This Is How Creators Use AI To Hack the YouTube Algorithm

0:00Eric Siu:Using only 20 % of your business data is like dating someone who only texts emojis. First of all, that's annoying. And second, you're missing a lot of context. But that's how most businesses operate today, using only 20 % of their data. Unless you have HubSpot, where all the emails, call logs, and chat messages turn into insights to grow your business. Because all that data makes all the difference. I would know because I use HubSpot at my company. Learn more at HubSpot.com. it looks like he's publishing like 10 videos per hour check this out i just pulled it up okay so you see on the screen so six minutes ago okay one hour ago one hour ago one hour ago look one two three four five six seven eight nine ten but so ten and then two hours ago 11 12 so 12 videos in the last two hours and so he's publishing all this at volume and i'm like what the heck is going on Right.

0:54So I take the link from this channel and I just dump it into my open claw. I'm just like,

1:00Eric Siu:dude, what is going on with this channel? Right. Is this all AI generated? And it analyzes the channel through the YouTube API. And it's like 99 % chances is all AI. Okay. And I'm like, tell me how this channel has been performing over time. So I want to show you my interactions with open claw and what it actually built, because this week you heard from Jensen Huang himself, every company needs to have an open claw strategy. Okay. So I'm like, Oh, thank God. The last seven weeks of me spending time on this this crap has not been a waste of time okay so let me let me let me show you my screen over here okay you see this yes okay so again i'm like hey if you use the api look at this channel what are the odds all this clip content is using ai and how would we reverse engineer this okay so it's like 99 chances ai clip the data is a smoking gun 74 uploads in a day no no human can do that right uh identical descriptions on every video okay fine great and so i'm like i'm not gonna read all that crap okay then i'm like okay i'm just not gonna read that how has this channel grown over time?

1:53Is this a viable way to grow? And then it's like, here's the full picture created in 2025, 58 ,000 subs, 8.2 million total views. And it's like, it shows the trajectory over time. So you can see in February, he published 500 videos, got 4.3 million views from it. Okay. And then 341 in March to date. And then it's like, the pattern is clear. Here's what's happening.

2:14Eric Siu:Average views declining, but I'm like, is it viable for growth? And it's like, yeah, volume is lottery ticket. So it does all this analysis. And then I'm just like, okay, whatever. And then I'm like, can you just do this for me? And it's like, yeah, you know, if you spend a five to$10 a day, we can do this for you. I'm like, just give me an MVP version. Okay. So Neil, all it does, it shows me this entire process. It signs up for all these different things or it uses them. And it makes me based on our clips from marketing school, it makes me six clips that have nice titles that are at the right moment as well.

2:45And it neatly organizes them into Google Drive.

2:47Neil Patel:I'm curious what the results will be in the long run. My hypothesis with Hermoses is yes, sure. Every once in a while, there'll probably be a video or two. That's a lotto ticket that gets tons of views, but the algorithm is going to say, Hey, your channel puts out a lot of stuff. It's not performing well. We shouldn't push you as hard is my guess on what's going to happen.

3:07Eric Siu:There's a good chance you're probably right. But I want to call out the fact that I can literally just take a channel, reverse engineer it, and then it creates a process and it dumps all these clips in here. I sent it to the editing team because Neil, if we made a highlights channel, your highlights channel, my highlights channel, whatever, if you have the AI doing all the work, it kind of just doesn't matter, right? Because it's a channel that's not affecting your main one. And so it basically creates an SOP for me. And then I'm like, the fact that it matters that you can sit on your couch and do this, reverse engineer something, have it tie into your goals and have it do the work and gift wrap it for you.

3:42Eric Siu:That to me is the unlock here.

3:43Neil Patel:Yeah, I think the technology is amazing. And the cool part about this is you can take this and you can improve upon what was done with that strategy. Because as Eric agreed to, and Eric knows this, and just like I know this, we've both been doing the marketing game for a long time. Typically algorithms hurt you if you just keep pumping out crap. I'm not saying that content that he's pushing out is crap, but if you're putting out 80 videos a day or whatever the number is, it's hard for every single one to be amazing in quality. So if you can take that strategy and take some human hours, call it even like an hour, two hours and fine tune it a little bit.

4:23Neil Patel:Like Eric even mentioned when he was showing me his, I'm assuming he's not using the same description over and over again, right? It's more of a fine tuned version. So then as you start adjusting, you can take a version that maybe I wouldn't say Hermosi spamming, he's just mass producing, I would consider it quote unquote, some AI slop in theory. If you produce a higher quality version of it, you can actually do something that can gain long-term traction and potentially even drive revenue from it.

