AI Image Generation Toolkit for Product Teams

Define the creative sandbox

Consistency is the enemy of generative AI. Without strict controls, Midjourney will give you a photorealistic photo one minute and a cartoon the next. Before touching a model, I collect brand palettes, typography specs, and composition rules.

These become our 'Negative' and 'Positive' prompts. We effectively program the AI to stay within our brand guidelines by explicitly forbidding styles that clash with our aesthetic. It's like setting up a style guide, but for a neural network.

Tools I rely on: Specificity vs Creativity

Midjourney is my choice for conceptual mood boards because it excels at lighting, texture, and abstract creativity. It's the 'Concept Artist'. When I need pixel-perfect UI fidelity, I move to tools like Uizard or Figma’s new AI features.

For production assets where I need exact control over composition, I leverage Stable Diffusion with ControlNet. This allows me to sketch a rough wireframe or pose and force the AI to render over that exact skeleton, ensuring the layout matches our grid system.

• ▹Midjourney: art direction and cinematic hero shots
• ▹Ideogram / DALL·E 3: UI scaffolding with high text legibility
• ▹Stable Diffusion + ControlNet: on-brand variants at scale with layout control

Post-processing is mandatory

AI art is never 'Done' out of the box. Every render goes through a 'human polish' pass in Photoshop. We fix the weird hands, correct lighting artifacts, and ensure aspect ratios are web-ready.

I also keep a legal checklist to verify licensing and watermark removal before assets move downstream. We fundamentally treat AI images as 'stock photography bases'—raw material that needs to be refined, not finished products.