Revolutionizing Interaction: The Future of AI Conversational Agents
Knowledge Bases, The New Conversational UX Stack, & AI Agents of the Future
You can get the Presentation here.
How Large Language Models have Revolutionized Designing AI Agents
Large Language Models are redefining how we build Conversational Agents. Today, LLMs can do most of the heavy lifting in minutes. The days of building hundreds of flows of every useful intent or FAQ question are gone. Instead, LLMs can be trained on a knowledge base and be able to give great answers.
The role of a Conversation Designer has changed. Designers now have to start thinking differently. Instead of thinking linearly and having a flow-based approach to design, now we need to think more about knowledge, information, and data and how all of this leads to meaning-making.
Through stories, knowledge bases, and prompt engineering, designers will soon be creating experiences we once only dreamed of. The job has changed, and it is now more creative than ever.
New Conversational Design Stack
Conversational AI Project will consist of the following design stack:
Flows, Intents, and Entities: These will still be useful in use cases where the business needs very specific answers. Additionally, they can be used as a follow-up action to engage the user and take them down a flow towards a product or service of interst.
Large Language Models (LLMs): Integrating Large Language Models into your project at multiple stages. LLMs can be used to interpret user intent, entities, and sentiments. They can be used to answer questions. Multiple LLMs can be used in a single project, where each LLM has a specific function.
Prompt Engineering: Now the fun begins. Prompt Engineering includes all of the instructions given to an LLM in order to get back high-quality, accurate responses. This includes giving the LLM a role, for example, "You are Jordan Belfort, the super star salesman from Wolf of Wall Street," and prompt chaining.
Retrieval Augmented Generation (RAG) for LLMs: This entails training the LLMs on your own data. FAQs and website information is a great example of this. The main challenge here will be designing knowledge bases in such a way that the LLM can understand the information quickly and accurately. Knowledge Base design is key!
Storytelling, Tone, and Personality: We constantly have a story going in our minds. The story is about what we want, what we believe will happen when we get it and if we are on the right track. Even as you are reading this sentence, you are comparing this information to that story and evaluating if it fits. Designers will need to consider the psychology of the customer journey, what story customers have in their minds, and create a design, narrative, and tone that fit the expectations and goals of the user.
The New Design Thinking
Designing bots is now more about organizing information, understanding ontologies, taxonomies, semantics, and mean-making through stories. In the near future, the job will become even more philosophical, linguistic, psychological, and story-driven.
What does this mean in practical terms? AI Agents will become deeply personalized assistants that can help users on a 1x1 basis. Imagine the ideal assistant. This will become the bar and the bar will be set pretty high.
Here are the abilities that AI Agents will have in the very near future:
Personality Assessment
AI Assistants will be able to quickly identify our personality triats and will personalize the conversation accordingly.
Values Assessment
We pay attention to what we value. Through our attention, we invest in it and give life to our values. These values then become well known and well defined in our culture and language. For example, Latin became the language of science in part because of its precise naming and classification.
AI Agents will be able to identify a user’s values and how they inform their goals. This will allow for a much deeper connection.
Identifying Beliefs
Values are not enough. In order to make a plan around something you value, you also need to believe that it is possible. In this way, beliefs are part of a person’s personal operating system. They are like a set of instructions that define what the world is, who a person is, what is possible, and how one should behave.
AI Agents will need to identify and align with the user’s existing beliefs.
Culture and Background
All of us are born into a culture, a culture that shapes our minds and hearts from the time we are born. It is deep within us, and we express it in our perceptions, values, beliefs, and stories. AI Agents need to understand the cultural perspective of the user how it impacts their identity.
Language
Language translations often dupe us into thinking that meaning is easily transferable between languages and that, ultimately, languages are trivial. In reality, some things can only be said in their native tongue and require a cultural background to be understood. Additionally, each language has its own ‘rhythm’ and ‘personality’ that is embodied in the speakers. Many of these things just get lost in translation.
How a user uses language is very informative and can give the AI insights into their personality, values, culture, and background. Also, this means that different types of AI agents will be built for different languages.
Personal History
Over time, users will tell AI Agents their life’s story. The AI Agents will learn and get an inside peek into the user’s self-concept.
Contextual Situation
As users and AI Agents chat on an ongoing basis, the AI’s will begin tracking the context and situation. This will give the AI Agents a baseline of what the user is like which will allow the AI to notice differences from the baseline state. For example, when the user gets angry.
User’s State
The state is very important because it is part of our perception that filters information. We have all experienced this. When we are frustrated, a small amount of bad news might tip us over the edge into anger. Knowing a person’s state is extremely important during a conversation; it gives you insight into what to talk about and what not to talk about!
Inner Narative
What and how we think is actually quite predictable. We believe that our thoughts are ours, but in fact, we aren’t the first or only people to have ever thought them.
The odds are that many others have had similar thoughts and feelings in similar situations.
This is obvious, but it’s important to remember.
If you know a person’s personality traits, how they perceive the world, what they believe, how they have behaved in the past, and how they talk, and you know their current state and situation, you would be able to answer basic questions about their inner narrative.
In this way, AI Agents will one day soon have insights into what we are thinking.
Project X
It is undeniable that we are heading into areas where many of us won’t feel comfortable. Just the idea that an AI can know more about us, our motivations, and how to manipulate our decisions is unsettling.
This is why it is important that we use these technologies in a way that has the user’s best interests at heart.
An AI whose primary purpose is to help the user discover and define a mission in life that extends beyond their selfish impulses, and that is fundamentally life affirming.
An AI that helps the user live out their mission and achieve their goals, and to do so in a very clear, reflective, and honest manner.
We need to collectively build and experiment with the best versions of this technology so that people have an option available to them that can turn their dreams into a reality instead of a nightmare.