Enhancing User Interactions with Actionable Prompt & Predictable Prompts

[vishalmysore]

Actionable Prompts: Actionable prompts are user inputs or queries that trigger immediate actions or responses within an AI system. These prompts typically express a specific intent or request from the user, prompting the AI system to perform a corresponding action. Actionable prompts are the initial inputs that drive interactions with the AI system, directing it to execute tasks, provide information, or facilitate processes based on user needs. Examples of actionable prompts include requests to book a reservation, retrieve information, schedule an appointment, or perform a specific function within an application or system.

Predictable Prompts: Predictable prompts are subsequent prompts or actions anticipated by an AI system based on the context or content of actionable prompts. These prompts are automatically predicted by the AI system after analyzing the initial user input and identifying potential follow-up actions or inquiries. Predictable prompts aim to proactively address user needs, preferences, or intentions by suggesting relevant actions or providing additional information without requiring explicit user requests.

In summary, actionable prompts initiate interactions with AI systems by prompting immediate actions or responses, while predictable prompts anticipate and suggest subsequent actions or inquiries based on the context of the initial user input. Together, actionable and predictable prompts enable AI systems to deliver proactive, personalized, and contextually relevant interactions with users, enhancing overall user satisfaction and engagement.
Example Scenario 1:
Consider a scenario where a user inputs the prompt, "My car broke down."

Actionable Prompt:

Action: BookTaxi ( implements com.t4a.bridge.AIAction)

import com.t4a.bridge.AIAction;

// Define the BookTaxi action class implementing the AIAction interface
public class BookTaxi implements AIAction {

    // Method to handle the BookTaxi action with parameters
    public void bookTaxi (String pickupLocation, String destination, int numberOfPassengers, boolean isLuxury) {
        // Logic to book a taxi with specified pickup location, destination, number of passengers, and luxury preference
        System.out.println("Booking a taxi from " + pickupLocation + " to " + destination + " for " + numberOfPassengers + " passengers" + (isLuxury ? " (Luxury)" : "") + "...");
        // Additional code to handle the booking process
    }
}

Subsequent Predictable Prompts:

Action: BookCarService (annotation '@'Predict)Prompt: "Schedule a car service appointment."Context: The user's car has broken down, indicating a need for repair or maintenance.

import com.t4a.bridge.AIAction;

// Define the BookCarService action class implementing the AIAction interface
@Predict
public class BookCarService implements AIAction {

    // Method to handle the BookCarService action with parameters
    public void bookCarService (String serviceType, String appointmentDate, String vehicleModel, boolean isExpressService) {
        // Logic to schedule a car service appointment for the specified type, date, vehicle model, and express service preference
        System.out.println("Scheduling a " + serviceType + " appointment for " + appointmentDate + " for vehicle model " + vehicleModel + (isExpressService ? " (Express Service)" : "") + "...");
        // Additional code to handle the booking process
    }
}

Action: OrderFoodDeliveryPrompt: "Would you like to order food delivery while waiting for your car to be serviced?"Context: Recognizing the potential inconvenience caused by the car breakdown, the AI system suggests the option of ordering food delivery to the user's location.

import com.t4a.bridge.AIAction;

// Define the OrderFoodDelivery action class implementing the AIAction interface
@Predict
public class OrderFoodDelivery implements AIAction {

    // Method to handle the OrderFoodDelivery action with parameters
    public void execute(String cuisineType, String deliveryAddress, String specialInstructions) {
        // Logic to order food delivery of the specified cuisine to the given address with special instructions
        System.out.println("Ordering " + cuisineType + " food delivery to " + deliveryAddress + " with special instructions: " + specialInstructions + "...");
        // Additional code to handle the ordering process
    }
}

Action: NotifyEmergencyContactsPrompt: "Notify emergency contacts about your situation?"Context: Considering the urgency of the situation, the AI system prompts the user to notify their emergency contacts about the car breakdown for assistance.

import com.t4a.bridge.AIAction;

// Define the NotifyEmergencyContacts action class implementing the AIAction interface
@Predict
public class NotifyEmergencyContacts implements AIAction {

    // Method to handle the NotifyEmergencyContacts action with parameters
    public void execute(String message, String contactPhoneNumber, String contactEmail) {
        // Logic to notify emergency contacts with the provided message, phone number, and email
        System.out.println("Notifying emergency contacts: " + message + " | Phone: " + contactPhoneNumber + " | Email: " + contactEmail);
        // Additional code to handle the notification process
    }
}

In this scenario, the initial user prompt triggers the immediate action of booking a taxi. Subsequently, based on the context of the situation, the AI system predicts and suggests additional actions that the user may need to address the consequences of the car breakdown.