What is Prompt Engineering? — How to Write Effective AI Prompts in 2025

Chances are your boss has asked you to start using AI, or you’ve been hearing how it’s transforming industries across the board. With all the excitement around AI, it’s easy to feel overwhelmed about how to actually use it.

According to McKinsey, AI has “the potential to automate work activities that absorb up to 70% of employees’ time today.”

Fortunately, the most common type of AI you'll likely encounter is generative AI (genAI), which operates through natural language. That means getting it to do something is often as simple as talking to it.

This is where prompt engineering comes in. It’s the practice of crafting effective prompts that align with how AI models work — ensuring you get the best possible results.

In this blog, we’ll break down how prompt engineering works and show you how to write better prompts, so you can future-proof your skills and confidently integrate AI into your workflow.

Where to Start Prompt Engineering?

Despite having “engineering” in its name, this skill isn’t overly complex. Since generative AI tools work through natural language, effective prompting is essentially about having clear, high-context conversations with the AI.

The more you engage and iterate, the better the AI understands your intent—and the more you learn about how it responds.

Take this simple example: you want to write a cover letter for a job application. You can copy and paste your professional summary along with the job description, and prompt the AI with something like:

“Read this job description and my professional summary, then write a suitable cover letter for my application.”

The AI will generate a draft, but it might not match your desired tone or could be too long or too short. That’s where iteration comes in. You might respond with:

“Make it slightly less formal and keep it under 300 words.”

You get the idea. This back-and-forth feedback loop allows you to refine the output until it meets your needs. This process is known as multi-shot prompting — each new prompt adds more context and improves the results.

Be Specific

The first thing to remember is that AI doesn’t share the context that’s in your head. So, if your prompt is too vague, the response might be completely off from what you were expecting.

For example, if you're researching recent innovations in blockchain technology, it’s important to include specific details in your prompt.

A generic prompt like “Explain recent innovations in blockchain” will likely return broad or outdated information. Instead, try something more focused, such as:

“Explain what developments in blockchain have driven innovation in decentralized finance (DeFi) since early 2024.”

This gives the AI a clear, well-defined scope, and as a result, you'll receive a much more relevant and structured response.

Give it Space for Reasoning

As we’ve seen, an iterative approach works best, but it's also important to give the AI room to think.

Avoid forcing your own conclusions or steering the conversation too narrowly. Doing so can lead the AI to generate weak or biased responses just to fit your prompt.

For example, instead of asking, “What’s the best VPN app for accessing Netflix?” ask something more open-ended, like:

“What factors should I consider when choosing a VPN for accessing blocked Netflix content?”

Once you have a solid list of criteria, you can follow up with: “Based on those factors, which VPNs would you recommend?”

This approach encourages deeper, more reasoned answers — and leads to better insights and smarter decisions.

Avoid Misspellings and Bad Grammar

Even though AI is quite good at recognizing typos or grammatical errors and can still generate a decent response, it's always best to refine your prompts using correct grammar and clear wording. This helps avoid misunderstandings and ensures more accurate results.

Create Scenarios and Personas

You can guide the AI by creating imaginary scenarios or role-playing exercises to help it adopt a specific persona. For instance, if you want it to respond like a sales manager, simply tell it to take on that role and provide the necessary context.

Your prompt might look like this:

“You are now roleplaying as a Senior Sales Manager at a fast-growing tech company. You are confident, persuasive, and solution-oriented, with a customer-first mindset. Your job is to answer customer questions in a way that builds trust, highlights value, and subtly encourages conversions. Maintain a professional yet friendly tone, and personalize where possible.”

From that point on, the AI’s responses will reflect the role and tone you’ve set, making interactions more aligned with your goals.

Use Delimiters to Structure Input Clearly

One of the most effective techniques in prompt engineering, especially when providing the AI with multiple pieces of information, is to use delimiters like triple quotes ("""), triple backticks (```), or clear markers like --- or ###.

Delimiters help the AI distinguish between different parts of your input and maintain clarity when parsing your instructions. This is especially useful when your prompt includes large blocks of text, such as documents, transcripts, user messages, or multiple data points.

Example:

“Summarize the following text: """The Industrial Revolution marked a major turning point in history..."""”

The clear separation provided by delimiters ensures the AI doesn’t confuse your instructions with the content you’re feeding it.

Prompting for AI Image Generation

Prompting an AI to generate images is quite different from prompting for text, but the core principle remains the same: clear, detailed natural language produces better results.

