『Creating a Custom GPT – First Steps to Training an AI Assistant #S11E3』のカバーアート

Creating a Custom GPT – First Steps to Training an AI Assistant #S11E3

Creating a Custom GPT – First Steps to Training an AI Assistant #S11E3

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 This is season eleven, episode three. In this episode, we will walk through how to create a custom GPT for customer queries. You will learn how to set up a custom GPT using OpenAI’s tools, define its scope, structure its responses, and implement rules to ensure accuracy and professionalism. By the end of this episode, you will have a clear roadmap for setting up your AI assistant and preparing it to generate accurate email drafts, chat responses, and quotation replies. So far, we have collected and structured past customer inquiries and created clean, standardized responses. Now it is time to train a custom GPT to use this data effectively. A well-trained AI assistant can reduce response time, improve consistency, and scale customer support without losing quality. Let’s go step by step on how to create a custom GPT that understands your business and communicates effectively. Step One: Setting Up a Custom GPT Using OpenAI’s Platform To create a custom GPT, we will use OpenAI’s platform. OpenAI allows you to fine-tune an AI assistant by customizing its instructions, training it with additional context, and providing a structured knowledge base. To begin: Go to OpenAI’s GPT customization page. If you do not have an OpenAI account, create one first.Click on "Create a custom GPT". This will open an interface where you can define your AI assistant’s behavior.Choose a name and purpose for your AI. Make it clear that this GPT is meant for customer support, sales inquiries, and quotation requests. Step Two: Defining the Scope and Personality of Your Custom GPT A custom GPT needs clear guidelines on what it should and should not do. This helps ensure it generates responses that match your brand’s voice and style. In the GPT settings, define: What the AI should focus on: Example: "This AI is designed to assist customers by answering product-related questions, providing specifications, and generating price quotations."What the AI should avoid: Example: "Do not generate speculative answers. If unsure, ask for human review."The tone of communication: Example: "Use professional, friendly, and concise language." By setting these rules, your AI assistant will stay on-brand and provide consistent responses. Step Three: Feeding Structured Knowledge to Your Custom GPT Now that the GPT knows its role, we need to train it with the structured data we prepared in the last episode. OpenAI allows you to upload reference documents or connect the AI to a knowledge base that it can use when generating responses. Here is how to integrate structured data: Upload FAQ documents, customer support guidelines, and product sheets. These documents should contain accurate, verified information that the AI can use.Use structured data formats like JSON or CSV for product specifications. Example: json CopyEdit { "Product": "XYZ Model 2000", "Battery Life": "10 hours", "Weight": "1.2 kg", "Charging Time": "90 minutes" } This allows the AI to pull product details in a structured way when a customer asks for specifications. Define fallback responses. Example: If the AI does not have an answer, it should say: "I will need to check with our team to provide the most accurate response.""Can I confirm your requirements before providing a quotation?" By structuring information correctly, your AI assistant can respond faster and more accurately. Step Four: Testing and Refining AI Responses Once your custom GPT is set up, it is time to test its responses and fine-tune its accuracy. Ask sample customer questions and analyze the AI’s replies. Example: Question: What are the specifications of the XYZ Model 2000?AI Response: The XYZ Model 2000 has a battery life of 10 hours, a weight of 1.2 kg, and a charging time of 90 minutes. Check for accuracy and completeness. If responses are incorrect or vague, adjust the training data.Refine prompt engineering to improve quality. Example: Instead of: What is the price of XYZ Model 2000?Try: Provide a price for XYZ Model 2000, including available discounts and shipping details. Better prompts lead to better AI responses. Step Five: Setting Rules for Human Review Even with well-trained AI, some responses will still need human review. To prevent errors, set rules for when AI drafts should be reviewed before sending. Examples of human review triggers: High-value orders or custom quotations: If a price exceeds a certain amount, require manual approval.Unclear customer questions: If a question is vague, AI should flag it for clarification.Complaints or disputes: AI should not attempt to resolve complaints without human input. Having these AI-human collaboration rules ensures the AI remains an assistive tool rather than a fully automated system. Key Takeaways from This Episode A custom GPT can be created using OpenAI’s customization tools.Defining clear instructions helps control AI responses.Structured data, such as FAQ documents and product sheets, improves AI ...

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