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.

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As AI makes it trivial to scrape data and bypass native UIs, companies will retaliate by shutting down open APIs and creating walled gardens to protect their business models. This mirrors the early web's shift away from open standards like RSS once monetization was threatened.

Companies are now rejecting expensive SaaS contracts because their internal teams can build equivalent custom solutions in days using AI coding tools. This trend signals a fundamental threat to the traditional SaaS business model, as the 'build vs. buy' calculation has dramatically shifted.

Historically, a deep library of integrations (like MuleSoft's or Rippling's) created a powerful defensive moat. Now, AI coding agents like Devin can replicate hundreds of integrations in a month at a very low cost, making this form of defensibility obsolete.

AI is becoming the new UI, allowing users to generate bespoke interfaces for specific workflows on the fly. This fundamentally threatens the core value proposition of many SaaS companies, which is essentially selling a complex UX built on a database. The entire ecosystem will need to adapt.

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.

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.

The ease of building applications on top of powerful LLMs will lead companies to create their own custom software instead of buying third-party SaaS products. This shift, combined with the risk of foundation models moving up the stack, signals the end of the traditional SaaS era.

The dominant per-user-per-month SaaS business model is becoming obsolete for AI-native companies. The new standard is consumption or outcome-based pricing. Customers will pay for the specific task an AI completes or the value it generates, not for a seat license, fundamentally changing how software is sold.

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.

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.