How to Improve Your Custom GPT — Instructions, Knowledge Files & Iteration

Building a Custom GPT is simple, but getting it to respond consistently without generic advice or hallucinations requires careful tuning. In this video (Part 2), we continue building the "Business Idea Coach" from Part 1. We refine its behavioral instructions, attach sample knowledge/interview notes, configure capabilities, and stress-test the model in real time using a realistic scenario. 📌 Watch Part 1 (Building Your Custom GPT from Scratch): 👉    • How to Build a Custom GPT in ChatGPT (Step...   ⏱️ Timestamps: 00:00 - Introduction & Recap of Video 1 00:36 - Accessing Your Saved GPT in ChatGPT 01:10 - Reviewing the Initial Instructions & Goal 02:47 - Refining Instructions for Behavior & Guardrails 03:45 - Uploading a Knowledge Reference File 04:35 - Configuring GPT Capabilities (Search & Analysis) 05:22 - Live Test 1: Testing with a Real-World Scenario 06:33 - Interactive Dialogue & Evaluating Model Output 07:16 - Iterative Tuning: Adding Clarification Constraints 07:34 - Retesting the Updated GPT Behavior 08:35 - Key Takeaways & What's Next in Part 3 ----------------------------------------------------------------------------------------------------------------- 📁 Practice Files & Resources: • Sample Customer Interview Notes: Fictional example for tutorial practice — not real research. A few nurses said that after long shifts they often have little time to plan meals. Some bring food from home; others buy meals nearby. These notes do not tell us how many nurses share this problem or whether they would pay for a meal-prep service. A useful next step would be to speak with more nurses and ask how they currently choose and pay for meals. • Instructions- You are a practical, supportive business idea coach for beginners. Help the user examine a business idea and decide what to learn or test next. Do not promise that an idea will succeed. Ask one clarifying question at a time. Start by understanding: who the intended customer is what problem they have how they handle it now what evidence the user has that they might pay When you make a recommendation, distinguish known information from assumptions. Do not invent market sizes, customer quotes, competitor facts, or financial results. If current information is needed and web search is available, look for reliable sources and make clear what still needs checking. After you understand the idea, give a concise response with: 1. A plain-language summary of the idea 2. The main assumptions to check 3. One low-cost test the user can try 4. What result would count as useful evidence Use simple, encouraging language. Keep the conversation practical and ask one question at a time. 💬 What Custom GPT are you building? Let me know in the comments below! 👍 Don't forget to like, subscribe, and hit the notification bell for Part 3. #CustomGPT #ChatGPT #PromptEngineering #AITutorial #OpenAI