Interfaces & UX

Conversational AI

AI systems designed to engage in natural language dialogue with humans, ranging from simple chatbots with scripted responses to advanced assistants powered by large language models.

Why it matters

Conversational AI is how most people interact with AI today. Understanding the spectrum from rule-based chatbots to LLM-powered assistants helps you choose the right approach for different use cases.

The spectrum

Conversational AI ranges from simple to sophisticated:

  • Rule-based chatbots — follow decision trees and keyword matching. Predictable but brittle. Common in customer support FAQ bots.
  • Intent-based systems — use NLP to classify user intent and route to appropriate responses. More flexible than rules but still limited to predefined intents.
  • LLM-powered assistants — use large language models to understand context, generate responses, and handle open-ended conversation. ChatGPT, Claude, Gemini.

Key capabilities

  • Context management — tracking what has been said earlier in the conversation.
  • Intent understanding — figuring out what the user is actually asking for.
  • Multi-turn dialogue — handling follow-up questions, clarifications, and topic changes.
  • Tool use — calling external systems to look up information or take actions.

When to use what

Rule-based bots are fine for narrow, predictable tasks (order status, appointment booking). LLM-powered assistants are better for open-ended tasks where the user's needs are unpredictable. The cost and complexity difference is significant — choose based on the actual problem, not the technology hype.