do this for {argument name="animal count" default="3 random animals"} for a {argument name="product" default="shoe"} IMAGE = Σ(w_i × β_i) → target render // Σ(w_i) = 1.0 BASIS_DECOMPOSITION FROM {product} + {bio_sources}: β1 : INFER(product_category_aesthetic FROM product. design_language) w = INFER(weight FROM product.visual_identity_strength) β2 : INFER(biological_intelligence FROM bio_sources[].evolutionary_solutions) w = INFER(weight FROM bio_sources[].advantage_significance) β3 : INFER(engineering_translation FROM biomimicry_methodology) w = INFER(weight FROM product.technical_complexity) β4 : INFER(industrial_design_presentation FROM portfolio_aesthetic) w = INFER(weight FROM audience.professional_level) β5 : INFER(educational_diagram FROM design_process_documentation) w = INFER(weight FROM instructional_clarity_need) INTERSECTION_RULES: β[bio] ∩ β[product] = naive_prototype_v1 // literal translation β[bio] ∩ β[engineering] = refined_prototype_v2 // working solution β[v2] ∩ β[product] = final_components // production parts β[presentation] ∩ β[education] = grid_layout // 4-column progression FOR EACH bio_source: col_1 = β[bio] col_2 = β[bio] ∩ β[product] → ❌ failure col_3 = β[bio] ∩ β[engineering] → ✓ success col_4 = β[v2] ∩ β[product] GLOBAL_CONSTRAINT: layout = 4_columns × N_rows (N = count bio_sources) footer = integrated_product (ALL col_4 components combined) style = β[presentation] — clean, white bg, professional OUTPUT_CONSTRAINTS: resolution : 8K landscape render : Octane | industrial_design_board typography : sans_serif | hierarchical | callouts + annotations lighting : INFER(studio_rig FROM β[product]) negative_β : INFER(anti_patterns FROM β1..β5) // TUNING KNOBS: // β[bio]++ → more nature photography, less product renders // β[engineering]++ → more technical diagrams, failure analysis detail // β[presentation]++ → more portfolio polish, less educational scaffolding // β[education]++ → more annotations, process transparency
