Every morning, I read a handful of AI newsletters over coffee. Not for the hype or the hardware updates, but for something far more practical. Prompts. Tucked between the headlines and think pieces, you’ll often find “Prompt of the Day” sections, promising to unlock the full potential of generative AI. Some are short, snappy, and direct. Others read like onboarding manuals for a new employee. And that got me thinking. When it comes to prompting AI, what really works best, and when? 

Does Prompting Really Matter? 

Yes it does. Short and simple. Prompting is not something you should ignore. It’s still worth putting thought into how you communicate with AI, especially reasoning-focused ones, which tend to respond better to well-structured prompts. And if you’re writing code that integrates LLMs, rather than just chatting with them, crafting a strong prompt becomes even more important. Obviously, for fooling around or chatting with AI companions, it doesn’t matter how you approach prompting. But if you’re using language models for learning, casual exploration, or answering questions, your energy is often better spent understanding what they’re good at, and where they fall short, rather than obsessing over the perfect phrasing.  

With that being said, here’s when you should use short or long prompts. 

The Short Prompt Advantage and Why I’m a Short Prompt Guy 

There’s something to be said for brevity. Short prompts are like tossing out an idea in a group brainstorm. You don’t know exactly what will come back, and that’s half the fun. They give you room to respond, adapt, and riff. It’s not a rigid structure. For example, if you start with: 

“Give me 3 creative ways to thank a customer.” 

You’ll come with a short list: handwritten note, social media shoutout, personalized gift. Nothing groundbreaking, but enough to spark a direction if you’re not sure which one to go with. Then, if you follow up with something like: 

“Make the gift idea feel more unique. The customer is a record enthusiast.” 

You’ll be looking at suggestions like limited-edition vinyl pressings or custom playlist curation. Short prompts work great here. There’s also a practical issue to consider when it comes to long prompts. Even the most advanced AI models can struggle when overloaded with too many instructions at once. The result? They’re more likely to produce inaccurate or confusing answers, sometimes called hallucinations, or just ignore parts of the prompt entirely. Shorter, more focused prompts make it easier to review the AI’s output and refine it step by step, keeping you in control and aligned with your original goals. 

For that very reason, I prefer short prompts. For me and the things I use AI for, short prompts keep things fast and flexible. I can toss an idea at the AI, see what comes back, and tweak it in real time. 

It’s not that I don’t like AI taking over. It’s more about steering, giving it just enough to start moving, then guiding it where I want it to go. I stay in control, adjusting as needed until it gives me something I can actually use. That’s the power of short prompts. It’s like creative ping-pong. You’re actively shaping the result rather than just watching it unfold. Of course, not everyone works this way. Some people prefer a detailed prompt to set the scene, and that’s fine. 

But Don’t Count Long Prompts Out 

Now, let’s be fair. There are plenty of people who live and die by the detailed prompt. You know the type. They write prompts that read like creative briefs, with personas, goals, formatting instructions, and disclaimers. And to be honest, sometimes those deliver scarily precise outputs. Long prompt may look something like this: 

“You’re a creative marketing manager for a new energy drink startup. You’re prepping a press release for a product that promises energy but doesn’t contain caffeine. The goal is to sound confident but not pretentious. Mention sustainability. Keep it under 300 words. Use Gen Z humor.” 

That’s a mouthful that may or may not get you there. You’re shaping the character, tone, purpose, all up front. If you know exactly what you want, a long prompt may get you there in fewer steps. The issue, though, is what happens when things go wrong. When your output is off, and with long prompts this happens more often than you’d expect, it’s harder to pinpoint what part of the prompt broke the logic. Did the tone fall apart because you mentioned Gen Z humor? Did the AI hallucinate a fictional product launch because your setup was too specific? Like mentioned earlier, shorter prompts will make things easier for AI to follow. 

The Flexibility Factor 

Long prompts are like formal contracts. They’re structured. Specific. There’s less room for improvisation. But when you’re experimenting, or when you’re not entirely sure what you want yet, short prompts leave breathing room. 

Let’s say you’re writing a product description. You could type: 

“Write a product description for a smartwatch.” 

Or you could go further: 

“You’re a copywriter at a high-end tech brand releasing a minimalist smartwatch designed for busy professionals. Write a short product description for the landing page. Highlight features like sleek design, long battery life, and smart notifications. Keep the tone confident, modern, and clean. Avoid buzzwords. Use short, punchy sentences.” 

You see the difference. The first one gives you something to react to. The second is great if you’ve already figured out the vision. But if you’re still deciding on the tone, audience, or even the event’s name, then a shorter start gets the job done faster or get some online tutoring.

At the heart of this debate is a simple question: Do you want to start perfect, or get there step by step? 

Short prompts are for iterators. Builders. People who enjoy watching the idea evolve in real time. Long prompts are for architects. People who know what they’re building before they break ground. 

Neither is wrong. But knowing which style fits you best can save you a lot of time, and a lot of weird AI misunderstandings. My suggestion is to take a free prompt engineering course like this one and learn best practices and how to apply them to your work. 

Find Your Own Style 

So what’s the verdict? Are short prompts better? Are long prompts overrated? This article is not “good vs bad prompts”, so there’s no definitive answer here. For me, short prompts all the way. But that’s the thing. That’s me. That works for me personally. The best prompt is the one that fits how you think. Some people are outliners. Others are improvisers. AI doesn’t care either way. It’s not grading your prompt. If you’re someone who thrives on structure, you might find that longer, more detailed prompts hit the mark. It all comes down to what helps you think clearly and get the results you want. 

Need a quick spark of inspiration? Keep it short. Looking for a more guided, in-depth response? Go long. 

Here’s something to try: next time you’re working with AI, run an experiment. Ask it to “brainstorm vegan dinner ideas” in ten words. Then do the same thing with a detailed, 100-word setup full of context and specifics. Compare the answers. 

You can also take a long prompt, maybe one you found online, and break it into pieces. Feed them in step by step, only moving forward when you’re satisfied with each part. You might find that layering your input this way gives you more control over the outcome. Which version feels better in your hands? Which one gives you answers that actually move the needle? There’s no single rule here. No prompt formula that works for everyone. It’s just about finding your rhythm, and once you do, the whole process gets a lot smoother.