Please see an update for me this morning in the comments. This disaster is going to make me a much better founder. I got up at 3:45 AM today to begin rebuilding my company. Original post follows: I’m standing here writing this in tears, and I want to give a very sobering warning to anyone who is considering upgrading from ChatGPT plus to a business Team’s account on ChatGPT. There is a a glitch that was unknown to me before I started this process, but is apparently well known in the open AI developer community that all of your data is deleted when you migrate it and you can’t get it back. Everything I’ve been building for months is just …. Gone. Other than what I had saved and backed up in my personal files, my entire ChatGPT history has been zeroed out, and it really hurts because this was like my external brain for both home and my business that I’m building. Open AI acknowledged that their company documentation failed to include a warning that all of my personal data would be deleted and everything that I have been working on since day one in my accounts has been deleted, and there’s nothing I can do to get it back even though I followed their exact instructions on merging my personal and business accounts, to the letter. I just paid $618 to upgrade my account to two seats on a business plan and merged the data from my personal account to my business plan. Within a minute or two of that transaction going through as I was following the step-by-step worksheet that ChatGPT itself printed out for me. My accounts froze, and I had to log out. I logged back in everything was blank. When I used my previous emails that I had my accounts tied to to log back in ChatGPT opened free tier accounts using my business email that I just paid $618 to open my business account on. I’ve escalated this to ChatGPT Support and they were extremely unhelpful. Basically they said sorry it’s a known issue and there’s nothing we can do. I was planning on shipping a product today using the ChatGPT business plan because it offers a secure link so that I’m not sending out raw proprietary JSON code.

We keep seeing the same pattern: someone tries AI, gets disappointed, and decides "it's not ready yet." But here's what's actually happening. They're treating AI like they'd treat a new hire, expecting it to just know what to do, read their mind, and deliver exactly what they wanted without any back-and-forth. That's not how AI works. And honestly, that's not even how people work. The mindset shift: The best analogy we've found is a sparring partner. Not someone who does the work for you. Not someone who reads your mind. But someone who pushes back, offers alternatives, and helps you think through the problem differently. When you spar with someone, you don't expect them to know exactly how hard to punch or which combinations to throw. You adjust in real time. You say "lighter" or "try this angle instead." The value comes from the interaction, not from them being perfect on the first try. AI is the same way. The magic happens in the conversation, not in crafting the one perfect prompt that generates the one perfect output. Here's what this looks like in practice: Version 1 (Treating AI like an employee): "Write me a blog post about productivity tips for entrepreneurs." AI gives you generic advice. You're disappointed and decide AI isn't useful. Version 2 (Treating AI like a sparring partner): "Write me a blog post about productivity tips for entrepreneurs." AI gives you generic advice. You respond: "This is too general. My audience is coaches who work from home with kids. Focus on strategies that work when you have 30-minute blocks of time max." AI adjusts. You respond: "Better. Now add a specific story or example for each tip so it feels real, not theoretical." AI refines again. Same starting point. Completely different outcome. The difference? You stayed in the conversation. Scenarios where sparring wins: Mark runs a consulting firm and was frustrated that AI-generated proposals felt flat. Then he realized he was dumping information and expecting polish. Now he treats it like a brainstorming session. First pass: rough ideas. Second pass: "Make this sound more conversational." Third pass: "Add specific metrics here." The proposals are better because he's coaching AI through his vision instead of expecting it to nail everything upfront.

One of the most meaningful lessons I took away from the AI Advantage Summit came from Sabrina Romanov. She taught us that we can give AI a role to play, so it can support us when we need it. I was able to use this technique yesterday for clarity and grounding. I want to share a very personal experience. I admit am writing this with tears in my eyes. My mom passed away on June 25. I cared for her for two intense years and supported her for more than twenty eight years. When I was nineteen and serving in the Navy, she had a mental health emergency. I stepped up and she became my official Navy dependent and she stayed with me all the way until June of this year. I wish I had AI tools like this during some of those years. We had many challenges. Love and grit carried us through. Yesterday I received my mom’s ashes from the Walter Reed medical center mortuary affairs specialist. My mom is mother of two veterans (including myself) and she chose to donate her body to the military medical hospital here in Washington DC. I learned yesterday that 417 military doctors, nurses, and medical professionals were able to learn from her anatomy. That final act of service was incredibly powerful. Holding the small box of her ashes made everything real. I needed time to grieve and reset before picking my 5 year daughter up from school. I remembered Sabrina’s guidance about assigning a role to the AI so it can respond with the tone we need. I typed into ChatGPT that I needed calm support while processing grief. What I received was steady, compassionate guidance that helped me take the next breath and steady myself. It did not remove the pain, but it helped me slow down and process what I was feeling. It also helped me think through gentle ways to talk about my mom’s passing with my daughter who is still trying to understand everything. I am sharing this because the summit opened my eyes to the different ways we can use AI tools in our daily lives. Sometimes we use them for productivity. Sometimes we use them for business planning. Yesterday I got the help I needed immediately to help me reset and it was a very needed moment.

