As AI and better tools commoditize software creation, traditional technology moats are shrinking. The new defensible advantages are forms of liquidity: aggregated data, marketplace activity, or social interactions. These network effects are harder for competitors to replicate than code or features.

As powerful AI models become cheap and universally accessible, having one is no longer a defensible moat. The real, lasting advantage for a business now comes from assets that a better model can't easily replace: proprietary customer data, deeply integrated user workflows that are difficult to replicate, and long-term client relationships.

Boris Cherny predicts AI will weaken traditional business moats. Switching costs decrease as AI can port systems, and process power is less defensible as AI can replicate complex workflows. However, foundational moats like network effects and scale economies will remain strong or grow in importance.

Unlike mobile or internet shifts that created openings for startups, AI is an "accelerating technology." Large companies can integrate it quickly, closing the competitive window for new entrants much faster than in previous platform shifts. The moat is no longer product execution but customer insight.

As AI makes software development nearly free, traditional engineering moats are disappearing. Businesses must now rely on durable advantages like network effects, economies of scale, brand trust, and defensible IP to survive, becoming "unsloppable."

When any feature can be replicated quickly using AI, the feature set itself is no longer a defensible moat. Sustainable competitive advantage must now be built on harder-to-copy assets like proprietary data, established distribution channels, and strong customer loyalty.

AI favors incumbents more than startups. While everyone builds on similar models, true network effects come from proprietary data and consumer distribution, both of which incumbents own. Startups are left with narrow problems, but high-quality incumbents are moving fast enough to capture these opportunities.

AI doesn't kill all software; it bifurcates the market. Companies with strong moats like distribution, proprietary data, and enterprise lock-in will thrive by integrating AI. However, companies whose only advantage was their software code will be wiped out as AI makes the code itself a commodity. The moat is no longer the software.

Oren Zeev argues against the narrative that AI will kill all incumbents. He believes businesses with operational complexity, deep data moats, and strong distribution are not easily disrupted. These companies are more likely to leverage AI to their advantage, while simpler software companies are at greater risk.