iso27diy-corp/Corpus/Various/LLMs and Vibe Coding/Designing an Agent.md

3.2 KiB
Raw Blame History

CLAUDE DID THIS

Creating an onboarding agent that takes the lead requires shifting from a reactive assistant model to a proactive interviewer model. Heres how to approach this:

Core Design Principles:

Start with a clear script structure where the agent drives the conversation forward. The agent should have predetermined pathways and questions, but with enough flexibility to adapt based on responses. Think of it like a skilled consultant or intake specialist who knows exactly what information they need to gather.

Conversation Flow Architecture:

Design your agent with a hierarchical question structure. Begin with broad, open-ended questions to understand the customers general situation, then progressively narrow down to specific details. For example, start with “Tell me about your current challenges with [your service area]” before diving into technical requirements or budget constraints.

Build in natural transition phrases that maintain conversational flow while keeping control: “Thats helpful context. Now Id like to understand…” or “Based on what youve shared, my next question is…”

Information Gathering Strategy:

Map out all the critical information you need for successful onboarding and organize it into logical themes. Create primary questions for each theme, with follow-up questions ready based on different response types. This prevents the agent from getting stuck or losing direction.

Consider using a mix of question types - open-ended for understanding context and motivations, specific for gathering facts, and clarifying questions to ensure accurate understanding.

Maintaining Control While Being Conversational:

Program the agent to acknowledge customer responses appropriately, then smoothly redirect to the next needed information. Use phrases like “I understand thats important to you. Let me ask about…” This validates their input while maintaining the interview structure.

Build in gentle persistence for critical information. If a customer deflects or gives incomplete answers, the agent should know how to circle back professionally.

Technical Implementation Considerations:

Create clear state management so the agent knows what information has been gathered and whats still needed. This allows for natural conversation flow while ensuring nothing is missed.

Design fallback responses for when customers ask questions or try to take control of the conversation. The agent can briefly address their concern, then guide back to the interview process.

Would you like me to elaborate on any of these aspects, or do you have specific questions about implementing this approach for your particular service?

Resources for learning this design approach

https://www.cloudskillsboost.google/course_templates/892

https://academy.cognigy.com/courses/conversation-design-course https://academy.cognigy.com/collections

https://www.udemy.com/course/design-conversational-ai-experience/

https://www.perplexity.ai/search/93f1aea8-7da1-48ce-94a8-5874628fe103

https://rosenfeldmedia.com/books/conversations-with-things/