Agentic AI Is Replacing SaaS: Narada CEO Tells TechCrunch

The SaaS Era Nears Its End, Says Narada AI

The focus keyphrase agentic AI enterprise software captures the emerging shift in how businesses use digital tools. In a recent interview with TechCrunch’s Equity podcast, Dave Park, co-founder and CEO of Narada AI, shared a provocative prediction: traditional SaaS is on its way out.

He cited inefficiencies plaguing today’s knowledge workers—who deal with up to 25 different tools daily and lose 2.5 hours managing them. According to Park, the future lies in intelligent agents that interact directly with data and databases, eliminating the need for separate SaaS interfaces.

Narada AI, founded on research from UC Berkeley, is developing what it calls large action models. These are enhanced versions of large language models designed to complete multi-step tasks across tools—even without APIs—by reasoning through instructions and acting independently.

What Makes Agentic AI Different from Automation

Unlike traditional automation, which requires predefined rules, agentic AI enterprise software responds to dynamic input and executes complex actions across silos. Park emphasized this point during his TechCrunch interview, explaining how these AI agents can navigate fragmented workflows without hardwired integrations.

The broader ecosystem is shifting in the same direction. Over 70 agentic startups were featured in Y Combinator’s latest batch. Meanwhile, enterprise leaders like Grammarly are assembling full-stack AI platforms through strategic partnerships and acquisitions—another signal that agents are poised to become foundational in enterprise software.

Rethinking Enterprise Software from the Ground Up

Park argues that users will no longer “use apps” in the traditional sense. Instead, workers will issue tasks to agents that coordinate actions across multiple systems, making decisions and completing operations autonomously.

This transition requires more than adopting new tools—it demands structural change. Organizations must prepare for decentralized workflows, flexible system architectures, and workforce models that revolve around outcome-based execution rather than task-based navigation.

As SaaS tools struggle to keep pace with rising complexity, agentic AI enterprise software offers a compelling new blueprint for productivity and digital transformation.

What would your business look like if you eliminated all apps—and just worked through agents instead?

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