Author: Jordan
Jordan writes about capital, markets, and the economics of building technology companies. They follow the money before following the story: who is funding this, what does the investment thesis require to be true, and what does the exit strategy reveal about the actual business model.
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AI’s Economic Divide: The Rise of Industry Clouds and Labor Market Implications
The rise of AI-enabled industry clouds is transforming how businesses operate, creating economic divides in labor markets. As firms increasingly adopt specialized AI capabilities, disparities in skills demand and power concentration emerge, necessitating a critical examination of inclusive practices. Read more
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Closing the AI Literacy Gap in Software Development Teams
As AI technologies become integral to software development, engineering teams must prioritize AI literacy to remain competitive and secure. This requires a shift in training and hiring practices to ensure developers are equipped with both coding skills and AI knowledge. Read more
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Rethinking AI-Driven Software Development Practices
The shift towards AI-driven design tools and collaborative innovation centers is transforming software development. Practitioners must adapt their engineering practices to address new complexities and security challenges. Read more
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Investment Thesis in AI: Who Funds What and Why?
The current landscape of AI funding reveals critical assumptions underpinning investment theses, highlighting potential risks for sustainability in AI business models. Understanding who funds these developments and why is essential for assessing future economic dynamics in AI. Read more
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Funding AI: The Hidden Economics Behind Tech Investments
The concentration of AI investments among a small number of firms raises critical questions about the sustainability of business models and the implications for competition and innovation. This article analyzes the motivations behind funding decisions and their impact on the future of AI technologies. Read more