AI agent teams often lag behind frontend teams, resulting in a struggle to keep up with new features and tools that enhance user experience. However, building an AI agent interface is straightforward if you leverage existing features rather than starting from scratch, allowing for broader access to tools and services.

Creating a feature-complete AI agent simplifies the user experience and reduces frustration by supporting all tools simultaneously rather than one at a time.

When building AI tools, companies often find themselves on a long path to feature parity with their existing frontend, which can delay the implementation of essential features.

The disconnect between a well-developed frontend experience and the slower development of AI tools leads to user confusion about which features are supported.

We are building a UI for AI that integrates chat, search, and agent management into one interface, enhancing productivity.

Instead of spending too much time on building an AI core product, launch smaller experiments to gather early user feedback before full integration.

When building your own AI tools, you can create a navigation tree and focus on unreliable parts, enhancing the overall reliability of the agent.

The ultimate goal for future AI agents is to seamlessly integrate various tasks, such as web searching and computer operations, in a more natural and human-like manner.

When creating an AI agent, focus on ongoing repetitive tasks that require some judgment but not full expertise, similar to delegating to a junior intern.