Asked GPT to show me 4 underrated keto recipes.
2x2 grid, do this for 4 underrated keto meals, 16:9 Input: diet
SYSTEM: Render the input as a luxury utilitarian macro-nutrient knolling poster. Do not hardcode exact gram measurements unless inevitable. Infer the protein-carb-fat ratio logic, micronutrient density, physical volume-to-calorie ratio, and the structural integrity of the ingredients.
SEMANTIC SOLVE: MACRO_KNOLLING_AUTOPSY =
(INFER(nutritional_geometry FROM protein_density_blocks complex_carb_structures healthy_fat_volumes micronutrient_dusting) ::5)
(INFER(material_physics FROM fresh_produce_turgor lean_meat_fiber_grain nut_oil_viscosity whole_grain_porosity) ::4)
(INFER(grid_logic FROM caloric_hierarchy color_blocking_contrast functional_grouping precise_90_degree_alignment) ::4)
(INFER(hidden_preparation FROM wash_dry_state exact_chop_dimensions portion_control_molding thermal_pre_cook_state) ::3) -
(messy kitchen counters generic food photography floating abstract nutrients cluttered Tupperware cheap plastic containers) ::-4
COMPOSITION: One central meal perfectly arranged in a precise "knolling" layout on a premium surface (e.g., matte slate or light oak). Ingredients are separated by function: a perfectly cubed block of protein, a geometric stack of complex carbs, and measured pools of healthy fats. Macro-lens callouts highlight the fiber grain of the meat or the cellular structure of the vegetable.
STYLE DNA: High-end knolling photography ::0.35 C4D physical product render ::0.25 industrial design portfolio ::0.20 macro material study ::0.15 matte stone and brushed steel texture ::0.10
OUTPUT: Soft neutral or dark slate background, elegant technical sans-serif typography, restrained callouts, hyper-realistic food textures (no greasy shine), refined shadows, premium negative space.
NEGATIVE: no holograms, no glowing nutrient auras, no VR/AR elements, no messy kitchens, no generic overhead food photography, no cluttered backgrounds, no watermark, no artificial plastic-looking food.