Contrary to fears of job displacement, Todd McKinnon believes AI will increase the demand for software engineers. While AI will handle more initial code generation, humans will be needed to manage the complexity of maintaining, scaling, and architecting the 10x more software that will be built with these new agentic systems.

As technology made marketing tasks more efficient (e.g., Google Ads), it democratized access, causing a 5x increase in marketing jobs since the 1970s. Box's CEO argues AI will have a similar effect on all knowledge work by lowering costs, which will dramatically increase overall demand for that work.

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.

AI makes tasks cheaper and faster. This increased efficiency doesn't reduce the need for workers; instead, it increases the demand for their work, as companies can now afford to do more of it. This creates a positive feedback loop that may lead to more hiring, not less.

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.

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.

AI tools make software development drastically cheaper. Rather than replacing engineers, this efficiency will likely trigger the Jevons paradox: the unlocked demand for new, more powerful software will skyrocket, increasing the overall need for people who can direct these new capabilities.

AI coding tools democratize development, making simple 'coding' obsolete. However, this expands the amount of software created, which in turn increases the need for sophisticated 'engineering' to manage new layers of complexity and operations. The field gets bigger, not smaller.

Counterintuitively, AI tools that make software engineering more efficient are increasing the demand for engineers. By lowering the cost of development (Jevons Paradox), AI is unlocking latent demand from non-tech industries that previously couldn't afford a large engineering workforce.