AI enables "software does labor" business models in industries previously deemed too small for specialized software, like dental offices or trial law. By replacing or augmenting specific labor tasks, startups can justify high-value contracts in markets that historically wouldn't pay for traditional SaaS tools.

Previously, the high cost of software development meant products needed to achieve scale to be successful. AI lowers this barrier, making it practical to build custom applications for very small, niche audiences (e.g., a Super Bowl app for 15 family members) that were never financially viable before.

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.

Contrary to the belief that AI will kill most apps, lower development costs will make it profitable to build and maintain software for smaller, niche audiences. This affordability will likely lead to an explosion of specialized apps rather than market consolidation.

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.

AI is drastically reducing software development costs. This makes it economically viable for small teams to build highly-focused applications for niche markets, such as specific skilled trades, that were previously too small to attract venture capital-backed software companies.

The true second-order effect of AI isn't just a single massive solo company. It's a "golden age" of B2B SaaS, where a one-person unicorn will rely on hundreds of other small, hyper-specialized software startups to handle its various functions.

AI is predicted to reduce engineering costs to near-zero, enabling individuals with strong product taste to build, launch, and market SaaS companies alone. The critical skill will shift from coding to user testing and product insight, functions that AI cannot yet fully replace.

AI will decentralize entrepreneurship by enabling solo founders to build software for niche markets. These small markets, often dismissed by VCs, can support highly profitable lifestyle businesses for individuals, creating a new wave of company creation outside the traditional Silicon Valley model.