For decades, software looked like a moat. Building a complex product took years and that friction kept competitors out. But it was almost always the underlying business dynamics that the software enabled, the network effects it accumulated, the proprietary data it generated, the relationships it locked in. The code was just the hard-to-replicate vessel.

Now AI is collapsing that timeline, stripping away the vessel, and forcing a clearer view of what was actually defensible all along.

If software becomes nearly free to build and AI models become commoditized, where does economic value actually get captured?

Software is no longer a moat

No one can build Chrome in a weekend yet, but the amount of human-years it took to write that code are compressing by Nx or more. AI companies know this, so they’re scrambling to build secondary moats: vertically integrated software platforms on top of their models, and user feedback loops that generate proprietary training data.

Software will probably never be truly “free”, there will always be human product management, design decisions, and coordination involved. But the cost curve is dropping fast enough that software alone can no longer protect a business. The companies that thought they were selling software were often really selling something else. AI makes that distinction impossible to ignore.

Data isn’t the best moat either

As Ilya Sutskever put it: “We’ve achieved peak data and there’ll be no more”, comparing human-generated content to a finite resource like oil.

And even this scarcity might not matter. Synthetic data is proving nearly as good as real data, sometimes better for edge cases. The data moat is eroding faster than most expected.

What moats still exist?

In a world where both AI models and software are commoditized, value gets captured elsewhere

Compute - Physical infrastructure is hard to replicate. In the short run, compute is scarce and the supply chain for creating more is undersupplied. Cloud providers like GCP, Azure, and AWS will have serious moats as long as GPU capacity remains a genuinely scarce resource.

Human relationships - Partnerships, contracts, brand recognition, and social networks are hard to replace even if the underlying software becomes trivial to rebuild.

Capital - Cash in the bank to weather competition and outlast races to the bottom.

Proprietary data - Not scraped or synthesized data, but data that only you can generate: operational data, customer behavior, private records.

Team - Rare talent that competitors can’t easily hire away.

Exclusive rights - Patents, trademarks, copyrights, regulatory licenses.

Network effects - Value that scales with users in ways that are hard to bootstrap from scratch.

The weakest position

Companies with the weakest moats right now are probably pure software companies. SaaS businesses and AI model creators who bet that the software or model itself was the defensible asset. It wasn’t. The question for all of them is: what’s the real moat underneath?

The strongest moats

So what will have the strongest moats in an AI-commoditized world?

Energy and logistics - Companies that can produce and transport energy at scale, with the right land and water rights. AI runs on electricity and cooling; whoever controls those inputs sits at the foundation of the whole stack.

Geography-locked compute - Data centers built next to scarce energy and water sources, where location itself becomes the moat.

Deep relationships - Companies like Meta or ByteDance with billions of users and entrenched network effects. Government contractors locked into long, custom contracts with institutional relationships that take decades to build and are nearly impossible to displace, regardless of what software can do.

The set of things worth building just got a lot bigger. The moats around those things just got a lot smaller.