Decide on core features for the prototype (answering questions, summarizing recipes, basic recommendations).
Target User:
Choose a specific user group (e.g., beginner home cook) to focus on.
Platform:
Select a platform for building your prototype (e.g., chatbots in Dialogflow, voice assistants in Google Cloud Speech-to-Text).
2. Design Conversation Flow:
Map user journeys:
Create flowcharts outlining user interactions with the AI, including starting points, potential questions, and responses.
Script key interactions:
Write sample dialogues demonstrating the AI's capabilities for specific tasks (e.g., finding recipes, asking substitutions).
Consider error handling:
Define how the AI will respond to unexpected questions or unclear inputs.
3. Build the Prototype:
Choose a development platform:
Utilize tools like Dialogflow, Rasa, or Botpress based on your chosen platform and desired features.
Implement NLP capabilities:
Train the AI to understand user input and respond with relevant information from recipe data.
Design the interface:
Create a user-friendly interface (e.g., chat window, voice commands) for interacting with the AI.
4. Test and Iterate:
Gather feedback:
Share the prototype with target users and collect feedback on its ease of use, functionality, and helpfulness.
Analyze user interactions:
Review how users interact with the AI and identify areas for improvement.
Refine the prototype:
Based on feedback, iterate on the design, flow, and AI responses to improve its effectiveness.
Additional Tips:
Start small and focus on core features first.
Use mock data initially and integrate real recipe data later.
Focus on a natural and engaging conversation style for the AI.
Prioritize user feedback and iterate quickly to improve the prototype.
Design
1. Define Prototype Scope:
Functionality:
2. Design Conversation Flow:
Map user journeys:
3. Build the Prototype:
Choose a development platform:
4. Test and Iterate:
Gather feedback:
Start small and focus on core features first. Use mock data initially and integrate real recipe data later. Focus on a natural and engaging conversation style for the AI. Prioritize user feedback and iterate quickly to improve the prototype.