ELIZA replied with pattern matches. DialogFlow mapped intents. GPT answered from weights. Claude runs tools and verifies. Each era solved the previous one's worst failure.
A user says "I want to change my flight." The system has to figure out what they want, what information is missing, how to get it, and how to complete the action. Then the user says "wait, what if I cancel instead?" and the system has to remember the context, switch tasks, and preserve state.
Conversation is hard for an ML system. The input is open-ended. The output has to be coherent over many turns. The system may need to act on the world (change a flight, charge a card). Every wrong step is visible to the user.
Chatbot architectures have cycled through four paradigms, each introduced because the previous one failed too visibly. This lesson walks them in order. The 2026 production landscape is a hybrid of the last two.
Full Access lesson
Keep going. The rest of this lesson is one step away.
Unlock all 503 lessons, video, code, quizzes and every future update. Pay in your own currency with Paystack.