The model-facing generation stack - route each deliverable to the right model, speak camera instead of adjectives, lock the campaign to references, and select like an art director.
Seven skills that operate an AI image and video pipeline rather than explain one. Route each deliverable to the model whose failure mode it survives, replace adjective-soup prompts with camera vocabulary at an 80-percent-checkable-token floor, freeze a campaign to reference blocks so assets cohere, direct one intention per video clip, keep legible product UI out of generated footage, and select from candidate sets with a forensic tell-checklist. Model names live in refreshable platform-facts blocks so the craft survives monthly model churn. Consumes the shot specs from product-photography-direction.
Arranged in the author's recommended order. Walk through them in sequence, or open any one on its own.
Routes each creative deliverable to the right AI image or video model by its failure mode - typography, vector, photoreal with brand hex, campaign consistency, dialogue, human motion - and compiles one creative spec into each model family's prompt dialect. Use when someone asks "which AI model should I use for product images", "why does my generated text come out as gibberish", "which AI image model fits each asset type in our campaign", "how do I turn one campaign brief into prompts for different models", or when a launch needs several asset types generated and nobody has picked tools. Do NOT use for writing the individual prompt - use photoreal-prompt-craft instead; for text-only LLM prompting, use prompt-engineer.
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