If you are new to AI, it is easy to feel overwhelmed with new terminology. Copy everything below this line into your AI tool to create your own glossary while you’re learning! _____________________________ I am a beginner and need a clear, simple glossary of important AI and large language model (LLM) terms. Please follow these exact instructions when creating the glossary. FORMAT REQUIREMENTS: • All topic words and acronyms must be in BOLD ALL-CAPS • Definitions must be in plain text • No numbering and no bullet points • Each definition must be single-spaced • There must be two line breaks between each glossary entry • Group similar terms under logical subheadings to help beginners understand how concepts relate • The glossary must be formatted so it can be exported as a portrait PDF with 1-inch margins on all sides • Do not include decorative boxes, shaded backgrounds, icons, or graphic elements WHAT EACH GLOSSARY ENTRY MUST INCLUDE: • BOLD ALL-CAPS TERM • Plain-text beginner definition • Why the term matters (one sentence) • A simple real-world use case that shows how the term appears in everyday AI tools or AI products CONTENT REQUIREMENTS: • Include 50 core AI and LLM terms, including but not limited to: LLM, NLP, API, GPU, TOKEN, TRANSFORMER, TRAINING DATA, PARAMETER, INFERENCE, PROMPT, PROMPT ENGINEERING, FINE-TUNING, RAG, EMBEDDING, MULTIMODAL, DATASET, VECTOR DATABASE, MODEL WEIGHTS, SAFETY GUARDRAILS, CONTEXT WINDOW, TEMPERATURE, LATENCY, etc • ask the user if they would like to generate a second list of 50 after the first 50 terms is completed. • Use clear, friendly, non-technical language • Do not assume any prior knowledge • Include a short three-sentence introduction at the top explaining why a glossary is helpful for beginners PDF REQUIREMENTS: At the end of the glossary, produce text formatted cleanly so that I can export the entire document as a PDF in portrait orientation, 1-inch margins, simple black text, and double spacing between entries, with no numbering, no bullets, and no decorative elements.

If you're still writing prompts the length of "War and Peace," and ChatGPT still produces some kind of nonsense, this article will change your life. Today I'll tell you about a programming method that makes neural networks much more responsive. A Prompting Method That Changes Everything - JSON Prompts and How to Use Them By the way, I'm Anton Shadrin. My job is to implement neural networks in business and make AI work for you, not you for it. What is this JSON beast and why is it better than regular prompts? JSON is simply a way to structure information. Imagine that instead of a solid sheet of text, you give ChatGPT a clear list: this is the role, this is the task, and this is the response format. A typical prompt looks like this: You're an experienced copywriter. Write a post for Instagram about the benefits of meditation. The text should be friendly and motivating, 150-200 words long. Use emojis and add a call to action at the end. And here's the same prompt in JSON: { "role": "Experienced social media copywriter", "task": "Write a post for Instagram about the benefits of meditation", "style": "Friendly and motivating", "length": "150-200 words", "format": "Text with emojis", "cta": "Call to start meditating today"} See the difference? In the second case, the neural network understands exactly what is being asked of it. No fluff, no double interpretations—a pure structure. Why this works better (spoiler: it's in the neural network's brain) ChatGPT was trained on millions of lines of code, where JSON is a standard data format. It's like its native language. When you feed information in JSON, the neural network switches to "oh, this is serious" mode and starts working more accurately. I tested both approaches on over 50 tasks. The result: JSON prompts produce the desired result on the first try 80% of the time, compared to 60% with standard ones. The time savings are enormous. Step-by-step instructions: creating your first JSON prompt Step 1. Define the structure