20VC: Monday.com CEO on Is SaaS Dead: Will Everything Be Vibe Coded | Will Systems of Record Become Valueless Databases in an Agentic World | Will LLMs Own the Value in the Application Layer with Eran Zinman

The smartest people in Silicon Valley are still pouring billions into new startups, even though anyone could theoretically "vibe code" their way to building the same companies. That paradox, according to Eran Zinman, CEO of Monday.com, reveals why the "SaaS is dead" narrative fundamentally misses the point about where AI creates and destroys value.

Zinman's argument cuts against the prevailing wisdom that large language models will commoditize software into worthless databases. Instead, he sees AI as the catalyst for the biggest business model transformation in SaaS history , one that his $12 billion company is betting everything on. "It's the biggest pivot moment for us, in the history of the company," Zinman says of Monday's shift toward consumption-based pricing and AI-native workflows.

The conventional story goes like this: AI agents will replace human workers, making systems of record irrelevant since humans won't need interfaces to interact with data. But Zinman sees a more nuanced future where the real challenge isn't replacing humans with agents , it's orchestrating collaboration between them. "It's like claiming that there's no need for SDR software because you bought Anthropic. It's a different problem to solve," he argues. The comparison reveals his core thesis: buying access to an LLM is not the same as building software that helps organizations actually deploy AI at scale.

This distinction matters because it points to where value will concentrate in an AI-driven economy. While tools for individual productivity and personal AI assistants proliferate, Zinman believes the harder problem , and bigger opportunity , lies in enterprise orchestration. "Companies will want guidance on how to do that. They're gonna need help setting up agents, figuring out what they can automate with agents and what they can replace in terms of headcount," he explains. This isn't about selling software licenses anymore; it's about solving the messy human problems of organizational change management in an AI world.

The shift represents a fundamental rethinking of how software companies create value. Zinman draws a sharp line between companies that bolt AI onto existing products versus those built as "AI native" from the ground up. "The bolt on AI strategy versus AI native built from the ground up with AI is just very different in how you build, integrate, and adopt, or approach AI as a fundamental platform," he observes. For Monday, this means abandoning the traditional seat-based SaaS model entirely in favor of consumption pricing , a risky transition that reflects his conviction that AI changes everything about how software gets used.

The timing of this transformation wasn't driven by any single breakthrough but rather a collective recognition across the industry. "Something changed about, I would say, a year ago. I don't know what it was, to be honest. Like, it's not like one tweet that I've seen or one product. I feel it was, you know, combining many many data points. But I think it was a collective understanding that things are changing and things are changing forever," Zinman reflects. That shift from skepticism to certainty among both founders and investors marks the moment when AI stopped being a nice-to-have feature and became an existential business question.

The implications extend beyond any single company or sector. If Zinman is right that the value lies in orchestration rather than raw AI capabilities, then the winners won't necessarily be the companies with the best models or the most data. They'll be the ones who figure out how to make AI actually useful in complex organizational contexts , a problem that requires understanding human behavior, change management, and business processes as much as it requires technical sophistication.

Watch for companies making this same bet: abandoning traditional SaaS metrics in favor of consumption models, rebuilding products around human-AI collaboration rather than human-only workflows, and positioning themselves as orchestration platforms rather than feature sets. The question isn't whether AI will disrupt software , it's whether incumbent software companies can reinvent themselves fast enough to capture the value that shift creates.