B (13:05)

Before we continue, let me tell you about a podcast I love. Marketing School. Marketing legends Neil Patel and Eric Su bring you daily actionable digital marketing lessons learned from years in the trenches. Marketing School delivers bite sized marketing wisdom you can implement immediately. Whether you have a new website or you're an established business. You'll learn the latest in SEO, content marketing, social media, email marketing, conversion optimization and general online marketing strategies that work. Today. They just did a great episode called 10 SEO Lessons that Still Work in the AI Era. Listen to marketing school wherever you get your podcasts.

A (13:48)

Now let's look at the other one that you're going to get access to, which is the Lookalike one, which is like one of my favorites. The way the Lookalike one runs is I would go and say here's a data dump of my LinkedIn post. Here's a Data dump of my substack posts. Here's a data dump of my top performant X articles. Here's a data dump of my best thought leadership posts on my blog. And I would upload that messy file to this skill that you're going to get access to. And what it does is it takes that mess and if it has performance data in there, it will look at the top 30% of your best performing posts because it wants to extract winning patterns from the best performing posts. If there is no performance data in there, it will just look across the data you have given it because it can't tell which ones perform better than others. And it first of all creates a profile because it wants to work from a profile. And so let me show you the output again. In HTML, the system all works in ND files. But for the purposes of this video I wanted to be able to visually show you how this works. So it creates my substack content profile. And so what it's broken out is it's basically said, hey, like this is the winning formula. This is the top performing clusters of content. Look how cool it is here tells me the different kind of clusters of content across my substack. It talks about the structural DNA of my substack. So like typically how long as opposed to different sections, the structural type, paragraph style, embeddable prompts work really well. If you haven't checked out my substack, you should. It's awesome. The hook formula, the emotional playbook and format that works, always really important to say like what doesn't work. And so from that messy data that you have given it, it creates that profile and then it goes to take that research and gives you a bunch of ideas. And so we're going to go back here into our content system. We have these ideas. So you can see here, I ran this last night for my substack. Look at this. How good is this? Right? These are ideas for substack again, always tailored to an audience. So it picks up a content profile and will basically say what content profile do you want to use? If you remember, the content profile is the audience. And then it will say this was the winning formula. And here are ideas again. I create content. I use a lot of the content system for ideation research, first drafts and actually I have a pretty cool skill to show you that actually helps me enrich some of my content. And so here it has one about meta prompting because when it looked at my topic clusters it could see that that was a really great topic for me is like People really still want to understand how can I get more out of these models? The AI boss era. How to run a fleet of agents across your marketing team. This is a good one. Actually your AI has been agreeing with you too much. Here's how to fix it. Pod models.

B (16:46)

Wow.

A (16:46)

