The piece dives into the evolving role of legacy SaaS systems and the impact of AI agents on software workflows. It highlights how traditional systems of record, like Salesforce and NetSuite, serve as organized repositories where users gather information and execute tasks. These systems often have rigid workflows that require predefined paths and error handling, making them less adaptable. As the SaaS market has matured, integrating multiple systems typically involves using integration platforms like Workato or Zapier, which also come with their own limitations. AI agents are changing the game by seamlessly working across different systems. Instead of relying on humans to connect the dots, these agents can pull data from multiple sources, update records, and automate actions without the constraints of traditional workflows. This ability raises critical questions about the future relevance of legacy SaaS. If these systems can’t adapt to encompass cross-platform functionality, they risk becoming mere data storage for AI agents. The author suggests that while some legacy providers may successfully integrate AI, many will struggle, as their capabilities are often confined to their own domains. The article shifts to financial metrics, providing insights into SaaS company valuations based on revenue multiples. The overall median EV/NTM revenue multiple sits at 4.4x, with high-growth companies seeing a median of 12.9x. This highlights how growth expectations significantly influence valuation. The author emphasizes that revenue multiples serve as a primary metric for evaluating software companies, especially since many are not yet profitable. The piece also touches on various operating metrics, like median growth rates and margins, painting a picture of the current SaaS landscape.