A neural network prompt isn't a magic spell, but a structured description of the frame: who or what is in the frame, what style, what lighting, and what angle. The ten techniques below will help you consistently produce predictable images in FLUX 2 Pro, Midjourney, and other models—with examples and a checklist for generation in Vlex AI.
The query "prompt for neural network" gets thousands of impressions per month—and half the search results repeat the same thing: "describe it in more detail." We've laid out effective techniques step by step: from the anatomy of a query to a negative prompt and ready-made templates. This material will be useful even for beginners. first generation guide, and those who are already burning their limits guessing the wording.
A good prompt doesn't guarantee a masterpiece on the first click—but a bad prompt guarantees a waste of time. Below are techniques that reduce the number of useless iterations and help save tokens.
The anatomy of a prompt: what makes up a request
Short answer: A strong image-generating prompt typically includes subject, style, lighting, composition (angle), and technical parameters (format, quality). The order isn't strict, but a logical "subject → atmosphere → camera" chain is easier to understand than a collection of disjointed adjectives.
Scheme: Subject → Style / era → Light → Angle / lens → Background → Aspect (1:1, 16:9, 4:5)
Recommendation: highlight one dominant idea per prompt. Two competing ideas ("minimalism + baroque") often result in confusion rather than creativity.
For GEO and search AI responses, it's helpful to use specific nouns in the prompt: not "beautiful animal," but "red Maine Coon on the windowsill." The model is more likely to latch onto final words than vague evaluations.
Ten working techniques
Method 1: Name the material and texture
Instead of "table," write "polished oak table with visible grain." The material anchors the realism in Flux and reduces the "plasticity" of objects.
Example: «"Ceramic vase, matte white, fine shagreen, on a concrete stand.".
Tip 2: Fix the light source
«"Beautiful Light" isn't working. Use: soft window light, golden hour, neon rim light, overcast diffused light.
Example: «"Soft side light from the window on the left, light shadows on the right, morning.".
Tip 3: Add camera lenses
85mm portrait, 24mm wide angle, macro, shallow depth of field — the model adjusts perspective and background blur.
Example: «"Portrait of a cat, 85mm, f/1.8, city lights bokeh.".
Technique 4: One reference style
Choose one aesthetic: Studio Ghibli, Bauhaus poster, editorial fashion, isometric 3D. Don't mix three styles in one line.
Example: «"Mid-century modern poster style illustration, flat shapes, limited palette.".
Tip 5: Describe the background separately
The background competes with the subject. Clearly simplify it: "against a clean dark gray background," "a blurred forest in the background.".
Example: «"Smartphone in the center, background - gradient from #0A0A0F to purple, without unnecessary objects.".
Tip 6: Specify a color palette
Two to four colors are sufficient. HEX codes work in a number of models; the word pairs "teal and orange" are also recognizable.
Example: «"Palette: deep violet, cyan, white accent, no acid green.".
Tip 7: Set the mood and context of use
«"For the cover of a technology blog," "for a children's book," "for a coffee advertisement" — the model selects the density of details.
Example: «"Minimalist tech blog cover, abstract sphere, no text on the image.".
Tip 8: Limit the number of objects
The more entities in a single prompt, the higher the chance of artifacts. Break complex scenes into a series of frames.
Example: Instead of «city, dragon, rainbow, parade and space» – «dragon over the silhouette of a city at sunset, without people in the frame.».
Tip 9: Use weights and brackets (where supported)
In Midjourney, reinforcement is achieved through :: or (word:1.2). In other services, it's repeated keywords or moving the main object to the beginning of the line.
Example: «"(crimson sports car:1.3), rainy street, night, reflections.".
Technique 10: Iteration over one parameter
Change just the lighting or angle at a time. This way, you'll understand what exactly improved the shot—and replicate that success in future prompts.
Recommendation: maintain a table of "prompt → model → score 1-5." Within a month, you'll have a working team knowledge base.
