Contrary to fears of job replacement, AI coding systems expand what software can achieve, fueling a surge in project complexity and ambition. This trend increases the overall volume of code and the need for high-level human oversight, resulting in continued growth for developer roles rather than a reduction.

Increased developer productivity from AI won't lead to fewer jobs. Instead, it mirrors the Jevons paradox seen with electricity: as building software becomes cheaper and faster, the demand for it will dramatically increase. This boosts investment in new projects and ultimately grows the entire software engineering industry.

Just as YouTube lowered media distribution costs, AI is lowering software development costs. This could shift the SaaS market away from large, one-size-fits-all platforms toward a model where small, elite teams deliver highly customized software solutions directly to enterprise clients.

While AI can improve existing software categories, the most significant opportunity lies in creating new applications that automate tasks previously performed by humans. This 'software eating labor' market is substantially larger than the traditional SaaS market, representing a massive greenfield opportunity for startups.

AI lowers the economic bar for building software, increasing the total market for development. Companies will need more high-leverage engineers to compete, creating a schism between those who adopt AI tools and those who fall behind and become obsolete.

Instead of fearing job loss, focus on skills in industries with elastic demand. When AI makes workers 10x more productive in these fields (e.g., software), the market will demand 100x more output, increasing the need for skilled humans who can leverage AI.

The argument that AI will eliminate software jobs by making coding easy overlooks a key reality: most existing software is buggy and frustrating. The demand for better, more reliable products is practically infinite, suggesting AI will augment developer productivity to meet this demand rather than replace developers wholesale.

Automating coding tasks won't eliminate engineers. Similar to the shift from assembly to higher-level languages, AI tools increase output potential, leading to an explosion in demand for software and the builders who can leverage these powerful new platforms.

Jevons Paradox states that as a resource becomes more efficient, consumption increases. Applied to AI, making software development faster won't eliminate developer jobs. Instead, it will create a surge in demand by enabling new applications like internal tools and personal apps.