Previously, building bespoke software for niche internal problems was too expensive. AI agents dramatically lower this cost, allowing companies to create custom-fit solutions for 99% of their problems, ending the era of contorting workflows to fit generic, off-the-shelf tools.

Applying Jevons Paradox, as AI makes code (the "digital brick") cheaper and easier to produce, it doesn't reduce the need for builders. Instead, it unlocks previously uneconomical or overly complex projects, thereby increasing the overall demand for software engineers to build more ambitious things.

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 created more jobs than television lost, AI will lower the cost of software creation so dramatically that millions of new, highly specialized SaaS businesses will emerge. These new companies can be viable with as few as 500 customers.

For decades, buying generalized SaaS was more efficient than building custom software. AI coding agents reverse this. Now, companies can build hyper-specific, more effective tools internally for less cost than a bloated SaaS subscription, because they only need to solve their unique problem.

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.

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.

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.

AI may drastically lower the cost of software engineering, threatening the dominant SaaS model by enabling companies to affordably build bespoke in-house software, mirroring the current market dynamics in China.