The AI equation

I've been working in the field of machine learning for more than 10 years. Recently, things have accelerated dramatically, and my time interacting with AI has increased significantly. I've learned a lot during this journey, and I'll share those lessons here.

When considering AI in the context of AI products, we can express it as a simple equation.

Value = Intent * Context * Knowledge * Intelligence * Actions * Trust

• Value is what the user wants to achieve.
• Intent is how users express what they want.
• Context includes everything users know that LLMs don't—from personal information to project-specific details.
• Knowledge encompasses information users need but don't currently have. For critical tasks, users typically need more reliable sources than LLMs or web-based information.
• Connections are the pathways that transform decisions into actions, such as API access or ecosystem integrations. Rarely is AI's output valuable in isolation.
• Intelligence serves as the connector that understands intent, knowledge, and context, translating them into actionable results. To be useful, it must maintain connections with external systems.
• Trust is essential at all levels: users must trust the UX to understand their needs and context, trust the knowledge and data sources being used, and trust the system's decision-making ability. This trust becomes particularly vital when AI operates autonomously.