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.
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The next generation of software may lack traditional user interfaces. Instead, they will be 'API-first' or 'agent-first,' integrating directly into existing workflows like Slack or email. Software will increasingly 'visit the user' rather than requiring the user to visit a dashboard.
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.
The barrier to creating software is collapsing. Non-coders can now build sophisticated, personalized applications for specific workflows in under an hour. This points to a future where individuals and teams create their own disposable, custom tools, replacing subscriptions to numerous niche SaaS products.
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.
In SaaS, value was delivered through visible UI. With AI, this is inverted. The most critical, differentiating work happens in the invisible infrastructure—complex RAG systems and custom models. The UI becomes the smaller, easier part of the product, flipping the traditional value proposition.
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.
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.
Instead of interacting with SaaS GUIs (like Greenhouse for hiring), users will interact with AI agents. These agents will directly manipulate the underlying system-of-record data, managing entire workflows from a simple conversation and making the traditional SaaS application redundant.
Instead of integrating third-party SaaS tools for functions like observability, developers can now prompt code-generating AIs to build these features directly into their applications. This trend makes the traditional dev tool market less relevant, as custom-built solutions become faster to implement than adopting external platforms.
