Your First AI Application is Easier Than You Think

Source: Dev.to

If you’re a developer, you’ve seen generative AI everywhere. It can feel like a complex world of models and advanced concepts. It can be difficult to know where to actually start.

The good news is that building your first AI‑powered application is more accessible than you might imagine. You don’t need to be an AI expert to get started. This post introduces a new codelab designed to bridge this gap and provide you with a first step. We’ll guide you through the entire process of building a functional, interactive travel chatbot using Google’s Gemini model.

Dive into the codelab and build your first AI application today!

Setting the Stage: Your First Project

In this codelab, you’ll step into the role of a developer at a travel company tasked with building a new chat application. You’ll start with a basic web‑application frontend and, step‑by‑step, bring it to life by connecting it to the power of generative AI.

By the end, you will have built a travel assistant that can:

• Answer questions about travel destinations.
• Provide personalized recommendations.
• Fetch real‑time data, like the weather, to give genuinely helpful advice.

The process is broken down into a few key stages.

Making the First Connection

Before you can do anything fancy, you need to get your application talking to the AI model. An easy way to do this is with the Vertex AI SDK, a complete library for interacting with the Vertex AI platform.

While the Vertex AI SDK is a powerful tool for the full machine‑learning lifecycle, this lab focuses on one of its most‑used features: building generative AI applications. This part of the SDK acts as the bridge between your application and the Gemini model. Without it, you would have to manually handle authentication, format intricate API requests, and parse responses. The SDK abstracts that complexity so you can focus on sending a message and receiving a response.

In this codelab, you’ll see just how simple it is.

Giving Your AI Purpose with System Instructions

Once your app is connected, the AI’s responses won’t be tailored to your specific use case yet. You can make it more useful by providing system instructions.

Hot Tip: Use Google AI Studio to Create Your System Instructions

A great way to develop your system instructions is to leverage Gemini as a creative partner. In Google AI Studio, ask Gemini to draft a thorough set of instructions for a “sophisticated and friendly travel assistant.”

After you have a draft, you can test it directly in AI Studio: start a new chat, set the Gemini model to the one you’re using in your app, and paste the text into the system‑instruction field. This lets you quickly see how the model behaves with your instructions, all without writing any code. When you’re satisfied with the results, you can copy the final instructions into your application.