VIRAL Designs in SECONDS: The AI Design Hack!

About this video

The creator tests Ideogram 3.0 for print-on-demand and argues its main advance is understanding short prompts better, especially through style reference. His workflow starts with research on Amazon Hot New Releases to find a niche with proven demand, rather than copying a bestseller directly. He takes a trending ’everyone is welcome here’ concept, asks ChatGPT for five similar-but-different ideas, and picks ’love unites us all.’ In Ideogram he uploads the original design as a style reference, keeps his own prompt very short, and adds a detail such as different colored hands, letting the reference supply the look. He repeats the method with a bunny found in the same research, using a short prompt about a cool rabbit in a hoodie and sunglasses, then refines it in Ideogram’s canvas with extend and magic fill to add text such as ‘rabbit life’ and a carrot, and to upscale, remove the background, or download a PNG. He also compares the same prompt in model 2.0 versus 3.0 and says 3.0 feels a notch better at reading the reference and producing realistic, usable results, while noting sellers still have access to the older models if they prefer them.

Key takeaways

• Use a proven trending design as a style reference in Ideogram, not as something to copy outright
• Ask ChatGPT for several similar-but-original variations, then build from the strongest new phrase or concept
• Keep Ideogram prompts short when using style reference, adding only the key differing detail you want changed
• Refine a chosen image inside Ideogram with remix, upscale, extend, magic fill, and background removal before downloading
• Test the same prompt across Ideogram versions, since the creator says 3.0 understood references better than 2.0 in his comparison

Episode details: published March 28, 2025 · 14:44 long. Summary written by Self Growth Videos from the episode itself. Business results and any income figures mentioned are RJ Martinez’s own claims, shared for education — they are not typical or guaranteed.

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