Prompts vs Agents

The term "agent" frequently gets thrown around in the LLM and NLP spaces. But what is an Agent, and how is it different than a complex Prompt?

Simple LLM Prompts

A LLM prompt is a short, well-defined input given to an existing pre-trained language model. The goal of the prompt is to elicit a specific response or answer from the model based on its learned patterns and relationships in the training data.

Here are some examples:

• "When is the first day of fall?"
• "What's a simple recipe I can make for a toddler?"

In this context, the prompt is used to retrieve information from the model's knowledge base or generate text based on its understanding of language patterns.

AI Agent

An AI agent is a program designed to simulate human-like conversation with users. Unlike simple LLM prompts, an AI agent has its own decision-making capabilities and can interact with users in a more dynamic way. It is outcome oriented, in that they typically assist a user in solving a problem or accomplishing a task.

An AI agent typically involves:

1. Intent detection: identifying the user's intent behind their input (e.g., asking for information, making a request).
2. Contextual understanding: understanding the conversation history and maintaining context.
3. Decision-making: determining how to respond based on the detected intent and contextual understanding.
4. Response generation: generating an appropriate response to engage with the user.

AI agents can be powered by pre-trained LLMs, but they are more complex systems that require additional infrastructure, such as natural language processing (NLP) pipelines, dialog management, and potentially even machine learning-based
decision-making mechanisms.

Examples of AI agents include:

• Chatbots in customer support or travel booking
• Virtual assistants like Siri, Alexa, or Google Assistant
• Conversational interfaces for e-commerce platforms or online services

Key differences between simple LLM prompts and AI agents are:

1. Interaction style: Simple LLM prompts typically involve a straightforward question-and-answer exchange, while AI agents engage in more dynamic conversations with users.
2. Decision-making capabilities: Simple LLM prompts rely on pre-trained models to generate responses based on the input prompt, whereas AI agents have their own decision-making capabilities to respond to user interactions.
3. Complexity: Simple LLM prompts are relatively simple and straightforward, while AI agents require more infrastructure, design effort, and technical expertise to develop.

In summary, a simple LLM prompt is an input given to an existing pre-trained model, whereas an AI agent is a complex system designed to simulate human-like conversation with users, involving intent detection, contextual understanding,
decision-making, and response generation.