Step-by-step: How I Create a Garden Visualization Prompt from Scratch

My journey in landscape design began long before the advent of artificial intelligence, but today I see it as a powerful tool. Especially when it comes to visualizing ideas. From my own experience, I've learned that the quality of the result directly depends on how precisely you can "speak" to the neural network. Creating an effective prompt isn't just a collection of words; it's the art of translating your vision into a language understandable by a machine.

Understanding the Task and Source Data

Before I start writing, I always ask myself: what exactly do I want to achieve? This could be a concept for a 10-15 are plot, a detailed coniferous corner measuring 15-20 m², or a visualization of an entrance group. I gather all available information: plot dimensions, its orientation to cardinal directions, existing structures, terrain, client preferences for style, plants, and functional zones. This helps me form a "database" for the prompt. For example, if the plot is on a slope, I immediately think about terracing or a drainage system. The lack of a clear objective is a common mistake that leads to vague and irrelevant results from the AI.

Structure of an Ideal Prompt: Key Blocks

For me, a prompt is not a single text, but a set of interconnected blocks, each serving its own function:

1. Subject: I clearly define what exactly we are visualizing: "Private garden landscape design," "Courtyard visualization."
2. Context and Description: I specify where the garden is located (city, suburb, forest area), its size, and features (e.g., "plot with a lake view," "Japanese-style garden"). This sets the overall framework.
3. Key Elements: I list the main objects and zones: "recreation area with a gazebo," "decorative pond," "fruit garden," "natural stone path 1.2 meters wide."
4. Style and Mood: I describe the desired aesthetic: "Modern minimalism," "Provence," "natural landscape," "cozy atmosphere," "sunny day," "morning light."
5. Technical Details: I clarify image requirements: "Photorealistic visualization," "high resolution," "rendering," "3D model." This helps the AI understand what the final file should look like.

Detailing Garden Elements: From General to Specific

After the general structure, I move on to details. What specific plants? "Coniferous trees (thujas, junipers), deciduous shrubs (spiraeas, hydrangeas), perennial flowers (lavender, roses)." What materials? "Wooden terrace," "stone boulders," "rolled lawn." Don't be afraid to be specific. Compare: "flowers" and "clusters of lavender and roses in soft hues." The latter will yield a much more predictable result. I even discussed how I explain what a coniferous garden corner is to a neural network in one of my articles: How I Explain to AI What a Coniferous Garden Corner Is.

Setting Style, Lighting, and Angle

This is one of the most important blocks for achieving the desired atmosphere and conveying the project's mood. I often specify the time of day ("sunset," "morning"), weather conditions ("clear day," "after rain"), and type of lighting ("soft diffused light," "contrasting shadows"). The angle also plays a key role: "bird's-eye view," "eye level," "close-up of a floral composition." Add keywords describing image quality: "photorealistic," "high detail," "HDR," "8K," to get the highest quality result.

Using Negative Prompts

Sometimes it's easier to tell the AI what I don't want to see. This is a powerful tool for cleaning up results from undesirable elements that could spoil the overall picture. Examples: "no people," "no clutter," "no plastic elements," "no unnatural colors," "no blur," "no distortions." This helps narrow the neural network's interpretation range and avoid absurd or irrelevant details that might appear due to the ambiguity of a positive prompt.

Common Mistakes and How to Avoid Them

• Lack of specificity: "Beautiful garden" is too general. The AI simply "fantasizes," and the result can differ significantly from your expectations.
• Contradictory requests: "Minimalist garden with an abundance of bright flowers and sculptures" — this confuses the neural network, and it won't be able to perform the task effectively.
• Overly long and complex prompt: Sometimes an excess of information also harms. It's better to break down a complex task into several prompts or iterations, gradually adding details.
• Lack of iterations: Rarely does the first prompt yield a perfect result. I always allocate 5-10 minutes for each iteration to refine the prompt; this significantly improves quality.

How to Plan in formspace.design

Before embarking on complex AI visualizations, I always recommend starting with clear planning. This is where formspace.design becomes an indispensable tool. In module 1.x "Plan/Zones/Objects," I can meticulously work out the functional zoning of the plot, place main objects (house, garage, gazebos, water features), and design the path network. For example, I can precisely determine that the recreation area will be 30 m², and the main path's width will be 1.5 meters. This allows me to obtain a structured foundation that will then form the basis of the prompt. Next, I can use module 2.1 "AI Concept" in formspace.design. By uploading the plot plan, I can ask the AI to generate several preliminary landscaping concepts or overall stylistic approaches. These concepts, even if not perfect, provide excellent starting points for formulating more precise prompts for external visualizers. Then, if I have photos of the existing plot, module 3.1 "Design by Photo" will help me "integrate" new elements into the real environment, which will also enrich my prompt with specific details and references. This approach significantly reduces time spent experimenting with AI, as I already have a clear understanding of the desired result and its alignment with the plan.

FAQ

Can prompts be used for an existing garden?

Absolutely. In this case, descriptions of existing elements are added to the prompt: "mature trees (oak, birch) in the northwestern part of the plot," "old brick wall," "existing stone terrace." This helps the AI organically integrate new elements into the established landscape, preserving its uniqueness.

How many details should be included in a prompt?

The optimal number of details depends on the desired result. For a general concept, 5-7 key elements are sufficient. For a photorealistic visualization of a specific area, such as a coniferous corner, I would recommend 10-15 detailed points, including plant types, materials, lighting, and angle.

How to avoid 'fantastical' solutions from AI?

To avoid unrealistic or absurd results, always specify "realistic," "photorealistic," "climate zone appropriate" in the prompt. Also, use negative prompts, for example, "no cartoonish elements," "no unnatural colors," "no objects not existing in nature."

What if the AI doesn't understand my ideas?

If the AI doesn't understand, try simplifying the prompt, breaking it into parts, or using synonyms. Adding reference images often helps. Sometimes the problem lies in too many contradictory details that the AI cannot reconcile, and these need to be eliminated.

Does the prompt language affect the result?

In most modern neural networks, the prompt language is not critically important, as they are trained on vast datasets in various languages. However, using English can yield more predictable results for some highly specialized terms, as a large portion of AI training data is in English.

Can I request multiple design options in one prompt?

Many AI tools allow generating several images from a single prompt, which effectively provides variations. For fundamentally different concepts, it's better to create separate prompts to avoid overloading the neural network and to obtain more focused, high-quality results.

What is the role of references and images?

Reference images are a powerful tool. If you want a specific style or composition, attach 2-3 high-quality examples. The AI can "learn" from them, reproducing the mood, color palette, and even texture details. This significantly increases the accuracy of the visualization and its alignment with your expectations.

Using AI in landscape design is not a replacement for creativity, but an enhancement of it. By learning to formulate prompts correctly, you will open up new horizons in visualizing ideas. My business journey, starting in the 90s when I manually kept records at "Alkar-Invest" without a single program, taught me to value automation and a systematic approach: The 90s: How I Manually Kept Records at "Alkar-Invest" Without a Single Program. Today, I apply this experience to make formspace.design a tool that will help you not only plan but also effectively communicate with the world of artificial intelligence. Try it yourself, and you will see your ideas come to life.