Here are some key tips to help you craft effective image prompts for tools like ChatGPT, Gemini, or any AI image generator:

1. Be Specific with Subject, Style, and Composition

Avoid vague descriptions. Clearly define what you want, how it should appear, and from what perspective. Include details about lighting, mood, setting, and color.

Example:

“A futuristic samurai standing on a neon-lit rooftop at night, cinematic angle, glowing katana, rain falling, cyberpunk style.”

2. Use Strong Adjectives and Descriptive Phrases

Descriptive language helps the AI visualize the tone and aesthetic. Words like “elegant,” “gritty,” “hyper-detailed,” or “vintage” add clarity and richness.

Example:

“An elegant Victorian living room, richly decorated, golden sunlight through sheer curtains, oil painting style.”

3. Anchor Style with Artist References or Mediums

Mentioning specific artists, genres, or mediums provides visual anchors and improves style consistency.

Example:

“Fantasy landscape in the style of Studio Ghibli, wide shot, soft pastel tones, whimsical forest path.”

4. Use Camera Terms for Realism and Framing

To get realistic or cinematic results, add photography terms like “depth of field,” “bokeh,” “35mm lens,” or “low angle shot.”

Example:

“Portrait of an elderly man with deep wrinkles, low-key lighting, shallow depth of field, 85mm lens, ultra-realistic.”

5. Iterate with Variants and Refinement

Start with a basic prompt, review the outputs, and tweak based on what worked. Modify composition, add detail, or shift styles to improve the results.

Example:

Initial Prompt: “A retro diner at sunset, empty tables, 80s neon signs, cinematic lighting”

Refined Prompt: “A retro diner interior at golden hour, empty red vinyl booths, glowing 80s neon, wide-angle shot, cinematic film grain.”

To use top-of-the-line AI image models and experiment prompting, check out ImagineArt’s AI image generator.

Prompting for AI Video Generation

AI video generation is a relatively new frontier, with reliable video models arriving well after image generators. To get the most accurate and cinematic results, you’ll need to craft your prompts with precision, much like directing a film.

Here are some essential tips for generating high-quality AI video clips:

1. Describe the Scene Like a Director

Think visually and narratively. Outline the setting, characters, motion, and mood. Use active language to describe what’s happening, not just what’s present.

Example:

“A man runs through a foggy forest at dawn, camera follows behind steadily, branches brushing past, soft diffused light.”

2. Add Camera Movements and Angles

Direct the AI’s perspective using terms like “tracking shot,” “zoom-out,” “overhead drone view,” or “slow pan.” These guide how the viewer experiences the action and enhance realism.

Example:

“Cinematic zoom-in on a lone warrior standing in the desert, dust swirling, low-angle shot, dramatic lighting.”

3. Include Temporal Cues and Motion Detail

Video generation relies on movement. Specify actions, speeds, and transitions—such as “walking slowly,” “rapid transitions,” or “hair blowing in the wind.”

Example:

“A dancer spinning under neon lights in slow motion, hair and dress flowing, lens flare with every turn.”

4. Specify Style and Visual Quality

Set the tone with stylistic choices like “anime-style,” “vaporwave aesthetic,” or “low-poly 3D.” For realism or clarity, mention resolution levels like “4K” or “8K.”

Example:

“Hyper-realistic 8K aerial shot of a futuristic city at night, glowing skyscrapers, cyberpunk colors, reflections on wet roads.”

5. Break Complex Scenes into Modular Shots

For detailed narratives, divide your video into shorter clips (5–10 seconds each) and stitch them together. Use consistent details for characters and environments to ensure continuity.

Example Sequence:

Prompt 1: “Close-up of a woman’s eyes opening slowly, light flickers in.”

Prompt 2: “She walks into a neon-lit alleyway, steady cam from behind, mist swirling at her feet.”

To experiment with multiple AI video models like Google Veo 3, Hailuo, and Seedance, all under the same platform, try out ImagineArt’s AI video generator.

Looking Forward

Prompt engineering is rapidly evolving alongside advances in AI and machine learning. We're heading toward a future where prompts can fluidly combine text, code, and images, which would unlock even more powerful and creative use cases.

Researchers are also working on adaptive prompts that automatically adjust based on context, enabling AI systems to respond more intelligently and intuitively.

Now that you know the essentials of prompt engineering, let's experiment and create something new with AI!