Many AI demos look impressive, but the actual products often fail to deliver and aren't widely used in real-world applications.

The AI industry suffers from a lack of rigorous evaluations and tests that demonstrate the frontier of model capabilities.

Many startups are focusing on selling tools for AI applications, but the reality is that many potential customers are still figuring out how to effectively use AI, leading to a disconnect between product offerings and actual market needs.

Building good products on top of AI models is incredibly difficult.

Some critics dismiss Manus as merely a wrapper for existing foundational models and tools, but this perspective overlooks the reality that many successful AI products also fit this description.

In product development, it's vital to communicate the capabilities and limitations of AI models upfront, ensuring users have the right expectations about what the technology can and cannot do.

Many AI agent assistants fail because they are built with incomplete features, leading to frustrating user experiences.

The current AI models still struggle with basic tasks, indicating a need for further optimization and development within the industry.

Products that start as AI-light and transition to AI-heavy often struggle to integrate AI features seamlessly into their core functionality.