Why It Matters
Consistent visual branding is a major challenge for companies adopting generative AI, and Gannon’s systematic approach demystifies how to achieve it without endless trial‑and‑error. By turning mood boards into actionable prompts, creators can produce scalable, on‑brand assets quickly, making AI‑driven design more reliable and accessible for businesses today.
Key Takeaways
- •Use mood boards as visual language for MidJourney prompts.
- •Style references improve consistency over generic mood boards.
- •Leverage personalization codes to fine‑tune brand aesthetic.
- •Combine image references and editorial keywords for higher quality outputs.
- •Iterate with AI feedback to align images with brand vibe.
Pulse Analysis
Creating brand‑level imagery with generative AI starts with a disciplined visual language. Jamie Gannon emphasizes building a mood board on Pinterest or similar platforms, then feeding those images directly into MidJourney as style references (srefs). This visual shorthand tells the model about color palettes, composition, and vibe without verbose text, dramatically reducing trial‑and‑error prompting. By treating the mood board as a language, designers can communicate complex aesthetics—like "high fashion" or "Vogue editorial"—in a single cue, ensuring the AI grasps the intended brand tone from the outset.
The next layer involves personalization codes, a semi‑automated profiling system that refines the model’s output to a specific aesthetic, such as a "late‑2025" look. Users vote on generated samples, teaching the AI which hues, contrast levels, and stylistic nuances align with their brand. Gannon also recommends leveraging external LLMs like ChatGPT to diagnose mismatches between mood boards and generated images, turning subjective feedback into actionable prompt tweaks. This iterative loop—quick generation, AI‑assisted analysis, and refined srefs—creates a repeatable workflow that scales across dozens of assets while maintaining visual cohesion.
Finally, Gannon demonstrates how to elevate prompts with editorial terminology and image references. Phrases like "day’s editorial" or "Vogue‑style macro portrait" embed industry‑specific lighting and composition cues, while dragging a reference image into the MidJourney UI anchors the composition and style. Combining these techniques with tools like Nano Banana for finer control yields crisp, brand‑consistent visuals ready for marketing decks, websites, or social media. For businesses, this systematic approach reduces design time, cuts outsourcing costs, and delivers a unified brand experience across all visual touchpoints.
Episode Description
Jamey Gannon is an AI creative director who specializes in creating consistent, beautiful brand imagery using AI tools. In this episode, Jamey demonstrates her streamlined workflow for generating cohesive brand assets using Midjourney, Nano Banana, and other AI image tools. She walks through her process of creating mood boards, using style references, developing personalization codes, and strategically iterating to achieve a consistent aesthetic. Rather than relying on complex prompts, Jamey shows how visual references and strategic shortcuts can produce better results with less effort.
What you’ll learn:
How to create effective mood boards that communicate your desired aesthetic to AI image generation tools
Why style references (SREFs) often produce more consistent results than general mood boards in Midjourney
A systematic approach to testing and refining your visual style
How to use personalization codes in Midjourney to develop your own unique aesthetic preferences
Techniques for combining image references, style references, and minimal prompting to achieve consistent brand imagery
A workflow for using Nano Banana to fix specific elements in Midjourney-generated images without extensive editing
How to package and deliver your brand imagery system to clients so they can continue generating consistent assets
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In this episode, we cover:
(00:00) Introduction to Jamey Gannon
(02:31) Creating mood boards as the foundation for AI image generation
(08:45) Using SREFs for better consistency
(11:15) Test prompts for evaluating style consistency
(12:33) The iterative process of creating and refining images
(24:28) Combining techniques for consistent brand imagery
(28:25) Scaling out your aesthetic across different subjects
(35:48) Using Nano Banana for targeted image refinements
(38:23) Creating realistic AI self-portraits for content
(43:04) Building a visual reference library for inspiration
(46:50) Troubleshooting techniques when AI isn’t cooperating
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Tools referenced:
• Midjourney: https://www.midjourney.com/
• Nano Banana: https://gemini.google/overview/image-generation/
• Flora: https://flora.ai/
• Pinterest: https://www.pinterest.com/
• Cosmos: https://www.cosmos.so/
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Other reference:
• Style references (SREFs) in Midjourney: https://docs.midjourney.com/hc/en-us/articles/32180011136653-Style-Reference
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Where to find Jamey Gannon:
Website: https://www.brand-sprints.com/links
LinkedIn: https://www.linkedin.com/in/jameygannon/
X: https://x.com/jameygannon
Instagram: https://www.instagram.com/jameygannon
Maven Course (get 10% off with this link): https://bit.ly/4b18RfM
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Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.
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