This project presents a vision for reimagining AI-native application security.

Most enterprise security products today remain fundamentally dashboard-centric and data-heavy. AI is often introduced as a conversational layer placed on top of existing interfaces. While well-intentioned, this approach frequently adds friction rather than providing user values much. Users are asked to translate complex work into chat prompts, navigate between dashboards and conversations, and mentally stitch the experience back together.

This work starts from a different premise: what if we reverse the paradigm entirely, and design application security as an AI-native system from the ground up? When AI becomes the interface rather than an overlay, the product evolves from a tool into a super-agent — one that owns workflows, moves work forward, and acts as a true partner rather than a passive tool.

To support this shift, the experience is structured around two primary entry points:

1. Proactive AI actions
   A natural-language, guided interface that anticipates user intent and offers structured, context-aware actions. Rather than waiting for users to search, filter, and correlate data, the system actively surfaces relevant insights and recommended next steps.

2. Agentic workflows
   Predefined and semi-automated workflows that continuously generate signals, initiate investigations, and move tasks forward with minimal manual input. These workflows reduce cognitive load while accelerating response and resolution.

This vision represents a meaningful departure from incumbent enterprise paradigms and requires both technical courage and organizational alignment to realize fully. While ambitious, it establishes a foundation for a new class of AI-native enterprise software—one that moves beyond dashboards and toward systems that think, act, and collaborate with their users.