“How AI in Context approaches thumbnails” by ChanaMessinger

I used an LLM to help draft this post, but I’ve edited/rewritten it extensively and endorse it. Writing up our current approach to thumbnails, which is nowhere near perfect, for easy shareability and cross-pollination of lessons. Would love to hear what other people are trying! Making thumbnails We're lucky enough to have folks at 80k with great design instincts. We work with them as well as with some external folks, but finding great people is harder than we expected. Let us know if this is something you or someone you know would be great at! We iterate way more than people expect Every video gets ~dozens of thumbnail variations, most of which are made after launch. You can see the full set of data on our IABIED thumbnails here. I believe 2/3 of our winning thumbnails (maybe all 3) were made after launch. It's pretty hard to predict ahead of time which thumbnails will do well. We launch with a few thumbnails we're excited about, a/b/c testing them We tried pre-launch testing via paid ads once, didn't correlate well, but we haven't tried super intensely We iterate from there. If one is doing well, or [...] --- Outline: (00:27) Making thumbnails (00:45) We iterate way more than people expect (02:48) What weve learned --- First published: May 8th, 2026 Source: --- Narrated by TYPE III AUDIO . --- Images from the article: Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts , or another podcast app.