Snowflake boosted revenue with AI not through internal productivity gains, but by embedding AI capabilities directly into its core analytics product. This made the platform more valuable and easier for customers to use, which in a consumption-based model, directly drove more usage and revenue.

The fundamental shift with generative AI in B2B is selling "work product" or "human labor equivalents," not just software tools. This reframes the value proposition and opens up historically difficult markets, like law firms, that were resistant to buying traditional SaaS products.

Companies like Notion and Datadog are re-accelerating by targeting new, dedicated AI budgets. This is separate from shrinking 'efficiency tool' budgets. Growth comes from solving problems that unlock this specific new spending category, not just adding a minor AI feature.

Hanover Park's CEO argues the era of selling software tools is ending. The next wave of successful B2B companies will be "AI native services" that use agents to deliver concrete business outcomes, fundamentally shifting the model from selling tools to selling guaranteed results.

Most successful SaaS companies weren't built on new core tech, but by packaging existing tech (like databases or CRMs) into solutions for specific industries. AI is no different. The opportunity lies in unbundling a general tool like ChatGPT and rebundling its capabilities into vertical-specific products.

Joe Lonsdale advises established SaaS companies to go on offense with AI. Instead of merely defending their core product, they should build AI agents on top of their platforms to automate customer workflows. This creates new, high-margin revenue streams by helping customers reduce headcount and increase efficiency.

The business model is shifting from selling software to selling outcomes. Instead of creating a tool and inviting users, create pre-trained agents that perform valuable work. Then, invite companies to a workspace where this 'team' of AI employees is ready to start delivering value immediately.

Simply adding a generative AI co-pilot is now table stakes for SaaS companies. The founder argues the next evolution is 'agentic AI' — systems that don't just provide insights but autonomously perform tasks and make decisions for the user, like qualifying and actioning a sales lead.

In a world where AI agents perform tasks, the value of a SaaS product is no longer its user-friendly interface but the robustness of its APIs. The core differentiator becomes the proprietary business logic, security, and data governance embedded within the API layer.