#275 · the fake podcast trick for cold email deliverability
Jack made the stacked podcast visualization; it’s a visual deck with a background image where we generate text. It’s gotten longer over time and we’ve tweaked it, though we can’t zoom out. The slides are essentially graphs. You could simply ask an AI to create a slide deck and it would do it without any special prompting.
I think it’s not a bad idea—I could funnel the Stack podcast into the workflow, although I don’t have many daily deliverables tied to work for it right now. I like to keep things related to my daily deliverables, so I’d only do it if it fit that pattern. Honestly, I’m not sure yet, but I’m open to the possibility.
Simple and straightforward: I would have AI break down long-form clips into short-form clips. I would target preferentially long-form platforms like LinkedIn, full-length X videos and X podcasts, and obviously YouTube videos like mine. I would build three major systems: a video-to-text-post converter, a video-to-static-image converter, and a video clipper. Video-to-text-post converter is pretty straightforward — we've been able to do that for a very long time — you take content that resounds within the transcript of the main piece of long-form content and cut it up for X, Instagram, whatever else. Video-to-static-image is basically the same thing, but there are really strong formats right now where people take what is said in a video transcript, cut it up into really high-ROI segments — the best parts — and turn those into notes that look handwritten. Ormozy did this, a bunch of other guys do this, it's a very common thing to do. Video clipping is where you take the transcript but also identify silences, and use both of those to feed into an AI model to cut at specific moments. You can then add effects, make the card half as tall, put yourself in the bottom half and have visuals and research on the top half. AI can actually do all this stuff now basically completely autonomously.
Yes, of course. I recommend refactoring your internal flow that generates these clips. Video processing doesn't need to take 70–90 minutes if you parallelize. For heavy workloads, people often rent a high‑core VPS (not a full supercomputer) with fast network storage, using saved configurations or code that pulls the video quickly. This lets them parallelize, run the jobs, and finish in about 5 minutes instead of 2 hours on a personal computer. To scale, turn this into a real podcast offer that saves time per client—it's easy and simple. Besides that, focus most of your time and energy on outreach, as most people do. Nick notes that there's still an overhang between what people think AI can do and what it actually can't.
I appreciate it, John Overflow AI, but I know the main channel doesn't do super well, but it kills me because the main channel only gets like 3x the total number of views that the podcast gets at this point. Isn't that crazy? Podcast is over 50 times smaller, which I think is a good segue into strategy.