While high capex is often seen as a negative, for giants like Alphabet and Microsoft, it functions as a powerful moat in the AI race. The sheer scale of spending—tens of billions annually—is something most companies cannot afford, effectively limiting the field of viable competitors.

Unlike traditional SaaS where a bootstrapped company could eventually catch up to funded rivals, the AI landscape is different. The high, ongoing cost of talent and compute means an early capital advantage becomes a permanent, widening moat, making it nearly impossible for capital-light players to compete.

A long-held software engineering law, the 'mythical man-month,' stated that adding money or people to a project wouldn't speed it up. AI has changed this fundamental rule. Elon Musk's xAI proved you can now 'throw money at the problem' to rapidly catch up on a technological lead.

For 50 years, adding engineers didn't speed up software development, giving startups a defensible head start. AI changes this. With proprietary data and massive GPU resources, large incumbents can now 'throw money at the problem' to close gaps quickly, eroding a first-mover advantage.

Major tech companies are locked in a massive spending war on AI infrastructure and talent. This isn't because they know how they'll achieve ROI; it's because they know the surest way to lose is to stop spending and fall behind their competitors.

In the AI arms race, a $10 billion investment from a trillion-dollar company is seen as table stakes. This sum is framed as the cost to secure a handful of top engineers, highlighting the massive decoupling of capital from traditional value perception in the tech industry.

While AI makes product development cheaper, the most promising AI startups raise more capital, not less. This is driven by high ongoing costs from using the latest models and investors' desire to pour capital into potential category winners to secure market dominance quickly.

The long-held belief from Fred Brooks' 'Mythical Man-Month'—that adding engineers slows projects—is now obsolete. With sufficient capital for GPUs and data, companies can compress years of software development into weeks, fundamentally changing competitive dynamics and making capital a primary weapon again.

Ben Horowitz argues that AI fundamentally changes a core tenet of startups. Previously, a small, fast team had a durable advantage against incumbents. Now, competitors with massive capital for data and GPUs, like Elon Musk's xAI, can catch up almost instantly, making moats less secure.