Advanced AI Prompting for Consistent Illustrations

Advanced AI Prompting for Consistent Illustrations

Using the picture of the girl on the home page as the reference image.

Prompt: The same girl, in a blue dress, now sitting in a park on a sunny day. Graffiti style, spray paint texture, urban street art, bold mural look.

You’ve crafted a beautiful children’s book story, and AI is helping you bring it to life. Then it happens: on page one, your fox wears a yellow scarf. On page two, it’s blue. By page three, the fox doesn’t even look like the same character.

This frustration, also known as character drift, is one of the biggest challenges in AI-assisted illustration. Readers, especially children, need visual consistency to connect with characters and follow the story. Without it, your book risks looking disjointed or unprofessional.

The good news is that with advanced prompting techniques, you can stabilise your illustrations and keep your characters accurate from the first page to the last. In this article, we’ll explore four methods: reference images, seed numbers, specialised consistency tools, and custom training.


Image of Chinese girl in orange summer dress


The Power of a Visual Anchor

One of the most accessible techniques is using reference images. By uploading an existing picture of your character, you provide the AI with a visual anchor, something to refer to, rather than asking it to start from scratch every time.

This is often called an “image-to-image workflow.”

Here’s how it works in simple terms:

  1. You generate or create an illustration you like (say, your fox character on the first page).
  2. Instead of typing only text prompts for the next scene, you also upload that fox image as a guide.
  3. The AI looks at your uploaded image and then adjusts it according to the new instructions you give in your prompt (for example: “same fox, but sitting under a tree, holding a book, watercolour style”).

Because the AI has both your words and the visual example, it’s far more likely to keep important details like the fox’s fur colour, clothing, and overall look consistent from page to page.

Tools that support this:

  • Adobe Firefly (in Adobe Express) → “Generative Match” or “Image-to-Image” lets you use an uploaded style or character as a base.
  • Canva AI → lets you drag in a picture and refine it into a new scene with text prompts.
  • Microsoft Designer → supports uploading a reference photo alongside your prompt to guide the new image.

👉 Think of this as giving the AI a photo ID card for your character. Each time you create a new illustration, you show the ID card and say, “Same character, new setting.”

Sample Prompts:

  1. Upload your fox character as a reference, then prompt: “Use this character reference. The same fox sitting under a tree, holding a book, watercolour style.”
  2. Upload your girl in a yellow dress, then prompt: “The same girl, now playing with butterflies in a meadow, digital children’s book style.”

Stabilising Your Style: The Role of Seed Numbers

Some platforms, like MidJourney and Stable Diffusion, let you set a seed number. Think of it like DNA: the seed is the starting point the AI uses to generate an image.

Why it helps: If you reuse the same seed, you can stabilise overall composition and style. It won’t guarantee pixel-perfect consistency, but it keeps the feel of your illustrations cohesive.

Important note: Not all tools support seed numbers — for example, DALL·E in ChatGPT doesn’t. Always check what’s available in your chosen platform.

Sample Prompt (MidJourney):

/imagine A friendly dragon flying above a medieval village, watercolour storybook style —seed 12345

Levelling Up with Specialised Consistency Tools

For authors creating longer books or planning a series, specialised tools can save hours of frustration. Platforms like Recraft.ai, ConsistentCharacter.ai, and Dzine.ai are designed for one purpose: character continuity.

These tools allow you to “lock in” a character’s design and then generate new scenes or poses without losing their identity. Some even have features like expression editors or action editors.

Sample Prompts:

1. “My locked-in rabbit character, now riding a bicycle in a sunny park.”

2. “The same bear in pyjamas, brushing his teeth at night.”

Advanced Workflows: A Glimpse into LoRA Training

For creators planning multiple books with recurring characters, the most advanced option is LoRA (Low-Rank Adapter) training. This technique involves training a mini-model specifically on your character.

LoRA offers near-perfect consistency, encoding your character’s identity at a deeper level than simple prompting.

But here’s the catch: LoRA is technical, time-intensive, and not necessary for beginners. If you’re creating a single book, reference images and consistency tools will usually be enough. Think of LoRA as the “professional studio” option, best suited for power users.

🔒 Pro Tip: What is LoRA Training?

You may hear people discuss LoRA (Low-Rank Adapter) training as the ultimate method for maintaining character consistency. Here’s what it really means:

  • In plain English, LoRA is like giving your AI a custom memory chip for your character. Instead of starting fresh with every prompt, the AI learns your fox, girl, or dragon in detail and can reproduce them reliably.
  • How it works: You collect 10–30 images of your character, feed them into a training tool, and the system creates a lightweight file (a LoRA) that plugs into your AI generator like Stable Diffusion or those that support custom models. From then on, you can prompt with a tag like <mycharacter_lora> and the AI will remember what they look like.
  • Why it’s powerful: It offers near-perfect consistency across dozens or even hundreds of images. Great for authors making a series of books.
  • Why it’s not for everyone: LoRA training takes time, technical setup, and usually a powerful computer or cloud service. Most first-time authors don’t need it — reference images and consistency tools will already solve most problems.

👉 Think of LoRA as the “professional studio” option. If you’re just starting, don’t worry about it. But if you ever decide to publish multiple books with recurring characters, it might be worth exploring.

Key Takeaways

  • Character drift can be solved.
  • Reference images are the easiest step for immediate consistency.
  • Seed numbers help stabilise style and tone (if your platform supports them).
  • Specialised tools give near-perfect continuity for larger projects.
  • LoRA training is for advanced users who need maximum control.

FAQs

Q: Do I need advanced tools to keep characters consistent?

A: Not always. For simple books, repeating the same prompt and style phrase may be enough.

Q: Which tool is best for character consistency?

A: Recraft.ai and ConsistentCharacter.ai are purpose-built for this. Canva and Firefly also handle basic consistency when guided well.

Q: Is LoRA training necessary?

A: Only if you plan to build a series with the same characters. For a single book, reference images and specialised tools are more than enough.

Staying in Control of Your Story’s Visuals

AI illustration can stumble when it comes to consistency, but that doesn’t mean you’re powerless. With the proper techniques, you stay firmly in control of your characters and your story.

Start small: try reference images. Experiment with seed numbers if your platform supports them. And when you’re ready, explore specialised tools to take your visuals to the next level.

References

Disclaimer

The information in this article is for general educational purposes only. AI tools evolve quickly, and results may vary depending on the platform, version, and your specific use case. Always review, refine, and validate your AI-generated content before publishing.