While CLIs were an important stepping stone for agentic AI, the industry is rapidly moving back to rich Graphical User Interfaces (GUIs). These new UIs are designed for simultaneous collaboration between a human user and an AI agent, offering a more powerful and intuitive experience.

Current communication tools like Slack are ill-suited for managing AI agents. The future lies in integrated "super apps" that combine chat interfaces with built-in credential management, file systems, and API key provisioning, creating a unified environment for human-agent collaboration.

Karpathy's home automation agent ("Dobby") replaced six different apps by interacting directly with smart device APIs. This suggests a future where users interact with a single agent, and software products must expose agent-friendly APIs to survive, as their bespoke UIs become irrelevant.

In this software paradigm, user actions (like button clicks) trigger prompts to a core AI agent rather than executing pre-written code. The application's behavior is emergent and flexible, defined by the agent's capabilities, not rigid, hard-coded rules.

As AI moves into collaborative 'multiplayer mode,' its user interface will evolve into a command center. This UI will explicitly separate tasks agents can execute autonomously from those requiring human intervention, which are flagged for review. This shifts the user's role from performing tasks to overseeing and approving AI's work.

The rise of autonomous agents like OpenClaw dictates that the future of software is API-first. This architecture is necessary for agents to perform tasks programmatically. Crucially, it must also support human interaction for verification, collaboration, and oversight, creating a hybrid workflow between people and AI agents.

A new software paradigm, "agent-native architecture," treats AI as a core component, not an add-on. This progresses in levels: the agent can do any UI action, trigger any backend code, and finally, perform any developer task like writing and deploying new code, enabling user-driven app customization.

Users will stop interacting with countless individual apps and websites. Instead, they'll communicate with a personal AI agent that handles tasks by interfacing with services via APIs, making traditional graphical user interfaces obsolete.

A major architectural shift is underway: instead of embedding AI features into a product, companies should treat AI as an external agent that uses the product via a CLI or API. This simplifies integration and better aligns with AI's capabilities.