7 hidden sources for static ads that actually scale ($100mm+ in ads used this)

1 Apr 2026 · 31 min
30:55

In this video Luke Iha, founder of the Genesis program, presents a comprehensive system for generating large volumes of high‑performing static ad creatives. He first argues that static ads are an undervalued yet cost‑effective and fast‑testing asset that can be scaled more aggressively than video, especially when integrated into a full‑funnel strategy (static → video → funnel). He outlines two broad ad categories based on consumer awareness levels – unaware/problem‑aware versus solution‑aware/product‑aware – and explains how each requires different creative styles (curiosity‑driven in‑feed vs. product‑centric). For solution‑aware/product‑aware ads he recommends a simple workflow: select 10‑12 proven static‑ad formats (side‑by‑side, infographic, comparison, collage, etc.), feed existing copy into a suite of AI “bots” (Claude‑based bots in Genesis, Poe.com, OpenClaw) that output image prompts optimized for models like Midjourney or NanoBanana Pro, then iterate and select the best concepts. The core of the presentation is the SCRAWL framework, an acronym for seven distinct sources of static‑ad ideas: 1. Swipes – mining competitor ads from Meta Ad Library. 2. Copy‑Derived – extracting visual concepts directly from the ad copy. 3. Reptile Triggers – applying 13 visceral “triggers” (gory, sexual, uncanny, etc.) that appeal to the reptilian brain. 4. Audience Language – mining real user comments/testimonials for concrete visual language. 5. Wild Sourcing – scouting organic content in niche communities (Facebook groups, Reddit) for attention‑grabbing imagery. 6. Loopback – analyzing patterns in your own past winning ads to reuse successful visual motifs. 7. Source – brainstorming from personal knowledge. He stresses that combining these sources with audience segmentation and awareness‑level matrices creates deep creative diversity, which platforms now reward. The video then walks through practical steps: selecting ideas, finding reference photos, reverse‑engineering prompts via Claude or other LLMs, feeding them into Midjourney or NanoBanana, adjusting aspect ratios, and iterating until the image is distinct yet on‑brand. Finally, Luke invites viewers to opt‑in for a downloadable cheat‑sheet and encourages comments.

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