the same spot.
Carroll intended absurdist humor. A century later, evolutionary biologist Leigh Van Valen saw something else: a fundamental principle of competitive systems.
Van Valen’s 1973 Paper
In 1973, Van Valen published “A New Evolutionary Law” in Evolutionary Theory. The paper analyzed extinction data across thousands of species and made a counterintuitive observation: the probability of extinction remains roughly constant regardless of how long a species has existed.
This contradicted the intuitive assumption that older species, having survived longer, should be more “fit” and thus more extinction-resistant. Van Valen’s data showed otherwise—a lineage that had survived for 10 million years had approximately the same extinction probability as one that had existed for 1 million years.
Van Valen proposed an explanation: species don’t compete against a static environment. They compete against other evolving species. As prey evolves better defenses, predators must evolve better hunting strategies. As hosts develop immune responses, parasites must evolve new attack vectors. Evolution is a zero-sum arms race where running is required simply to maintain relative position.
He named this the Red Queen hypothesis, after Carroll’s character.
The Red Queen in Information Technology
The Red Queen principle extends beyond biology. Any competitive system with adaptive agents exhibits similar dynamics. Information technology provides some of the clearest examples.
Software Development: The Technical Debt Treadmill
Software systems exist in an environment of continuous change. Dependencies update. Platforms evolve. Security vulnerabilities are discovered. User expectations increase. Competitors release new features.
A codebase that remains static doesn’t stay the same—it degrades. This is the Red Queen in action.
Consider a web application built in 2020:
- Framework dependencies have released multiple major versions with breaking changes
- Security patches require updates that may break existing functionality
- Browser APIs have changed, potentially breaking features
- User expectations have shifted based on competitor innovations
- Infrastructure (cloud platforms, container orchestration) has evolved
The application hasn’t changed, but its relative fitness has decreased. Without continuous adaptation, it becomes legacy software—functional but increasingly expensive to maintain and extend.
This explains why technical debt compounds. Deferred maintenance doesn’t just accumulate—it accelerates. Each postponed update makes the next update harder. The environment continues evolving while the system stands still.
Studies in IT:
Lehman’s Laws of Software Evolution (1974-1996): Manny Lehman studied IBM OS/360 and other large systems, formulating laws including “Continuing Change”—a system must be continually adapted or it becomes progressively less satisfactory.
Eick et al. (2001): Analyzed 15 years of change data from a 100-million-line telecommunications system, demonstrating that code decay is measurable and follows predictable patterns when maintenance is deferred.
Cybersecurity: Perpetual Coevolution
Cybersecurity represents the clearest IT analog to biological host-parasite dynamics. Attackers and defenders are locked in continuous coevolution.
The historical progression demonstrates Red Queen dynamics:
| Defense Innovation | Attacker Adaptation |
|---|---|
| Firewalls (1988) | Port tunneling, application-layer attacks |
| Signature-based antivirus (1990s) | Polymorphic malware, metamorphic code |
| Intrusion Detection Systems | Evasion techniques, encrypted C2 |
| Machine learning detection | Adversarial examples, model poisoning |
| Zero Trust Architecture | Identity-based attacks, supply chain compromise |
Each defensive innovation creates selective pressure for offensive innovation. Each offensive innovation demands new defenses. Neither side achieves permanent advantage.
Research evidence:
Anderson (2001): “Why Information Security is Hard” argued that security failures stem partly from economic incentives that don’t favor adequate defense investment—a Red Queen interpretation.
Herley & Florêncio (2010): Showed that attackers rationally adapt strategies based on defender responses, creating evolutionary dynamics similar to biological systems.
MITRE ATT&CK Framework: Documents the continuous evolution of attack techniques, with regular additions reflecting attacker adaptation to defensive improvements.
The implication: security is not a problem to be solved but a condition to be managed. Organizations that invest in adaptive security capabilities (threat intelligence, incident response, continuous monitoring) outperform those seeking static “secure” states.
Infrastructure: The Platform Treadmill
IT infrastructure exhibits Red Queen dynamics at the platform level. Consider compute infrastructure evolution:
- Physical servers → Virtual machines → Containers → Serverless
- On-premises → Colocation → Public cloud → Multi-cloud → Edge
- Manual deployment → Scripts → Configuration management → Infrastructure as Code → GitOps
Organizations that don’t continuously migrate face increasing costs:
- Talent scarcity: Fewer engineers know legacy platforms
- Vendor support: Older platforms lose support and security updates
- Integration friction: Modern tools assume modern platforms
- Competitive disadvantage: Newer platforms enable capabilities legacy systems can’t match
Standing still isn’t standing still—it’s falling behind.
Case study: A 2019 McKinsey analysis found that companies with “legacy technology debt” (systems older than 10 years comprising >50% of infrastructure) spent 60-80% of IT budgets on maintenance versus 20-40% for companies with modern stacks. The Red Queen claims most of the budget.
Implications for IT Organizations
Understanding the Red Queen reframes several IT management questions.
1. Maintenance Is Not Optional
Maintenance isn’t discretionary spending—it’s survival expenditure. Organizations that minimize maintenance budgets aren’t saving money; they’re accumulating extinction risk.
2. Modernization Has Declining ROI When Delayed
Deferred modernization costs more than timely modernization. The gap between the system and its environment widens continuously. Waiting for the “right time” to modernize is usually suboptimal.
3. Security Requires Continuous Investment
No security investment achieves permanent protection. Security budgets must reflect ongoing operational expenses, not one-time capital expenditures.
4. Technical Decisions Should Optimize for Adaptability
Given that change is inevitable, systems should be designed for change. Modularity, loose coupling, automated testing, and deployment automation all reduce the cost of the continuous adaptation the Red Queen demands.
5. Skills Require Continuous Development
Continuous learning isn’t career advancement—it’s career maintenance.
Conclusion
Van Valen’s Red Queen hypothesis explains a fundamental dynamic: in competitive systems, adaptation is required merely to maintain relative position. Biological evidence supports this principle across species and timescales.
Information technology exhibits the same dynamic. Software degrades. Security defenses are outpaced. Infrastructure becomes obsolete. Models decay. The environment continuously evolves, and systems must evolve with it or fall behind.
This isn’t a problem to solve—it’s a condition to understand and manage. Organizations and individuals that accept the Red Queen’s race and build for continuous adaptation outperform those seeking stable endpoints.
Carroll’s Red Queen delivered her observation as absurdist paradox. Van Valen recognized it as scientific principle. For IT professionals, it’s operational reality.
The race has no finish line. Run accordingly.