I replace the marketing teams. This is a really good one. We were in the era of functional teams and now we are in the era of pod models. And I think you have to structurally rethink the way you think about team structure. The 6x Gap why some marketers get insane AI results and most don't. A study of 9000 AI users find a 6x productivity between the effective and surface level AI. Wow. This is super cool. Wow. Data hook. So it tells me which they are by the way. You can see it kind of frames it up for me. AI frameworks. It's a data hook. It should be a four step tutorial. And then this is the emotional driver. How to simulate your customer's reaction before you launch it. I've done that one. So that's interesting. That's picked up that one. Why your LinkedIn prompt fails in every other channel. Okay, yeah, that's a good one. Actually what it's really saying is there's like this quirk where you say create a Great post for LinkedIn to the model and the model goes and says well this is what a great post looks like on LinkedIn. And. And LinkedIn for the most part sucks. Well, not sucks, but there's a lot of bad content on there. So you're going to get a ton of bad content from that. So you can see how good these are. I'm actually reading through some of them myself. I only read through the first five. The most underused AI technique in marketing. Every AI output you've ever seen was a first draft. The AI never reviewed its own work beforehand. And I mean I kind of feel like this is better than me. It's come up with so much good stuff. Before we go to market push. I fed the entire strategy into my AI model and asked you to find every way fail. That's very good. I found six problems we haven't seen here are the exact process and then it does like a nice little summary here. But you can see here gives me the title the key pattern. Right. I always like to do pattern match and I think content is kind of modular. It's patterns tutorial and then the trend and signal. It's pretty good. And so where's the one I really like? Pods replacing teams feature of teams Framework and HubSpot story. Yeah. POD defaults for high performance. Yeah. Wow. So much great content. Too much great content. But. But as we said, we are building an agentic team and the agentic team is going to do this autonomously. And because you're subscribed to the best YouTube channel on all this stuff, you will get that first when I built it. So let's go back to our graphic. I'm going to like show you the post enricher because it's dope. This works the way you think it would work. But I will do a separate video just on content creation because too many people will use these. Cut and paste. That's not how you do that. Right. So I think I will do a standalone video just on feedback loops because I think that's pretty important. But given I want to make sure that you can get through this and there's a lot to it. We're going to go add a sequence here in terms of how the system should be used. But again, I keep talking about this. This is not like using software. It's flexible. And so when you've extracted talking points, obviously the system would then say, here's your talking points. And you can basically just point at one and say, okay, like turn this into a draft LinkedIn post. Turn this into a draft YouTube transcript. Turn this into a draft substack. Turn this into a draft X article. What I want to do is because I want to show you the post enricher. I'm going to try to see if I can just give it a talking point and ask it to enrich that post. We have data enrichment. I have built content enrichment tools and I want to show you how they work. And I think I will do a standalone episode. I have just decided to do a standalone episode on content enrichment because it's super dope. But I'm going to show you this. Let's see which one of these we like. Educational workflow redesign is a real 80% of AI adoption domain expertise, speech prompt and skill. Your job is now AI agent and management. Spicy Take roi. Gap is a coordination problem, not a measurement problem. Agencies need to rebrand proactively. Reality gap standards data nugget 91 adoption vs 6% 0 employee AI marketing team in the room where nobody uses AI. Let's see what the story spark is. Okay, so let's do a first draft of a LinkedIn post for the Story Spark. Zero employees using the LinkedIn skill and then we'll use the post enricher because I'm kind of doing that sequence. So I want to show you the content enrichment tools need a first draft to enrich and so trying to enrich just the idea is kind of hard. All right, so it's done a post. Here's your LinkedIn post. So remember this is a story spark, so it should actually feel like a story. Also this is a draft, an idea and then you make much better. He didn't hire a marketing team, he onboarded one. So it's actually taken someone's real story. Documented this in February he built a full marketing function with 0 employees. 4 AI roles fully integrated on top of each other. Ads, analysts, content, user, blah blah. Each role had to find inputs, outputs and handoffs the whole stack run. So if I was doing this, I think the cool version of this is marketing teams of one and gets like multiple examples. So for example, there's one person in Claude running a lot of their marketing. So I'm going to get my transcript that I've done here and actually start to like format this into a kind of marketing team of one story enrichment. So it does have enrichment. But I'll show you how this works. The party gets buried in the excitement. He didn't just pick four AI tools, he structured each agent like an employee in board and document a defined scope yet so it tells you that's the gap between market and running. Blah blah. All right, so like it's a pretty good first draft. Again, first draft. When you look at this, I do not use this to post content. And so these are all ideas and now it's pulled in my enrichment here. So enrichment should actually get me modules, case studies, stories, examples, enrichments. Let's make sure we use the post enrichment skill. Here we go. All right, we're back. So this is the beginnings of an enrichment tool that I'm building. So it looks for ways to enrich that content. 