Unlocking ChatGPT with prompt engineering: A video editor's journey

**Unlocking the Power of Prompt Engineering for ChatGPT 🚀** **Why mastering prompt design is a game-changer in AI interactions!** As a video editor stepping into the realm of AI, I discovered how effective prompt engineering enhances chatbot and AI utility, especially in generative models. Here’s what I learned: ⭐️ Prompt engineering defines how we interact with AI models for more accurate and useful outputs. ⭐️ Crafting a "good prompt" requires clarity, context, and purpose to guide the AI efficiently. ⭐️ Hands-on practice with prompts reveals the subtleties that make or break the AI response. ⭐️ Identifying and avoiding common prompting errors is crucial to maximize AI capabilities. ⭐️ Advanced prompt engineering enables tackling complex instructions and tasks creatively. ⭐️ Applications span from content creation to automating workflows with virtual assistants. As someone with less than a year of experience, these insights are particularly valuable in understanding how AI can augment my work and boost productivity. Prompt engineering isn’t just for developers; it’s a skill that will redefine roles across fields, including creative ones like mine. What’s your take on using AI with tailored prompts to enhance workflow? Are you already experimenting with this in your domain?

Ever wondered how ChatGPT actually processes your prompt? Here's a guide that breaks it down into 10 simple steps - from your raw input to the polished response you see in real time. Key highlights: - Prompt Input → Your question is the starting point. - Tokenization & Encoding → Words become machine-readable data. - Pattern Recognition & Context Understanding → AI interprets tone, intent, and meaning. - Knowledge Retrieval → Pulls insights from training. - Response Generation & Coherence Check → Ensures clarity, grammar, and flow. - Final Output → A conversational answer that feels natural. Whether you’re a developer, AI enthusiast, or just curious, understanding this process helps you craft better prompts and get smarter results. [Learn More In The Post] If you found this helpful don’t forget to save this for later and comment your thoughts. Get exclusive free video training on how to use AI to work faster, smarter, and automate your workflow with AI tools : https://lnkd.in/eWTUNUYx Follow Denis Panjuta on Linkedin : https://lnkd.in/eUHjTBUi

📊 Interesting breakdown: how people are using ChatGPT across tasks Some use it for writing. Some for coding. Some for learning. Few treat it as a strategic advisor. In wealth planning, this reminds me: tools are amplifiers, not deciders. It’s not about what tech you use — it’s about how consciously you use it. 👉 What’s your guardrail when using new tools — productivity vs reliability vs accuracy? #ifg #ai #chatgpt #investments

💡 Big news: OpenAI just released something that will change the way you use ChatGPT. ...... ...... ...... It’s called the Prompt Optimizer—and it makes your prompts dramatically smarter. Instead of guessing how to phrase things, you can drop in any rough idea, and the Optimizer instantly rewrites it into a clear, structured, and powerful prompt that gets much better results. ✨ What makes it special? Not only does it sharpen your prompt, but it also explains why it made the changes—so you actually learn to write better prompts over time. Here’s how to try it: 1️⃣ Head to the OpenAI Playground 2️⃣ Select Prompt Optimizer 3️⃣ Paste your rough idea & hit “Optimize” 4️⃣ Copy the improved version into ChatGPT—and watch the difference It’s like having a pro prompt engineer built right into ChatGPT. 👉 Want the link? Comment below and I’ll share it. 🔔 Follow Elevate Labs for more tips on getting the most out of AI.

✨ How does ChatGPT actually work? I recently came across a brilliant video by Rakesh K (Codergyan) where he explained this concept using a restaurant analogy — simple yet powerful storytelling. Key learnings 👇 🔹 LLMs don’t have real-time internet access. They are trained on existing resources like Wikipedia, books, and research papers. 🔹 For real-time data (like weather or news), models use external tools such as web search. 🔹 A backend router decides which model or tool should be used — whether it’s the LLM itself, a reasoning model for complex logic, or an image generation model. 🔹 It’s not just one model, but a smart orchestration of multiple models and tools working together seamlessly. 💡 Thanks to Rakesh K for breaking down such a complex topic with great clarity. Looking forward to exploring more such thought-provoking topics. #AI #ChatGPT #LLM #ArtificialIntelligence #Learning

Why AI is a Game-Changer for Professional Development! 🚀 Ever wondered why AI is making waves? As I explored my CPE credit options, I discovered this video that opened my eyes to the true potential of AI tools like ChatGPT. It's not just a search tool—it's like a "personal assistant," enhancing the quality and efficiency of my search. AI is an excellent option for quickly accessing vast amounts of data and receiving help in sorting and summarizing it. It offers deep, expert-level conversations, allowing me to focus on what truly matters. While my human expertise is still crucial for cross-checking facts, AI provides a fantastic starting point for my professional growth. Let's embrace AI and elevate our careers! 💼✨ #AI #ProfessionalDevelopment #Efficiency #Innovation #CareerGrowth

ChatGPT doesn’t think, it predicts. One of the biggest misconceptions I see when teaching people is the belief that AI “remembers” or “considers” facts like a human would. When a model like ChatGPT, Gemini, or Claude generates text, it’s not reasoning about truth. It’s doing math to predict the most likely next chunk of text--like an extremely advanced autocomplete. That misunderstanding is the root of so much frustration in the workplace: - Engineers trusting false directions and increasing ticket resolution times. - Leaders seeing budgets wasted on “AI pilots” that stall - Customers losing confidence when answers don’t line up The first breakthrough for everyone I work with is this: once you really understand how the model works, you can start to shape its output with prompts, guardrails, and workflows. That’s when reliability goes up and frustration goes down.

Open AI recently published a study on how people are using Chat GPT. Most folks aren’t wiring n8n graphs or utilising Claude code or shipping Lovable/ V0/Replit apps. They’re using AI for day-to-day stuff. Recent usage data shows: - people mostly want practical guidance, info, and help writing and much of the “writing” is actually editing at work, I get that myself as ESL. - Non-work usage now accounts for ~73% of ChatGPT messages—so design for everyday tasks, not just office workflows.  - Adoption is real: 65% of companies report regular gen-AI use in at least one function—marketing, product, and IT lead the way.  - GitHub Copilot users finished coding tasks ~55% faster: when you meet users where the work lives, results pop. - Growth is skewing younger and fastest in low/mid-income countries: think mobile-first Ship the advisor today, learn from edits, then automate the boring parts. Momentum beats perfection. The future favors builders who turn curiosity into compounding product loops. Report link in the comments.