Story suggestions vs. Agentic AI

In the previous Botsify system, you had to train your chatbot by:

• Creating Stories (predefined conversation flows).
• Adding Story Suggestions (sample phrases/intents) to teach the bot how to recognize user inputs.

This was a manual intent training process.

What’s Changed Now?

With Agentic Botsify, you no longer need to:

• Write long lists of training phrases.
• Manually set up intent recognition.
• Manage separate “story” flows for every possible query.

👉 Why? Because your AI Agent is now powered by a Large Language Model (LLM).

That means your AI can:

• Understand user input in natural language without intent training.
• Adapt to variations in how users phrase their questions.
• Respond more intelligently based on context + memory.

How You Train Your AI Now

Instead of giving story suggestions or training phrases, you simply:

• Describe the behavior you want in plain English (or your preferred language) to create your first chatflow
• Let the AI generate the chatflow for you.
• Refine by giving direct instructions (e.g., “Change the greeting to…”, “Add a reply when someone says thanks”).

Example

Old System (Story + Intent Training):

• Create Story: Gym Pricing Inquiry
  
• Add training phrases: “How much is the gym?”, “What’s your fee?”, “Tell me about pricing.”

New System (Agentic AI):

Just say:

When users ask about pricing, show them my membership plans with monthly and yearly options.

The AI will automatically handle variations of the same question.

✅ Summary:

• Story Suggestions = no longer needed.
  
• LLM-powered Agentic AI = understands users naturally.
  

You just describe what you want, and your AI agent takes care of the rest.