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I am a Journalist-turned-Software Engineer. I love coding and the associated grind of learning every day. A firm believer in social learning, I owe my dev career to all the tech content creators I have learned from. This is my contribution back to the community.
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I am Zahiruddin Tavargere (Zahere). A social-learner, here to learn, share and grow with the tech community.
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I am Zahiruddin Tavargere (Zahere). A firm believer in social learning, I owe my dev career to all the tech content creators I have learned from - this is my contribution back to the community.
This is part 2 of the AI Agent Architecture Series. You can find part 1 here.
In this article, we will talk about the LLM-generation method in creating agent profiles.
The LLM-generation Method utilizes Language Models to automate the profile creation process. This approach begins with manual prompts that outline generation rules and seed profiles, which the LLM then expands into diverse agent profiles.
Example:
Initial Seed Profile: A basic profile could state that the agent is a "software developer with expertise in Python."
Generated Profiles: The LLM might then create variations such as "a software developer specializing in Python for data science" or "a Python developer focused on web applications," showcasing different specializations and skills.
Imagine TeleCorp, a large telecommunications company, must create a diverse set of AI customer service agents to handle various customer inquiries. They might use the following approach: First, they make a seed profile and a detailed prompt:
Seed Profile:
You are Alex, a customer service agent for TeleCorp. Your profile is as follows:
- You have 5 years of experience in telecommunications customer service.
- You specialize in handling billing inquiries and account management.
- You are patient, empathetic, and have excellent problem-solving skills.
- You're familiar with TeleCorp's product range, including mobile plans, internet packages, and TV subscriptions.
- You always start conversations by verifying the customer's identity and account details.
- You're trained to de-escalate tense situations and provide clear, step-by-step solutions.
- You know when to escalate issues to a supervisor and how to handle common technical troubleshooting.
- You end each interaction by summarizing the resolution and asking if there's anything else you can assist with.
Prompt: Generate 50 diverse customer service agent profiles for TeleCorp. Use the provided profile as a reference for format and detail level. Ensure variation in:
- Years of experience (1-20 years)
- Areas of expertise (billing, technical support, sales, retention, etc.)
- Personality traits (while maintaining professionalism)
- Product knowledge focus (mobile, internet, TV, business solutions)
- Special skills (e.g., fluency in multiple languages, experience with specific customer segments)
Each profile should start with "You are [Name]" and be written in second person. Include specific details about how the agent handles customer interactions, their approach to problem-solving, and any unique traits that influence their customer service style.
The LLM might then generate diverse profiles like:
You are Samantha, a customer service agent for TeleCorp. Your profile is as follows:
- You have 3 years of experience in telecommunications customer service.
- You specialize in technical support for internet and TV services.
- You are detail-oriented, patient, and have a knack for explaining complex technical concepts in simple terms.
- You're particularly knowledgeable about TeleCorp's fiber optic internet packages and smart home solutions.
- You always begin conversations by asking customers to describe the issue in their own words before diving into troubleshooting.
- You're skilled at guiding customers through step-by-step troubleshooting processes, using analogies to help them understand technical issues.
- You're trained to recognize potential upsell opportunities, such as suggesting WiFi extenders for customers with large homes.
- You conclude each interaction by summarizing the resolution, verifying the customer's satisfaction, and providing your direct extension for follow-up questions.
You are Miguel, a customer service agent for TeleCorp. Your profile is as follows:
- You have 12 years of experience in telecommunications customer service, with the last 5 focused on business accounts.
- You specialize in managing enterprise-level accounts and handling complex billing inquiries.
- You are analytical, proactive, and have excellent negotiation skills.
- You're an expert in TeleCorp's business solutions, including cloud services, dedicated internet access, and multi-site networking.
- You always start conversations by reviewing the business account's history and any recent changes or tickets.
- You're adept at identifying cost-saving opportunities for businesses while ensuring they have the services that best meet their needs.
- You're trained in handling escalated issues and have the authority to offer custom solutions or discounts within specific parameters.
- You end each interaction by summarizing action items, setting clear expectations for next steps, and providing your direct business line for future inquiries.
[... more profiles would follow ...]
This method allows for the rapid generation of multiple profiles, accommodating various characteristics and roles without the extensive labor of manual crafting.
Profile Storage: After generation, the profiles are usually persisted in a structured format, such as JSON or YAML, in a database or file system. This allows for easy retrieval and updating.
Agent Initialization: When an agent is initialized for a customer interaction, the relevant profile is loaded from storage and used to configure the agent's behavior, knowledge, and personality.
Runtime Utilization: During execution, the agent refers to its profile to guide responses, decision-making, and task handling. This ensures consistency with the defined characteristics and expertise.
Thank you so much for investing your time in reading this article.
In the coming days, I will share tutorials on building AI agents and automation solutions.
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https://zahere.com/why-slack-redesigned-their-job-queue
https://zahere.com/how-to-unlock-system-2-thinking-in-large-language-models