Ubiquitous local AI agents that can script any service and reverse-engineer APIs fundamentally threaten the SaaS recurring revenue model. If software lock-in becomes impossible, business models may shift back to selling expensive, open hardware as a one-time asset, a return to the "shrink wrap" era.

While AI expands software's capabilities, vendors may not capture the value. Companies could use AI to build solutions in-house more cheaply. Furthermore, traditional "per-seat" pricing models are undermined when AI reduces the number of employees required, potentially shrinking revenue even as the software delivers more value.

Companies will adopt a hybrid "build vs. buy" approach. They will use AI agents to build bespoke, simple software "screwdrivers" for specific workflows on the fly, eliminating many niche SaaS tools. However, they will continue to "rent" large, foundational platforms like ERPs and CRMs, which serve as heavy-duty "trucks."

For decades, buying generalized SaaS was more efficient than building custom software. AI coding agents reverse this. Now, companies can build hyper-specific, more effective tools internally for less cost than a bloated SaaS subscription, because they only need to solve their unique problem.

Turing's CEO claims SaaS is dead for two reasons. First, powerful foundation models drastically lower the cost of building custom software internally. Second, existing SaaS products are built for human interaction via GUIs, not for AI agents that will increasingly use APIs and tool-calling functions directly.

The fundamental business model of many SaaS companies is based on per-user pricing. AI agents pose an existential threat to this model by enabling smaller teams to achieve the same output as larger ones. As companies wonder why they should pay for 100 seats when 10 people can do the work, the entire economic foundation of the SaaS industry faces a crisis.

The traditional SaaS model—high R&D/sales costs, low COGS—is being inverted. AI makes building software cheap but running it expensive due to high inference costs (COGS). This threatens profitability, as companies now face high customer acquisition costs AND high costs of goods sold.

Countering the idea of a zero-sum SaaS market, Box CEO Aaron Levie argues that AI agents create net-new value. By performing complex knowledge work on existing data (like analyzing contracts), agents allow software platforms to capture budget previously allocated to human labor, thus expanding the total addressable market.

The disruption to software isn't just about professional developers. It's about non-technical employees, like sales executives, using AI tools like Claude to build functional internal applications that replace paid SaaS products. This trend democratizes software creation and directly undermines the traditional SaaS business model from within customer organizations.