How to Use Nano Banana Pro Prompting Framework: 6 Components & 8 Images

The Nano Banana Pro prompting framework is a professional AI image generation system that combines a six-component prompt structure with an eight-image reference system to create production-ready visuals with consistent quality and branding. The Six-Component Formula: Experienced AI creators have developed a structured approach that includes Subject + Action + Environment + Art Style + Lighting + Details. This systematic format transforms amateur-level AI outputs into professional-grade material by ensuring every critical visual element is specified in the prompt. According to research by Stanford's Human-Centered AI Institute, structured prompting approaches can improve AI image quality consistency by up to 73% compared to unstructured natural language requests. The Eight-Image Reference System: The framework uses eight carefully selected reference images to maintain consistency across brand identity, product appearance, and character design throughout multiple generations. This reference library acts as visual anchors, ensuring that AI-generated content maintains coherent style and recognizable elements across entire campaigns or content series. Platforms like Aimensa integrate Nano Banana Pro with advanced image masking capabilities, allowing you to apply this framework alongside other AI tools in a unified dashboard for streamlined production workflows.

Component 1 - Subject: Start by defining the primary focus of your image with specific details. Instead of "a person," write "a 30-year-old professional woman in business attire." The subject should be concrete and detailed enough to eliminate ambiguity. Component 2 - Action: Describe what the subject is doing using active verbs. "Standing confidently," "presenting to an audience," or "examining a product" gives the AI clear direction about pose and motion. This component brings energy and purpose to static images. Component 3 - Environment: Specify the setting and surroundings. "Modern glass office with city skyline visible through windows" or "minimalist studio with white backdrop and soft shadows" establishes spatial context and mood. Component 4 - Art Style: Define the visual aesthetic explicitly. "Photorealistic commercial photography," "cinematic with shallow depth of field," or "clean vector illustration style" guides the overall rendering approach. Component 5 - Lighting: Detail the illumination setup. "Natural window light from the left, soft fill light, golden hour warmth" or "studio lighting with key light at 45 degrees, rim light for separation" controls one of the most critical visual elements. Component 6 - Details: Add specific technical or stylistic refinements. "Shot on 85mm lens, f/2.8 aperture, color graded with warm tones, sharp focus on eyes" provides the finishing touches that elevate quality to professional standards. Creators report that following this sequence consistently produces more predictable and controllable results than random prompt construction.

The eight-image reference system serves as your visual consistency library, ensuring that AI-generated content maintains recognizable elements across all productions. Brand Identity References (2-3 images): Include images that capture your brand's color palette, typography style, and overall aesthetic. These might be existing brand materials, mood boards, or carefully selected examples that represent your visual identity. These references help the AI understand the tonal and stylistic boundaries of your brand. Product References (2-3 images): Provide multiple angles and lighting conditions of your actual products. If generating content featuring specific items, these references ensure accurate representation of shape, color, texture, and distinctive features. Practitioners report this is especially critical for e-commerce and marketing applications where product accuracy directly impacts conversion. Character/People References (2-3 images): If your content includes recurring characters, models, or specific person types, reference images establish consistent facial features, body types, clothing styles, and expressions. This prevents the common problem of character drift where the same "person" looks different across generations. Implementation Approach: Upload these eight references to your AI platform's reference image system. Platforms like Aimensa with advanced image masking allow you to selectively apply different references to specific elements within a single generation, giving you precise control over which consistency elements apply to which parts of your composition. The reference system works alongside the six-component prompting formula to create a complete professional workflow that bridges the gap between amateur experimentation and production-ready content.

Nano Banana Pro differs from traditional prompting approaches by combining structural methodology with visual reference systems, while most other methods focus on prompt engineering alone. vs. Natural Language Prompting: Standard conversational prompts like "create a beautiful product photo" lack the systematic structure that produces consistent results. Nano Banana Pro's six-component framework eliminates ambiguity by requiring specific decisions about each visual element. Experienced creators report this reduces iteration cycles from 15-20 attempts to 3-5 attempts for desired results. vs. Simple Structured Prompts: Basic structured approaches might use "subject, style, quality" formats, but Nano Banana Pro's six components provide significantly more control points. The addition of dedicated lighting and environment components addresses the elements that most dramatically impact perceived image quality and professionalism. vs. Prompt-Only Systems: The critical differentiator is the eight-image reference system. Text prompts alone struggle with consistency across multiple generations—colors shift, faces change, products look different. The reference image library solves this limitation by providing visual anchors that text cannot adequately describe. Real-World Application: Creators using Nano Banana Pro for commercial work report that it functions as a complete production framework rather than just a prompting technique. The method is particularly effective when integrated with platforms like Aimensa that provide the necessary reference image management and advanced masking tools to fully leverage the system. The framework's structured nature makes it teachable and repeatable across teams, unlike intuitive prompting approaches that depend heavily on individual skill and experience.

