Painting with Words: How to Craft Effective Prompts

AI art. (See prompt below)

  

Introduction: Crafting Effective Prompts for AI-Generated Images

In an age where artificial intelligence can generate images from text, the words we use carry more weight than ever. A vague request like “draw a castle” may conjure thousands of results, none of them matching your mental picture. Why? Because much like in art itself, the devil is in the detail. When we were children, teachers often asked us to describe a person or a landscape. The exercise was meant to sharpen our perception. The same principle applies today: the more accurately you can see with your mind’s eye, the more precisely you can say what you want — and that’s exactly what a machine needs.

This article aims to bridge the intuitive process of imagining with the discipline of visual analysis. By borrowing tools from the painter’s vocabulary — composition, form, tone, colour, and subject-matter — you can learn to craft prompts that don’t merely describe an image, but construct it. As John Berger once wrote, “The relation between what we see and what we know is never settled.” Writing a good prompt begins with learning to see.

Learning to See: Five Foundations of Visual Grammar

Before you can build an image with words, it helps to understand how painters structure their pictures.

Composition is the architecture of the painting — how elements are arranged and how your eye moves across the canvas. Da Vinci’s The Last Supper offers a textbook example: the figures are aligned horizontally, converging toward the central Christ figure through clear linear perspective. When crafting a prompt, mention spatial layout: “symmetrical composition,” “diagonal lines,” or “crowded foreground” give the AI direction.

Form refers to how three-dimensional the elements appear. Is the image flat, or do figures have volume and solidity? Caravaggio’s use of chiaroscuro models form through dramatic contrasts of light and shadow. To evoke this effect, a prompt might include: “volumetric figures,” “realistic anatomy,” or “sculptural rendering.”

Tone concerns the interplay of light and dark. Rembrandt’s portraits are rich in tonal depth, often enveloping subjects in shadow while spotlighting key features. In prompts, think about mood and contrast: “high tonal contrast,” “soft shadows,” or “dim candlelight illumination.”

Colour can serve either expressive or structural functions. Mondrian uses primary colours to create rigid structure; Van Gogh’s vibrant palette, in contrast, expresses emotion and energy. Clarify the role of colour in your prompt: is it symbolic, emotional, muted, or vivid?

Subject-matter may be literal, suggestive, or entirely absent. Classical art focused on religious and mythological scenes; modern abstraction often eliminates subject altogether. AI can interpret both. Specify whether you want a landscape, a narrative scene, or simply “a composition with no recognizable objects.”

Style, Medium, and Perspective

To deepen the prompt, reference style and medium. Is the image to be realistic, impressionistic, or surreal? Neoclassicism (e.g., David) emphasizes clarity, symmetry, and fine lines. Impressionism (Monet) is more ephemeral, using loose brushstrokes and shimmering light. Abstract art (Kandinsky, Pollock) breaks form entirely.

Medium also plays a role: oil paintings appear rich and layered; watercolor is soft and translucent; woodcuts are bold and graphic. Mentioning the medium — “charcoal drawing,” “ink wash,” “digital vector art” — tells the AI what texture or finish to emulate.

Perspective is another important cue. Renaissance painters like Masaccio used single-point perspective to simulate depth. Cubists like Picasso shattered space into angular fragments. Phrases like “flat perspective,” “birds-eye view,” or “fragmented geometry” give spatial clarity to your instructions.

From Vague to Vivid: Prompting as a Visual Art

Consider these two prompts:

• “A woman sitting in a garden.”
• “A neoclassical oil painting of a seated woman in a formal French garden, soft morning light, symmetrical composition, pale green and cream tones, realistic form, calm expression, background foliage rendered with delicate detail.”

The second version is not only more evocative — it gives the AI a concrete framework. You're not just asking for an image; you’re directing a visual production. Similarly, compare:

• “An abstract painting.”
• “A large-scale abstract acrylic painting with warm swirling brushstrokes, dominated by circular forms and energetic motion, no discernible subject, expressive use of burnt orange and crimson.”

By referencing specific visual elements — tone, movement, palette — the prompt becomes a design document. This is how you "paint with words."

Beyond Description: Culture and Constraints

Even the most detailed prompts are interpreted through the lens of the AI’s training data. Many systems have been trained primarily on Western-centric images, which means phrases like “a royal palace” may default to European styles unless specified otherwise. Prompting isn’t just visual — it’s also cultural. To guide the AI effectively, you may need to specify: “a Mughal palace with domes and red sandstone,” or “imperial Chinese design with sweeping tiled roofs.”

In addition to what you include, consider what you want to exclude. Advanced systems like Stable Diffusion allow for negative prompting — instructions about what not to generate. For example, if you want a clean composition without text or watermarks, you might add: “no text, no logos, no watermarks.” Negative prompts help refine results by ruling out common distractions or stylistic artifacts.

Conclusion: From Seeing to Saying

Crafting a strong prompt for image generation isn’t about verbosity — it’s about vision. The clearer your mental image, the more effectively you can guide the AI. Just as painters compose, shade, and structure their works with care, prompt writers must learn to see before they speak. “You can’t teach people to draw,” said David Hockney, “you can only teach them to see.”

And so it is with words. The goal isn’t just to describe, but to design. Whether you’re conjuring a Rembrandt or a Rothko, it all starts with how you frame the picture in your mind — and how well you translate that into language. In this new collaboration between human and machine, words function as brushes, and the screen as a canvas.

Practical example:

A cozy living room in the early evening, seen from an over-the-shoulder perspective. A young person sits cross-legged on a plush sofa, focused on a laptop. Warm ambient lighting creates a gentle contrast of light and shadow, establishing a calm, focused tone. The composition centers the figure, balanced by a potted plant on the left and a bookshelf on the right. The form is realistic and volumetric, with a strong sense of three-dimensional space. Rendered in a digital style with clean lines and polished textures, the scene conveys a modern, creative atmosphere. The laptop screen shows a vivid digital illustration of an orange-and-white kitten playing with a blue butterfly in a sunlit garden, offering a contrast in tone and colour. The colour palette features earthy shades (ochres, browns, soft greens) in the room and brighter, saturated hues on the screen to highlight imagination and artistic engagement.

Bibliography

Berger, John. Ways of Seeing. London: Penguin Books, 1972.

Elkins, James. How to Use Your Eyes. New York: Routledge, 2000.

Manovich, Lev. The Language of New Media. Cambridge, MA: MIT Press, 2001.

McCormack, Jon, and Mark d’Inverno, eds. Computers and Creativity. Berlin: Springer, 2012.

Mitchell, W. J. T. Picture Theory: Essays on Verbal and Visual Representation. Chicago: University of Chicago Press, 1994.