Designing an AI for enterprise (complex, task-oriented) conflicts with consumer preferences (personable, engaging). By trying to serve both markets with one model as it pivots to enterprise, OpenAI risks creating a product with a "personality downgrade" that drives away its massive consumer base.

SaaS playbooks for sales, marketing, and success were designed for annual product changes. AI-native products iterating every 30 days require a complete organizational rethink, as old go-to-market motions cannot keep pace with the product's rapid evolution.

Unlike prior tech cycles with a clear direction, the AI wave has a deep divide. SaaS vendors see AI enhancing existing applications, while venture capitalists bet that AI models will subsume and replace the entire SaaS application layer, creating massive disruption.

In the age of AI, 10-15 year old SaaS companies face an existential crisis. To stay relevant, they must be willing to make radical changes to culture and product, even if it threatens existing revenue. The alternative is becoming a legacy player as nimbler startups capture the market.

Established SaaS companies with strong, but not explosive, growth will struggle to raise new venture capital. Their path forward involves running a capital-efficient business while aggressively integrating AI to create new tailwinds, or else face a long, slow grind to a modest exit without further investment.

The conventional wisdom for SaaS companies to find their 'second act' after reaching $100M in revenue is now obsolete. The extreme rate of change in the AI space forces companies to constantly reinvent themselves and refind product-market fit on a quarterly basis to survive.

To transition to AI, leaders must ruthlessly dismantle parts of their existing, money-making codebase that are not competitively differentiating or slow down AI development. This requires overcoming the team's justifiable pride and emotional attachment to legacy systems they built.

To succeed in the AI era, SaaS companies cannot just add AI features. They must undergo a 'brutal' transformation, changing everything from their org chart and GTM strategy to their core metrics and pricing model. This is a non-negotiable, foundational shift.

Sierra CEO Bret Taylor argues that transitioning from per-seat software licensing to value-based AI agents is a business model disruption, not just a technological one. Public companies struggle to navigate this shift as it creates a 'trough of despair' in quarterly earnings, threatening their core revenue before the new model matures.