Qualcomm’s CEO says AI agents will be the new app, and 40 new devices are coming

Introduction

In a recent interview, Qualcomm's CEO Cristiano Amon predicted that AI agents will become the new standard for mobile applications, replacing traditional apps. This shift represents a fundamental change in how we interact with our devices, moving from discrete applications to intelligent systems that can understand context and act autonomously. In this tutorial, you'll learn how to create a simple AI agent using Python and the OpenAI API that can perform basic tasks like answering questions, summarizing text, and setting reminders. This foundational knowledge will help you understand how these future AI agents will work in your daily life.

Prerequisites

Before starting this tutorial, you'll need:

• A computer with internet access
• Python 3.7 or higher installed
• An OpenAI API key (free to get at platform.openai.com)
• A code editor (like VS Code or PyCharm)

Why these prerequisites? Python is the most accessible language for beginners to learn AI concepts, while the OpenAI API provides access to powerful language models that form the backbone of AI agents. The API key is necessary to interact with OpenAI's services.

Step-by-Step Instructions

1. Set Up Your Development Environment

First, create a new folder for your project and open it in your code editor. Then, create a virtual environment to keep your project dependencies isolated:

python -m venv ai_agent_env
source ai_agent_env/bin/activate  # On Windows: ai_agent_env\Scripts\activate

This virtual environment ensures that your project won't interfere with other Python installations on your computer.

2. Install Required Packages

With your virtual environment activated, install the necessary Python packages:

pip install openai python-dotenv

The openai package provides the interface to OpenAI's API, while python-dotenv helps manage your API key securely.

3. Create Your API Key Configuration

Create a file named .env in your project folder and add your OpenAI API key:

OPENAI_API_KEY=your_api_key_here

Why use a .env file? This keeps your API key secure and prevents accidentally sharing it in public repositories.

4. Create the Basic AI Agent Structure

Create a file named ai_agent.py and start with this basic structure:

import os
from openai import OpenAI
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# Initialize the OpenAI client
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

def get_response(prompt):
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[
            {"role": "user", "content": prompt}
        ]
    )
    return response.choices[0].message.content

This sets up the basic framework for an AI agent that can respond to user input using OpenAI's language model.

5. Add Functionality to Your AI Agent

Enhance your agent by adding specific functions. Replace the basic get_response function with:

def get_response(prompt):
    # Define a system message to guide the AI's behavior
    system_prompt = "You are a helpful assistant. You provide concise, accurate answers to user questions."
    
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": prompt}
        ]
    )
    return response.choices[0].message.content

# Add a function to summarize text
def summarize_text(text):
    prompt = f"Please summarize the following text in 3 sentences or less:\n\n{text}"
    return get_response(prompt)

# Add a function to set reminders
def set_reminder(reminder_text):
    prompt = f"Create a simple reminder for: {reminder_text}"
    return get_response(prompt)

These functions demonstrate how AI agents can be specialized for different tasks, which is what makes them more powerful than traditional apps.

6. Test Your AI Agent

Update your main execution block to include the new functionality:

if __name__ == "__main__":
    print("AI Agent: Hello! I'm your AI assistant. How can I help you today?")
    while True:
        user_input = input("You: ")
        if user_input.lower() in ["quit", "exit", "bye"]:
            print("AI Agent: Goodbye!")
            break
        elif "summarize" in user_input.lower():
            text_to_summarize = input("What text would you like me to summarize? ")
            summary = summarize_text(text_to_summarize)
            print(f"AI Agent: {summary}")
        elif "reminder" in user_input.lower():
            reminder_text = input("What would you like to be reminded about? ")
            reminder = set_reminder(reminder_text)
            print(f"AI Agent: {reminder}")
        else:
            response = get_response(user_input)
            print(f"AI Agent: {response}")

This enhanced version allows your AI agent to handle specific tasks, showing how agents can be more intelligent than simple apps.

7. Run Your AI Agent

Save your file and run it from the terminal:

python ai_agent.py

You should see your AI agent respond to your input. Try asking it to summarize a short article or set a reminder to test its functionality.

Summary

In this tutorial, you've created a basic AI agent that can answer questions, summarize text, and set reminders. This simple demonstration shows how AI agents differ from traditional apps by being more intelligent, context-aware, and capable of performing multiple functions. As Qualcomm's CEO predicted, these agents are becoming the new standard for how we interact with our digital devices. While this agent is basic, it illustrates the core concept of AI agents: they're not just applications that do one thing, but intelligent systems that can understand context and adapt their behavior to help you accomplish tasks.

As you continue learning, you can expand this agent by adding more functions, integrating with other APIs, or even connecting it to your phone's native features to create a truly personalized digital assistant.