Advanced Guide: Fix Washed-Out Colors in AI-Generated Product Shots for E-commerce Photographers Using Claude

You are a specialist commercial photographer with 14 years of experience producing high-conversion product imagery for e-commerce brands. Help me write a product photography prompt so I can achieve accurate, punchy color output without washed-out or desaturated results. My situation: - Product category and primary material: [e.g., "ceramic kitchenware with matte glaze finish"] - Brand color palette the image must reflect: [e.g., "terracotta #C2603A, cream #F5EFE6, forest green #2D4A3E"] - Lighting setup I want to reference: [e.g., "soft north-facing window light" / "overhead softbox, single fill card"] - Background style required: [e.g., "seamless white" / "textured linen in cream" / "dark slate surface"] - Final use — platform and dimensions: [e.g., "Shopify hero image, 1200x1200px square"] - Biggest color problem in current generations: [e.g., "greens shift teal, reds go orange, shadows lose hue"] - Reference photographer or studio aesthetic: [e.g., "Kinfolk editorial flatlay" / "still life realism, Dutch Golden Age influence"] Deliver: 1. A full product photography prompt structured in three blocks — subject description, lighting specification, and background and surface detail 2. A color accuracy clause to append to any prompt that forces the model to preserve specific hex-adjacent hues rather than defaulting to generic saturation 3. Five negative prompt terms targeting the exact causes of color washout in studio-style AI image generation 4. A lighting descriptor library of eight phrases covering soft, hard, directional, and diffused setups — ready to swap in and out per product material 5. A prompt variation for reflective surfaces (glass, ceramic glaze, polished metal) that prevents blown highlights while keeping color integrity 6. A post-generation evaluation rubric with four checkpoints to assess whether color, shadow depth, and surface texture meet e-commerce platform standards 7. A prompt iteration log template — tracks what changed between versions so color improvements are reproducible, not accidental 8. Two subject-line-style prompt openers that establish the camera perspective and shooting distance before color and lighting details are added **Write every prompt component assuming it will be used by a photographer who understands light but has never written an AI prompt — bridge the gap between photography vocabulary and model instruction language.**