1. No User Interface, No Problem
AI agents operate in the background as backend code. Unlike SaaS, which relies heavily on user interfaces (UIs), these systems are autonomous—they make decisions and take actions on behalf of a company, communicating through APIs without human input.
With SaaS, building UIs requires a lengthy and complex process involving UX designers, product managers, frontend and backend engineers. This development cycle centers on creating screens for users to input data and click buttons.
In contrast, AI agents bypass all that. At Qurrent, we’ve seen one engineer develop an entire workflow for a company in weeks instead of months. The simplicity of backend development leads to faster iteration and deployment of powerful solutions.
2. Rapid Iteration for Probabilistic Systems
AI agent systems are not deterministic—they don’t follow rigid functional specs. Instead, they handle a wide variety of scenarios, making their behavior probabilistic and adaptive.
This requires a rapid, iterative development process. You observe the agent’s behavior, refine it, and repeat. Unlike traditional software development—where you squash bugs until the system performs as specified—AI agents evolve continuously to meet real-world needs.
3. The Customization Imperative
AI agents make decisions autonomously, often without human oversight. This autonomy necessitates highly customized systems tailored to each company’s unique legacy tech stack, workflows, and customer interactions.
This is a departure from the SaaS mindset, where companies build a product once and sell it to thousands of customers. In the AI agent era, success depends on a build-not-buy approach, or a hybrid solution involving a product heavily customized to meet specific business needs.
A Model for the Future
Companies like Palantir Technologies, which thrive on customization, are wellpositioned in this new era. Palantir’s business model involves custom-building applications for each client using repeatable software frameworks.
Historically, customization and professional services were seen as a liability in the venture capital world, perceived as less scalable. But Palantir leaned into it, achieving a market cap per employee higher than any other major tech company. Their approach demonstrates the power of combining scalable frameworks with bespoke engineering.
The rise of AI agents marks a shift in how we think about software development and implementation. These systems require a new mindset—one that embraces speed, adaptability, and deep customization. As this paradigm continues to unfold, businesses that adapt quickly will have a significant competitive advantage.
