Photography AI - Professional Visual Engineering Skills Framework

What problem does it solve?

This skill addresses the common failures of AI visual generation: inconsistent character identity across frames, photographic implausibility (lighting, lens, material response), and recurring artifacts like extra limbs, plastic skin, and temporal drift that break professional output quality.

Core Features & Use Cases

• Structured Prompt Engineering: The Scaffold Method to compose subject, action, lighting, lens/specs, style, and quality for predictable renders.
• Photographic Literacy: Guidance on lighting patterns, lens choice, aperture, and advanced rendering terms to produce physically believable images.
• Strategic Negation & Identity Preservation: Negative prompting patterns and seed/reference locking to prevent artifacts and maintain character continuity across generations.
• Post-Processing Workflow: Inpainting, upscaling, A/B iterative refinement, and external tool handoff for delivery-grade results.
• Agent Orchestration: Design patterns for multi-agent production pipelines with human-in-the-loop checkpoints for scale projects.
• Use Case: Produce consistent headshots for a brand campaign, orchestrate multi-scene cinematic sequences, or build production pipelines that hand off assets to color grading and upscaling tools.

Quick Start

Generate a photorealistic corporate headshot: 85mm f/2.8, Rembrandt lighting, seed 12345, preserve identity with a character reference and include a negative prompt to avoid plastic skin and extra fingers.