I’ve been exploring how prompt engineering works great for demos, but production systems often need additional layers like output validation and schema enforcement to stay stable.
Would love to hear your thoughts on where prompting ends and system design begins.
Hi, I’m Jaideep Parashar, Founder of ReThynk AI, AI Strategist, and Author of 40+ books on Artificial Intelligence, Prompt Engineering, and AI Solutions for Global Problems. Pioneering AI Future!
Thank you for sharing that, and you’re absolutely right. Prompting is a great interface for exploration and demos, but in production, it’s only the entry point, not the system.
In practice, prompting ends where reliability requirements begin. Once outputs affect real users or workflows, you need additional layers: validation, schema enforcement, guardrails, quality checks, versioning, and feedback loops. That’s where system design takes over, defining what “good” looks like, how failures are caught, and how behaviour stays consistent over time.
So I’d frame it this way: prompts shape intent, but systems shape outcomes. Both matter, but long-term stability comes from the architecture around the model, not from the wording alone. I appreciate you raising this; it’s exactly the distinction many teams discover the hard way.
Distributed backend specialist. Perfectly happy playing second fiddle—it means I get to chase fun ideas, dodge meetings, and break things no one told me to touch, all without anyone questioning it. 😇
The first thing I do with any GenAI tool is set up instructions! I genuinely cannot wrap my head around how anyone just... runs Copilot or even ChatGPT raw, like some kind of daredevil coder.
I spent weeks writing and tweaking these hyper-detailed scenarios for my blog posts, then GPT-5 came along and straight-up lawn-mowered them. 😆 So, now I’m redoing the whole thing — still duct-taping it together as I go. And that’s just the project-specific pile stacked on top of the system ones, times however many active projects I’ve got right now (twelve-ish, depending on how you count the ones I pretend are “paused”).
Hi, I’m Jaideep Parashar, Founder of ReThynk AI, AI Strategist, and Author of 40+ books on Artificial Intelligence, Prompt Engineering, and AI Solutions for Global Problems. Pioneering AI Future!
Haha, I totally get this! 😊 I’ve seen the same thing—without clear instructions, AI is like giving a supercar to someone who’s never driven. Setting up detailed prompts is half the battle.
GPT-5 can feel like it just steamrolls your carefully built frameworks, but iterating and refining is where the magic happens. Twelve projects at once? Respect. That’s real multi-prompt mastery!
Distributed backend specialist. Perfectly happy playing second fiddle—it means I get to chase fun ideas, dodge meetings, and break things no one told me to touch, all without anyone questioning it. 😇
I seriously worry about the world if “Write a 700-word blog on personal branding for developers. Use short sentences, 3 real-world examples, and end with a call-to-action.” is enough to produce content consumed by other people.
Hi, I’m Jaideep Parashar, Founder of ReThynk AI, AI Strategist, and Author of 40+ books on Artificial Intelligence, Prompt Engineering, and AI Solutions for Global Problems. Pioneering AI Future!
I completely get your concern. As someone who works with AI and digital transformation every day, I see this tension too. AI can produce content quickly, but it should not replace context, insight, or the human touch.
It's just that there's no point, is there? I could chat with ChatGPT myself; other people getting output with basically no insightful input is slop. Reguritated content (for now at least) that doesn't give me a human story, it doesn't provide me insight and it doesn't move knowledge forward.
Hi, I’m Jaideep Parashar, Founder of ReThynk AI, AI Strategist, and Author of 40+ books on Artificial Intelligence, Prompt Engineering, and AI Solutions for Global Problems. Pioneering AI Future!
Interesting. I never thought of constrains as a form or indicator of creativity. By the way, out of curiosity, I tested the art of prompting a few months ago. I asked someone to write 5 free prompts and 5 with constraints using ChatGPT (so 5 pairs). Maybe I'm just completely stupid, but I was forced to guess for all 5 pairs and got 4 wrong. I didn't see any difference in quality between the free prompt and the engineering prompt.
And it doesn't even know what the word count is. If we asked for 500 words, he gave 400, if 600, then 800.
However, I agree with points 2 and 4. Patient, iterative use and providing examples lead to absolutely better results.
Hi, I’m Jaideep Parashar, Founder of ReThynk AI, AI Strategist, and Author of 40+ books on Artificial Intelligence, Prompt Engineering, and AI Solutions for Global Problems. Pioneering AI Future!
Hey Dominik, I also agree with your perspective, this is exactly why prompting is part art, part science. I’ve found that patience and experimenting with phrasing usually make the biggest difference—sometimes a small tweak changes everything.
Hi, I’m Jaideep Parashar, Founder of ReThynk AI, AI Strategist, and Author of 40+ books on Artificial Intelligence, Prompt Engineering, and AI Solutions for Global Problems. Pioneering AI Future!