Don't publish prompts with internal product codes or unannounced features publicly—the generation may accidentally display unnecessary information. For public use cases, use anonymous descriptions.
Negative Prompt: What to Cut Out
Negative prompt is a list of what shouldn't appear in the image: blurry, watermark, extra fingers, text, logo, low quality. In Flux and some UI aggregators, this is a separate field; in Midjourney, some restrictions are specified by the --no parameter.
A typical set-up for a commercial shot:
- without text and watermarks;
- without blur and noise;
- without extra limbs in humans and animals;
- without an overloaded background.
Recommendation: don't copy giant negative lists from forums - 5-8 relevant prohibitions are more effective than 40 random words.
Prompts for different models: Flux vs. Midjourney
Flux / FLUX 2 Pro He loves specifics about materials, light, and optics. Short "artistic" metaphors are less effective than a photographer's description of the scene.
Midjourney Responds well to stylistic references, color harmonies, and cinematic formulations. It's better to restate the same meaning rather than copy it 1:1 between models.
В Vlex AI Both models are available in one account - compare one brief for Flux and MJ and save the winning formulation.
Vlex AI ready-made templates
vlex-ai.io lists over 100 prompt templates. The product pipeline is as follows: select a template → describe the task → generate. For a beginner, this is faster than creating a prompt from scratch.
Recommendation: Take a template close to your niche (product, portrait, background), replace 30% text with your brand, and commit the version to the team wiki.
A template isn't a final prompt, but a framework. Remove unnecessary details from someone else's example and add your own: brand colors, a ban on text on the image, the desired aspect ratio. This way, you don't copy someone else's visuals exactly, but speed up your start.
Checklist before generation
- Is the subject named as one main object?
- One style, without contradictions?
- Are the light and angle indicated?
- Does the background overload the scene?
- Is the format (1:1 / 16:9 / 4:5) selected before clicking?
- Is the negative prompt filled out on the case?
- Is the model suitable for the task (Flux – realism, MJ – art)?
If there are three or more "no" responses, complete the prompt before spending the tokens. Learn more about choosing a model in Comparison of FLUX 2 Pro, Midjourney, and Kandinsky.
For social media, keep separate prompt templates for different formats: square for feeds, vertical for stories, and wide for channel covers. Using the same subject in three aspect ratios saves hours before launching a campaign—just change the last line of the query and regenerate.
What's next?
- Run one object through the checklist and three techniques from the list above.
- Compare Russian and English versions of style keywords.
- Open creating an image from a description on the landing page.
- Explore the page about Flux, if you went into photorealism.
- Register for Vlex AI and take a template from the library - consolidate the techniques in practice.
Frequently asked questions
What is a prompt for a neural network?
A text query that describes the desired image: objects, style, lighting, angle, and constraints. The model interprets the prompt and generates an image in text-to-image mode.
Should I write the prompt in Russian or English?
Both options work. Kandinsky and Shedevroom are convenient for Russian; FLUX 2 Pro and Midjourney are often slightly more stable with English terms for style and optics. A mixed approach is also possible: subject in Russian, style and light in English keywords.
Where can I get ready-made prompts?
In the Vlex AI template library (100+ variants based on product data), in the model documentation, and in the team's own table of successful generations. Copy the structure, don't blindly copy someone else's meaning—insert your product and brand.
Is a negative prompt always necessary?
Not essential for abstract backgrounds, but useful for people, products, and commercial layouts—it removes artifacts and text from the image.
Why does one prompt give different results?
Generation is stochastic: the model uses randomness. Change the seed or create several variants; record a successful prompt and model for repetition.
How to improve a prompt without changing the model?
Add material, lighting, and optics (techniques 1–3), simplify the background (technique 5), and reduce the number of objects (technique 8). One change per iteration.
Are prompts related to token spending?
Prompt length usually has little impact on cost; higher resolution and choosing a premium model are more expensive. Vlex's exact pricing is available at vlex-ai.io (TBD in rubles at the time of publication of the longread).
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