The rise of AI services companies like Invisible and Palantir, which build custom on-prem solutions, marks a reversal of the standardized cloud SaaS trend. Enterprises now prioritize proprietary, custom AI applications to gain a competitive edge.

AI is becoming the new UI, allowing users to generate bespoke interfaces for specific workflows on the fly. This fundamentally threatens the core value proposition of many SaaS companies, which is essentially selling a complex UX built on a database. The entire ecosystem will need to adapt.

For decades, buying generalized SaaS was more efficient than building custom software. AI coding agents reverse this. Now, companies can build hyper-specific, more effective tools internally for less cost than a bloated SaaS subscription, because they only need to solve their unique problem.

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.

Frame your product's value not around the underlying AI, but around the premium insight it unlocks. The key is to instantly provide an answer—like a valuation or diagnosis—that previously required significant time, money, or human expertise.

SaaS value lies in its encoded business processes, not its underlying code. AI's primary impact will be forcing SaaS companies to adopt natural language and conversational interfaces to meet new user expectations. The backend complexity remains essential and is not the point of disruption.

Value in the AI stack will concentrate at the infrastructure layer (e.g., chips) and the horizontal application layer. The "middle layer" of vertical SaaS companies, whose value is primarily encoded business logic, is at risk of being commoditized by powerful, general AI agents.

As foundational AI models become commoditized, the key differentiator is shifting from marginal improvements in model capability to superior user experience and productization. Companies that focus on polish, ease of use, and thoughtful integration will win, making product managers the new heroes of the AI race.