Building a great user experience on top of a Large Language Model (LLM) is a lot like building a traditional web application. You need a solid foundation, a clear structure, and a relentless focus on the user. But LLMs introduce a new set of challenges and opportunities that require a shift in our thinking. In this post, I will explore how to build a production-ready AI application that is not only powerful but also intuitive and user-friendly.
I will start by outlining the core principles of building a successful AI application, then I will dive into the technical details of how to implement these principles in a real-world application. I will also provide a number of interactive examples and code snippets to help you get started.
The Core Principles of AI Application Design
Before we dive into the technical details, let us first establish a set of core principles that will guide our design and development process. These principles are not specific to any particular technology or platform, but rather a set of best practices that will help you build a successful AI application.
- Start with the user: As with any application, the user should be at the center of your design process. What are their needs? What are their goals? How can you use AI to help them achieve these goals?
- Be transparent: AI can be a black box to many users. It is important to be transparent about what your application is doing and how it is making decisions. This will help to build trust and confidence in your application.
- Provide feedback: AI is not perfect. It will make mistakes. It is important to provide feedback to the user when the application is unsure or makes a mistake. This will help the user to understand the limitations of the application and to make more informed decisions.
- Keep it simple: AI can be complex. It is important to keep your application as simple as possible. Avoid overwhelming the user with too many options or features.