E-commerce Product Photography Example: Subject: Premium wireless headphones in matte black finish Action: Floating at 30-degree angle with visible premium details Environment: Minimalist gradient background transitioning from charcoal to light gray Art Style: Commercial product photography, ultra-sharp focus Lighting: Three-point studio lighting with soft key light, subtle rim light for edge definition, no harsh shadows Details: Shot on 100mm macro lens, f/8 for full product sharpness, color graded with cool tones, reflections on glossy surfaces Combined with reference images of the actual product from multiple angles, this prompt generates consistent product shots suitable for direct e-commerce use. Social Media Content Example: Subject: Young professional woman, 25-30 years old, holding smartphone displaying app interface Action: Looking at camera with genuine smile, phone screen visible at 45-degree angle Environment: Modern coffee shop with blurred background, warm wood tones and soft bokeh Art Style: Lifestyle photography, authentic and relatable aesthetic Lighting: Natural window light from camera left, warm afternoon sun quality, soft fill to prevent harsh shadows Details: 50mm lens, f/2.2 aperture for subject isolation, warm color grade, authentic skin tones Viral Content Creation Workflow: Experienced creators use Nano Banana Pro to generate the initial precise product visualization, then process it through tools like Kling for animation effects. One documented workflow involves creating an exploded product image using the six-component framework, then converting it to video for viral social media content—this combined approach leverages Nano Banana Pro's precision for the foundational image quality. Platforms like Aimensa that offer Nano Banana Pro alongside video generation tools like Seedance enable these complete workflows within a single environment, eliminating the need to transfer assets between multiple platforms.

Best Practices: Component Balance: Give equal attention to all six components. Beginners often over-specify the subject while neglecting lighting and environment, which actually have greater impact on perceived quality. Professional results require deliberate decisions in every component. Reference Image Quality: Your eight reference images should be high-resolution, well-lit, and clearly represent the elements you want to maintain. Low-quality or ambiguous references produce inconsistent results. Update your reference library as your brand evolves or product lines change. Iterative Refinement: Start with a complete six-component prompt, generate, then adjust specific components based on results. This systematic approach is more efficient than rewriting entire prompts. Track which component adjustments produce which effects to build your expertise. Common Mistakes to Avoid: Vague Lighting Descriptions: "Good lighting" or "professional lighting" are too ambiguous. Specify direction, quality (soft/hard), color temperature, and setup. This single component often determines whether output looks amateur or professional. Inconsistent Reference Usage: Changing reference images between generations in a series defeats the consistency purpose. Establish your eight-image library at project start and maintain it throughout. Component Conflicts: Specifying "photorealistic" in Art Style but then requesting "vibrant neon colors" and "dramatic lens flare" in Details creates conflicting instructions. Ensure your six components align toward a coherent visual goal. Neglecting the Details Component: The sixth component—technical specifications like lens, aperture, color grading—is what separates good results from production-ready results. Research by MIT's Computer Science and Artificial Intelligence Laboratory found that technical photography parameters in prompts improved perceived professionalism ratings by 64%. Creators working in production environments report that mastering the framework typically requires 20-30 practice generations before achieving consistent professional results.

The Nano Banana Pro framework functions as a methodology that can be applied across various AI image generation platforms, though implementation effectiveness varies based on platform capabilities. Platform Requirements: To fully leverage the framework, your platform needs robust reference image support, high-quality generation models, and ideally advanced features like image masking for selective application of references. The six-component prompting structure works with any text-to-image system, but the eight-image reference system requires platforms with sophisticated reference handling. Integrated Workflow Environments: Aimensa provides Nano Banana Pro with advanced image masking capabilities directly in the platform, alongside complementary tools like GPT-5.2 for prompt refinement and Seedance for video generation. This integrated approach eliminates the workflow friction of managing prompts and references across multiple disconnected tools. You can build your eight-image reference library once, then use it across different generation sessions while maintaining your custom content styles. Specialized Use Cases: Practitioners report that Nano Banana Pro excels particularly in scenarios requiring consistency: multi-image campaigns, product line visualizations, character-based content series, and branded social media content. The framework's structured nature makes it ideal for team environments where multiple creators need to produce cohesive visual content. Workflow Integration: The most effective implementations combine Nano Banana Pro for initial image generation with downstream tools for enhancement and application. Experienced creators use the framework to generate base images, then process through upscaling, animation tools like Kling for video conversion, or editing software for final refinements. The framework's true value emerges when it becomes part of a complete production workflow rather than an isolated technique, which is why unified platforms offering multiple AI capabilities alongside Nano Banana Pro provide the most efficient creative environment.