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SaaS businesses thrived by organizing newly abundant information. AI now makes the creation and organization of software itself abundant, driving its cost to zero. This commoditization of the core value proposition of many SaaS companies makes them a poor venture investment category going forward.

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Founders are no longer pitching traditional software businesses. The focus has shifted entirely to AI-native companies building 'systems of intelligence' or 'systems of action'. This reflects a market belief that existing software workflows without a deep AI moat are too easily replicated and devalued.

As SaaS firms use AI to optimize operations, they feed models data on how their products are built. This creates a deflationary spiral where customers can use the same AI to build cheaper alternatives, threatening the core SaaS business model by accelerating price and profitability compression.

Enterprises no longer need to buy expensive SaaS products for tasks like customer feedback. They can now spin up custom AI agents internally, making it harder for SaaS companies to acquire new customers and leading to higher-than-modeled churn. This poses a fundamental threat to the SaaS business model.

As AI makes the software itself easier to build and replicate, the durable value of a SaaS company is no longer the code. Instead, the moat lies in the customer relationship, the proprietary data, the system of record it represents, and the deep understanding of user workflows.

Traditional SaaS models benefited from near-zero costs for new users. AI's high computational and token costs upend this, creating deeply unprofitable users and workflows unless firms carefully manage implementation and pricing.

A partner at Google's AI-focused fund, Gradient Ventures, has adopted a "short SaaS" investment thesis. The rationale is that AI makes building software so easy that most traditional SaaS companies no longer have a defensible moat. This puts the entire business model in jeopardy, making it an unattractive area for new venture investment.

SaaS companies face an existential threat not just from AI commoditizing their features, but from its shift from a workflow augmentation tool to a labor replacement tool. This fundamentally breaks traditional per-seat pricing models, which are tied to human headcount, creating a pricing crisis.

AI is making core software functionality nearly free, creating an existential crisis for traditional SaaS companies. The old model of 90%+ gross margins is disappearing. The future will be dominated by a few large AI players with lower margins, alongside a strategic shift towards monetizing high-value services.

For over a decade, SaaS products remained relatively unchanged, allowing PE firms to acquire them and profit from high NRR. AI destroys this model. The rate of product change is now unprecedented, meaning products can't be static, introducing a technology risk that PE models are not built for.

The fundamental shift from AI isn't about replacing foundational model companies like OpenAI. Instead, AI creates a new technological substrate—productized intelligence—that will engender an entirely new breed of software companies, marking the end of the traditional SaaS playbook.