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How LLMs are Transforming Conversational UX


Hello, Trailblazers of the AI Space,


Remember the days when building a bot felt like a never-ending cycle of setting flows and interpreting user inputs through rigid NLU frameworks?


Conversational Design Before LLMs

Not too long ago, we were all immersed in creating intricate flows, anticipating every possible user input, and crafting responses accordingly. It was a time of structure, precision, and rigidity—a time when creativity felt bound.

Those days are gone. They are becoming a distant memory, thanks to the introduction of Large Language Models (LLMs).


Conversational Design After LLMs

Today, the world of Conversational AI has been flipped upside down. The work is less about the exhaustive setting of flows and more about understanding the potent dynamics of prompt chaining and harnessing the power of well-structured knowledge bases.


However, the real change is in thinking.


Designers now need to think about what information is and how it is interpreted into something meaningful.


Understanding this dynamic will lead to organizing and retrieving information more accurately and efficiently and to creating better conversational agents.


So in summary, it boils down to:

  1. Organing and Retrieving Information and generating Meaning

  2. Flows: Very strategic Flows using NLP and NLU


The New Conversational Design Stack


The new CUX Design Stack will include a whole new section on Knowledge.


LLMs will tap into the Knowledge and be able to answer most questions, and then NLUs will follow up with the next logical step for the business.


For example, a user might ask about a product warranty, which triggers the Knowledge Base. The LLM answers the user's questions using the knowledge base and the user responds with enthusiasm. Then, the NLU is triggered to take the user down the happy path and close the sale.


In the example, the design stack includes:

  1. Knowledge Base: Training the LLM on specific information

  2. Prompt Design / Engineering / Tuning: prompts, instruction, roles given the LLM

  3. NLU Flows: Very strategic Flows using NLP and NLU


Knowledge Bases and the Future of Conversational UX

To give you a visual guide through this significant shift in bot creation, we've prepared a video that highlights the nuances of using LLMs effectively.



Join us in exploring this evolving landscape, where we'll continually delve deeper into making the most of the technologies reshaping our industry.


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