The rise of agentic coding is creating a "SaaSpocalypse." These agents can migrate data, learn different workflows, and handle integrations, which undermines the core moats of SaaS companies: data switching costs, workflow lock-in, and integration complexity. This makes the high gross margins of SaaS businesses a prime target for disruption.

Traditional SaaS switching costs were based on painful data migrations, which LLMs may now automate. The new moat for AI companies is creating deep, customized integrations into a customer's unique operational workflows. This is achieved through long, hands-on pilot periods that make the AI solution indispensable and hard to replace.

The value in software is shifting from SaaS platforms (like CRMs) to the AI agent layer that automates work on top of them. This will turn established SaaS companies into simple data repositories, or "hooks," diminishing their stickiness and pricing power as agents can easily migrate data.

The primary moat for many SaaS companies was the complexity and high cost of migrating away from their product. AI agents can now automate this process, eroding that advantage, increasing competition, and giving buyers significant leverage to renegotiate contracts.

With AI agents in platforms like ChatGPT becoming the primary work surface, the traditional SaaS moat of owning the user interface is eroding. The most defensible position will be owning the core data as the "system of record," making the SaaS platform an essential backend database.

The lucrative maintenance and migration revenue streams for enterprise SaaS, which constitute up to 90% of software dollars, are under threat. AI agents and new systems are poised to aggressively shrink this market, severely impacting public SaaS companies' incremental revenue.

SaaS products like Salesforce won't be easily ripped out. The real danger is that new AI agents will operate across all SaaS tools, becoming the primary user interface and capturing the next wave of value. This relegates existing SaaS platforms to a lower, less valuable infrastructure layer.

Sierra CEO Bret Taylor argues that transitioning from per-seat software licensing to value-based AI agents is a business model disruption, not just a technological one. Public companies struggle to navigate this shift as it creates a 'trough of despair' in quarterly earnings, threatening their core revenue before the new model matures.

If AI agents are delegated to choose the optimal software for a task, they will constantly evaluate and switch between vendors based on performance and cost. This dynamic breaks the long-term customer relationships and enterprise lock-in that SaaS companies rely on, effectively commoditizing the software market and destroying brand loyalty.