Even if your strategy is a ubiquitous AI layer, building your own applications (like an email client) is essential. These dedicated "surfaces" allow you to fully express your vision for an AI-native experience, which is constrained when only building on top of others' products.

Customers are hesitant to trust a black-box AI with critical operations. The winning business model is to sell a complete outcome or service, using AI internally for a massive efficiency advantage while keeping humans in the loop for quality and trust.

To achieve hyper-growth ($40M+ ARR in year one), your product isn't enough. Every internal function—finance, legal, contracting, customer onboarding—must also be AI-native to process deals and deliver value at a velocity that matches sales success.

A truly "AI-native" product isn't one with AI features tacked on. Its core user experience originates from an AI interaction, like a natural language prompt that generates a structured output. The product is fundamentally built around the capabilities of the underlying models, making AI the primary value driver.

The traditional SaaS method of asking customers what they want doesn't work for AI because customers can't imagine what's possible with the technology's "jagged" capabilities. Instead, teams must start with a deep, technology-first understanding of the models and then map that back to customer problems.

Point-solution SaaS products are at a massive disadvantage in the age of AI because they lack the broad, integrated dataset needed to power effective features. Bundled platforms that 'own the mine' of data are best positioned to win, as AI can perform magic when it has access to a rich, semantic data layer.

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.

An AI-native service provider goes directly to the end customer, bypassing intermediaries. They offer a superior result (e.g., faster, cheaper cybersecurity) at a lower price, making the switch an easy decision by solving the entire problem.

Traditional SaaS was built for siloed human departments (e.g., sales, marketing, support). AI enables a single agent to manage the entire customer journey, forcing these distinct software categories to converge into unified platforms.