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.

Investors and markets don't care about AI-driven efficiencies in go-to-market or engineering; those are table stakes. The existential question for any software company is how AI disrupts not just *how* you build, but *what* you build for your customers. Failure to reinvent the core product is a death sentence.

When AI competitors emerged, Product Fruits' founder realized their steady growth ("riding a horse") was a path to obsolescence. He adopted a "riding the tiger" mindset: an aggressive, all-in AI rebuild. The only way forward is to keep pushing, because stopping means the new, risky tech will consume you.

Classic software engineering warns against full rewrites due to risk and time ("second-system syndrome"). However, AI's ability to rebuild an entire product in days, not years, makes rewriting a powerful and low-cost tool for correcting over-complicated early versions or flawed core assumptions.

Faced with an "AI mandate," many companies try to force-fit AI onto their current offerings, leading to failure. The correct first step is a fundamental assessment: is this problem even a good candidate for AI, or does the entire product need to be reimagined from the ground up?

For incumbent software companies, surviving the AI era requires more than superficial changes. They must aggressively reimagine their core product with AI—not just add chatbots—and overhaul back-end operations to match the efficiency of AI-native firms. It's a fundamental "adapt or die" moment.

Monday.com's CEO admits their initial AI features were merely "sprinkling AI dust"—superficial additions that didn't change the product's core value. True transformation requires abandoning bolt-on features and undertaking a complete reinvention of the product to be AI-native from the ground up.

The transition to AI is a platform shift potentially larger than mobile. As argued by OpenAI CEO Sam Altman, companies built from the ground up with AI at their core have a fundamental DNA advantage over incumbents who are simply adding AI capabilities to existing products and workflows.