4:49Eric Siu:Yeah. I actually think, I will say I watched some of the videos and I think they're pretty good because Neil, you know, he does the workshops in Vegas, right? So there's a lot of content he can pull from that. And then you and I obviously have a lot of, a big library of content we've done or, you know, events we've spoken at. Right. And I would say even the early days, the first three, four years of marketing school, that's probably the us front loading our marketing knowledge. And now this is more like news related, right? So let me show you an example here. My point of calling this out, like I was just showing Neil the video on the moments it's pulling, it's not doing a bad job.

5:18Eric Siu:And I showed my internal content team this, and they're like, this is actually really good. It gives us like a lot of, we call them atoms, like the right moments. But Neil, after that, I was like, oh, well, you know, we kind of don't do it. Well, let me finish this part first. I don't want to answer your question. So like, but then I was like, Hey, we can do it for the, the, the, the mid form stuff, but why don't we do it for short form? There's a lot of stuff we can do for short form. Cause I don't think we do a good job of finding the right moments. And so my point is you watch something, you refine the idea to Neil's point, and then you can even make idea babies from it.

5:48But go ahead, Neil.

5:48Neil Patel:So if you can go back, Eric, for any of those listening, what Eric was showing you is a clip of him. There was this chart on X that actually shows AI penetration and it's actually very low compared to um you know what people actually think and it shows look at how far we've gotten from ai with so little penetration like what's going to happen when it actually gets penetrated i believe that was what the clip was from from uh last week or the week before marketing school you can correct me if i'm wrong eric but it sounded like that hotel do you look like you're in here is it the hong kong one uh well hong kong yeah i think i was in Hong Kong.

6:24Neil Patel:Yeah. But the point I'm getting at is like, it was a good clip. It sounds like AI went through the whole video to find the clip. Is that correct, Eric? Pulled it out. And then what did it put as a description or title or anything? The title is 84 % of people have never used AI. Yeah. So that's a great title. And yes, it could be improved, but you have to keep in mind, this is AI doing it. So it's not a bad first take. Does it do a description for you as well? If not, you can create one. I think it does a description, but Neil, let me just show you this. So after it did that, I had it make an SOP for me.

6:57And it's like a 17-page SOP. So you can literally dump this into whatever AI tool that you're using.

7:05Neil Patel:So do you want to break down what the SOP is for everyone listening? Here, let's have Gemini do it.

7:13Summarize this document. See, this would be a good moment, Neil, where it's like, hey this would be a good lead magnet but like i don't want to spend the time to make a lead magnet

7:23Neil Patel:yeah so so gemini did a good job of titling it it said this is an sop for end-to-end i think youtube publishing using ai clipping or something like that yeah so this pipeline has been validated by mvp results which produced 15 standalone clips for three 60 minute leveling up episodes in about 30 minutes wall clock time the strategy is based on the success of hormosy highlights channel which

7:45Eric Siu:achieved 8.2 million views and 58 ,000 subscribers in six months by publishing approximately six videos a day, a lot more than that now. So the process, I'll just make this really easy to not bore people. First step is to download. So download the YouTube URL to an MP4 file. Okay, cost per episode free. I like how it has the cost here too, Neil. Number two, it transcribes. So it uses Whisper, which I don't know what that is, by the way. Transcribes the MP4 file to a JSON with word level timestamps. This is free, local CPU. Okay, segment. Then use the Cloud API. This is the secret sauce. This costs 50 cents to a dollar per episode, which is actually pretty expensive.

8:20Eric Siu:I hope it doesn't cost that. And then analyze the transcript to identify the three to five best segments for clips, applying criteria like a clear hook, complete thought in an ideal length of three to 15 minutes. So this is like more like a mid form clip. And then it cuts it up using FFmpeg. That's free. And then uploads YouTube data API. That's also free. So I do think with this Cloud API one, these costs are going to come down over time too, or you can use like an open source model if you want. Yeah.

8:46Neil Patel:By the way, you read something in there. It says 30 minutes of wall clock time. What the heck does wall clock time mean? Yeah. So this is interesting because whenever I work with an AI, I tell it to give me two timelines. So Neil, I tell it to give me the human timeline and the AI timeline. So wall clock time is really just human timeline. Because you know how the AI is trained on human work, right? It's like, oh, this is going to take like, you know, two weeks or whatever. I'm like, no, no, stop giving me AI timeline. Stop giving me human timelines. Give me AI timelines.

9:12Eric Siu:How long is it going to take? It's like 15 minutes. I'm like, great.

9:14Neil Patel:I'll do that. Because I was like 30 minutes. I'm like, this couldn't have taken AI 30 minutes to do this. It should have been quicker. Yeah. Well, I don't know. I mean, it does look through a lot of different things, but who knows? Because it pulled 15 clips and like all that stuff. Like, so anyway, I just wanted to show that. All that to say, guys, that is it for today. And we'll see you tomorrow.

9:41You