مطور مبتدئ، بدأت رحلتي في البرمجة بدافع إنساني: المساهمة في حماية الناس من السرقة والفساد.
أعتمد على الذكاء الصناعي كمساعد تقني، وأتعلم خطوة بخطوة.
أؤمن أن الأفكار البسيطة ممكن تكون بداية لحلول كب
Hi, I’m Jaideep Parashar, Founder of ReThynk AI, AI Strategist, and Author of 40+ books on Artificial Intelligence, Prompt Engineering, and AI Solutions for Global Problems. Pioneering AI Future!
AI is incredibly powerful, but it’s not magic. Without careful planning and thoughtful prompts, it can easily create more problems than solutions. LLMs' models often show illusions in the output, and it becomes difficult to remove illusions in the outcome.
Hi, I’m Jaideep Parashar, Founder of ReThynk AI, AI Strategist, and Author of 40+ books on Artificial Intelligence, Prompt Engineering, and AI Solutions for Global Problems. Pioneering AI Future!
Really helpful summary of common prompt mistakes
I’ve been exploring how prompt engineering works great for demos, but production systems often need additional layers like output validation and schema enforcement to stay stable.
Would love to hear your thoughts on where prompting ends and system design begins.
Thank you for sharing that, and you’re absolutely right. Prompting is a great interface for exploration and demos, but in production, it’s only the entry point, not the system.
In practice, prompting ends where reliability requirements begin. Once outputs affect real users or workflows, you need additional layers: validation, schema enforcement, guardrails, quality checks, versioning, and feedback loops. That’s where system design takes over, defining what “good” looks like, how failures are caught, and how behaviour stays consistent over time.
So I’d frame it this way: prompts shape intent, but systems shape outcomes. Both matter, but long-term stability comes from the architecture around the model, not from the wording alone. I appreciate you raising this; it’s exactly the distinction many teams discover the hard way.
The first thing I do with any GenAI tool is set up instructions! I genuinely cannot wrap my head around how anyone just... runs Copilot or even ChatGPT raw, like some kind of daredevil coder.
I spent weeks writing and tweaking these hyper-detailed scenarios for my blog posts, then GPT-5 came along and straight-up lawn-mowered them. 😆 So, now I’m redoing the whole thing — still duct-taping it together as I go. And that’s just the project-specific pile stacked on top of the system ones, times however many active projects I’ve got right now (twelve-ish, depending on how you count the ones I pretend are “paused”).
Haha, I totally get this! 😊 I’ve seen the same thing—without clear instructions, AI is like giving a supercar to someone who’s never driven. Setting up detailed prompts is half the battle.
GPT-5 can feel like it just steamrolls your carefully built frameworks, but iterating and refining is where the magic happens. Twelve projects at once? Respect. That’s real multi-prompt mastery!
Tbf, I usually only have a third of that going at any one time, but managing the edits is a special kind of learned skill 😉😆
I seriously worry about the world if “Write a 700-word blog on personal branding for developers. Use short sentences, 3 real-world examples, and end with a call-to-action.” is enough to produce content consumed by other people.
I completely get your concern. As someone who works with AI and digital transformation every day, I see this tension too. AI can produce content quickly, but it should not replace context, insight, or the human touch.
It's just that there's no point, is there? I could chat with ChatGPT myself; other people getting output with basically no insightful input is slop. Reguritated content (for now at least) that doesn't give me a human story, it doesn't provide me insight and it doesn't move knowledge forward.
I absolutely agree with that. It's horrific, but real...
Prompts matter! 🎯
@suvrajeet Yes, prompts definitely matter.
Interesting. I never thought of constrains as a form or indicator of creativity. By the way, out of curiosity, I tested the art of prompting a few months ago. I asked someone to write 5 free prompts and 5 with constraints using ChatGPT (so 5 pairs). Maybe I'm just completely stupid, but I was forced to guess for all 5 pairs and got 4 wrong. I didn't see any difference in quality between the free prompt and the engineering prompt.
And it doesn't even know what the word count is. If we asked for 500 words, he gave 400, if 600, then 800.
However, I agree with points 2 and 4. Patient, iterative use and providing examples lead to absolutely better results.
@daemonic01
Hey Dominik, I also agree with your perspective, this is exactly why prompting is part art, part science. I’ve found that patience and experimenting with phrasing usually make the biggest difference—sometimes a small tweak changes everything.
Glad it was helpful! Excited to hear how it works out for you.
الذكاء الاصطناعي هو مارد هذا العصر
عليك توجيهه جيدا فربما طلباتك بدون تفكير وتخطيط مسبق تصبح لعنة وليس مساعدة
AI is incredibly powerful, but it’s not magic. Without careful planning and thoughtful prompts, it can easily create more problems than solutions. LLMs' models often show illusions in the output, and it becomes difficult to remove illusions in the outcome.
Good!
Thank You.