The most successful AI applications like ChatGPT are built ground-up. Incumbents trying to retrofit AI into existing products (e.g., Alexa Plus) are handicapped by their legacy architecture and success, a classic innovator's dilemma. True disruption requires a native approach.

Don't just sprinkle AI features onto your existing product ('AI at the edge'). Transformative companies rethink workflows and shrink their old codebase, making the LLM a core part of the solution. This is about re-architecting the solution from the ground up, not just enhancing it.

MongoDB's CEO argues that AI's disruptive threat to enterprise software is segmented. Companies serving SMBs are most at risk because their products are less sticky and more easily replaced by AI-generated tools. In contrast, vendors serving large enterprises are more protected because "products are always replaceable, platforms are not."

Notion's CEO compares current AI adoption to swapping a water wheel for a steam engine but keeping the factory layout the same. The real gains will come from fundamentally rethinking workflows, meetings, and hierarchies to leverage AI that works 24/7, rather than just layering it onto existing processes.

AI-native companies find more success selling to new businesses or those hitting an inflection point (e.g., outgrowing QuickBooks). Trying to convince established companies to switch from deeply embedded systems like NetSuite is a much harder 'brownfield' battle with a higher cost of acquisition.

Incumbents face the innovator's dilemma; they can't afford to scrap existing infrastructure for AI. Startups can build "AI-native" from a clean sheet, creating a fundamental advantage that legacy players can't replicate by just bolting on features.

The shift to AI creates an opening in every established software category (ERP, CRM, etc.). While incumbents are adding AI features, new AI-native startups have an advantage in winning over net-new, 'greenfield' customers who are choosing their first system of record.

Since 2022, AI has created a pivotal moment where the long-term value of existing software is being questioned by both investors and customers. MongoDB's CEO asserts that in this new stack, only two layers feel certain to endure: the foundational data layer where information is stored and the LLM layer that provides intelligence. Everything in between must now re-prove its value.

The company's key innovation is Humane One, an AI operating system for enterprises. It replaces the fragmented, icon-based world of separate apps for HR, finance, etc. with a unified system. The biggest implementation challenge is not the technology, but shifting the organization's culture and mindset.