2022, Jeff Bose sent an internal memo that changed how Amazon built software. Every team had to expose their data and capabilities through clean surface interfaces Divine and blah blah. 20 years later, the same principles are showing up in AI marketing stacks. The agent can that run reliably in production are the ones built with precise rules. Very cool connection. The failure mode isn't AI quality, it's the same failure Bezos was solved in the 2022 undefined roles that don't scale whether the work is very cool gives you a nice little case study here. But a platform running autonomously talks about the connection and then gives you a pretty good quote. Paul writes, sir, who runs the AI Marketing Institute Next gen marketers know that in order to deliver personalization experiences, modern consumers expect marked and must become smarter. Blah blah blah. Okay, so you can see the enrichment tool and I can easily just pick one of these and it will enrich that post. All right, it's not finished. It's saving that post but I can show you a different one. So remember I was really interested in that marketer role being split. I thought that was a pretty good post. I did do a first draft of that one. The marketer job split into this year. Most people haven't noticed. Very cool. It's actually done it as a LinkedIn post. It's so good. Spicy take again. Audience profile, hook pattern, contrarian punch enrichment type. Because all my stuff gets enriched enrichment source actually tells me where it was word count talking point and so it tells me what file I pulled from. It's on the other one now as well so you can see what it looks like. It's really good by the way. Right. The marketing jobs get into this year. Most people have noticed on one side go to market operators, they build systems inside cloud code, hello outbound engines running on 11 APIs, ad creative generators producing 100 various blah blah. On the other side, marketers waiting for the next platform to do it for them. And Chris Walker put the logic plainly in 2024, instead of having 100k SDRs doing it, what if we had 200 SDRs augment 8 people with AI blah blah blah. Very cool. And so it saves in there the other ones in here as well. He didn't hire a marketing team, he onboarded one. I have a hook skill and so I can improve the hook with that skill, much like I have a content enrichment skill. So obviously I would never ship this. I actually think the more interesting one is the rise of the one person marketing team. But there's some like really good stuff in here and here's the enrichment that we did. Now the last thing I want to close this out in the last minute is where people don't understand the importance of feedback loops because they're not systems builders, but systems builders do. And so what actually happens here is the system picks up all of the content in these apps. This one sucked as one of the worst performing posts. People did not like a product position, they're not into it. And so it picks up all the posts that I've created and then I can go here and I will be able to add the LinkedIn API at some point, but I don't have it added at the moment and so I have to manually add the data in here. But once I add the data, what actually happens is then I can just go and run a skill and the skill does review analysis of all of the performance so you can see what was created from the system, it can look at the performance and it actually updates all of my skills. So it's a skill that improves my skills. So everything I showed you will get updated and improved each month based upon what's doing well, what's not doing well. And so that is Claude code content system, your free skill that you get for free which is one of my favorite actually. It's pretty like cool. The lookalike content audience and if you don't have a lot of content then you can go collect other folks content that you like and give it that as a data file and it will go find those within patterns. You don't have to have your own substack, your own LinkedIn, your own X. You can go get that content from elsewhere. So that is the content system. There's a lot in this. I'm going to do some follow ups on the feedback loop, going to do a follow up on cloud code for content creation and how you could iterate really, really fast. All of that and more on a future episode of Marketing against the Green. So make sure you have subscribed and I will see you then. Foreign.

B (26:46)

You know, Kieran and I have been doing the podcast for a while now. We've been at this for a couple years. We love it. We could not be happier to be doing this, but we wanted to take things to the next level. We want to level up the impact we're having with marketing. It's the grain. So the next step of our journey is something we're really, really excited about. We're going to launch the Marketing against the Grain newsletter. And Marketing against the Grain newsletter is going to be amazing. If you are a marketing leader, practitioner, you're in the trenches doing marketing every day. This is for you. We're going to deliver right to your email inbox and you're going to get all the behind the scenes frameworks, practices, tutorials from us, from the guests we have on the show, and from people even beyond the podcast that we think are going to be helpful and and really have an impact on your day to day, week to week doing marketing. You're going to love it. It is something we've been talking about for a while. We're really excited to have it out in the world. We've already got a hundred thousand marketers who are on this newsletter. Please join. It's completely free. We'd love to have you as part of the Marketing against the Grain community. And it's easy. You can click the link in the description below, or you can head to marketingagainsthegrain.com subscribe.