CTO Priorities: Intelligence, Demand Inversion, and the New Valuation Metric

Authored by Marcus Daley

At this time last year, I was pessimistic about where the global trajectory on AI was leading humanity. However, as we progressed through 2024, my thinking has evolved, particularly regarding the definition of intelligence and the future of software development.

Recent statements from CEOs at companies like SFDC, Anthropic, and Microsoft, suggest a halt in hiring software engineers in 2025 and those comments align with my predictions of agentic solutions from late 2023/early 2024. However, I now believe their view is overly influenced by the rapidly diminishing limitations of AI and the short-term rewards of the financial markets.

The Definition of Intelligence

• Today's AI: Excels at working with existing knowledge but struggles with out-of-distribution scenarios. The markets reward short-term profits, where knowledge automation fits nicely.

• Tomorrow's AI: True intelligence lies in the ability to succeed in uncertain situations. Uncertainty transforms knowledge into intelligence. Tomorrow, market sentiment will shift more speculative with greater emphasis on the rate of invention.

As AI begins to accelerate the creation of intelligence, we will likely encounter Jevons Paradox:

• Jevons Paradox: Technological improvements increasing efficiency can lead to increased consumption of that resource (see: https://en.wikipedia.org/wiki/Jevons_paradox). Increasing efficiency + increasing the rate of invention will form the perfect paradox.

• The Future Workforce: Employees will become power users of AI agents, dramatically multiplying individual productivity. People will tout their agentic skills on their resumes.

The New Valuation Metric

• The Future of Leadership: The creation of intelligence will require CEOs and their companies to focus on creating new value rather than solely maximizing profit. The key metric will tilt less toward profit and instead to the rate of new value creation, enabled by the force-multiplying effect of AI at extremely low costs – a potential explosion of innovation akin to a Monte Carlo simulation.

Demand Inversion

The primary challenge ahead is demand inversion:

• Demand Inversion: A situation where a rise in price leads to an increase in demand.

In this context, individuals and economies proficient in using AI agents will experience demand inversion. Those resistant to or lacking access to digital or robotic tools will face displacement and further wealth concentration.

Open-source AI models, like DeepSeek R1, can help distribute the necessary digital tools, but they will also further accelerate the push for rapid innovation and genuine value creation. The rate of invention will be the answer to the ultimate question :)

Conclusion

The traditional model of valuing companies based solely on profit maximization is becoming outdated. In an AI-driven world, the rate of invention – fueled by AI agent productivity and accelerated by the dynamics of Jevons Paradox and demand inversion – will be key determinants of market value. Companies that can rapidly innovate and create new value, leveraging the force-multiplying effect of AI, will be the most highly valued.

While the shift towards specialized roles (true full stack) focused on AI integration, system design, and the development of increasingly complex and sophisticated software solutions may seem disruptive, it emphasizes the importance of continuous learning and adaptation for software engineers to remain relevant in an AI-driven world!