Bonus: Scaling Content and Content Publishing in the AI Era by Ina Toncheva

Lecture Slides

About the Speaker

Lecture Transcript

[00:00:00] 

Over the last couple of years, I’ve been working very closely with marketing teams, figuring out how AI fits into their content systems. And the same question keeps coming up, how do we scale content without losing our brand voice and content quality? So today I want to walk you through how I think about scaling in the AI era.

Not from the perspective of hype, but from what actually works when you’re running real campaigns with constraints and KPIs. Right now marketing teams are under enormous pressure. Every AI tool out there promises complex, strategic and operational work reduced to simplicity and speed, and this creates unrealistic expectations to say the least.

Almost like there’s a conveyor belt somewhere that we just haven’t discovered yet. You press [00:01:00] a button and perfectly polished posts and videos rollout on the other side. However, speed and volume in scaling are only meaningful if there’s clarity to begin with. I’ve seen teams double their output and see no movement, and I’ve seen teams reduce their output and improve their results.

The difference isn’t the volume itself, it’s the system. Misconception number one is that content scaling means producing more post videos and landing pages faster, and that’s true, but only if you have an understanding of the different content types across different platforms and formats, and if you have some kind of system already.

Otherwise, what you produce simply doesn’t work. Another myth that I hear constantly is AI makes repurposing easy and fast. Well, technically it’s possible [00:02:00] you can paste a blog post into a model and ask it to turn it into three LinkedIn posts and email and a YouTube script. However, the problem with this easy and fast approach is that the final results look more like resizing than repurposing.

While repurposing is closer to translation than to copying and resizing. YouTube rewards strong titles and deep well structured content that keeps attention over time. While TikTok favors fast-paced hooks, emotional delivery, and quick payoffs, LinkedIn is the most effective when you clearly explain an idea or present a strong point of view.

On the other hand, Instagram is better suited for visual storytelling, quick emotional moments, and easy to swipe formats. To create winning content for all these different platforms takes judgment and understanding of each platform’s native language. [00:03:00] So what does true scaling means? Scaling means being able to create more of the content that works and bring meaningful results at a high level.

That comes from three things. Repeating what’s already proven, trying what you haven’t been able to do before, and making sure your best ideas actually reach people. That’s the foundation. Let’s take a look at the five layers of scalable content. The first layer is do more. If LinkedIn works. Lean harder into LinkedIn.

If your newsletter has a high open rate, invest more time in creating even stronger content. Scaling begins with doubling down on your proven strengths. The second layer is experimenting with new content formats and channels you haven’t used before. Short videos, interactive assets like custom gpt and so on.

This is where AI becomes [00:04:00] incredibly useful, and I’ll show you my favorite workflow in just a moment. Number three is with purpose. Something we touched on briefly, as I mentioned. Adapting content natively for each platform is essential if you wanna drive results. Next are AI tools. From SEO focused editors to multichannel scaling platforms, AI can amplify every layer as long as it’s used strategically.

And finally, distribution. It usually gets treated as the last step, but in my system it is actually the starting point. Because if content needs to be adapted or created specifically for each platform, then distribution isn’t an afterthought. It’s the foundation of the entire planning process. One of the simplest exercises teams can do is mapping their current content ecosystem using three columns, do more, improve, [00:05:00] and start testing.

You take all your channels or content formats, blog, email, social, video campaigns, everything, and place them in these categories. You can see where you are under investing, where you’re stretched too thin, and where the biggest opportunity lie. So where does AI fit in all this? Here’s my answer. AI is not the engine.

AI is the layer that sits on top of a working engine. If your strategy is clear, your formats work and your distribution is solid, AI will help you scale all of that much faster. But if those foundations are shaky, AI quickly becomes a distraction in it pulls you in the wrong direction at the exact moment when you should be laser focused on setting up your system.

Right. So when people ask me which AI tool should we use, the real answer [00:06:00] is it depends on what you’re trying to scale. Each tool category solves a different problem. If you’re managing multi-channel content that needs structure and consistencies platforms like Jasper are built for that they support full team workflow across blogs, ads, emails, landing pages, everything in one plug.

If search visibility is your priority, surfer AI is designed for SEO first writing. It scores your content in real time, aligns with Serbs and supports multilingual optimization. If you need flexibility, research depth, and full control over brand voice, large language models like Cha, GPT, and um, Claude, as well as custom GPTs offer the most adaptable workflows.

They’re ideal for small teams or marketers who want to design their own internal writing system. If you are looking for writing tools that connect directly to your publishing stack, [00:07:00] something like Write Sonic could work really well. It combines AI writing with features like AI visibility and WordPress, Zapier integrations.

And if budget is tight or you just need quick, simple drafts, writer is a lightweight option with multiple tones and languages. So instead of asking what’s the best tool, the more useful question is, which bottleneck in our process are we trying to remove? Remember how I mentioned several times that we need to create content that’s native to each platform?

It’s not easy to do it by by yourself, but AI is a great helper. No matter what you create, videos, posts, landing pages. I want to show you my universal approach that works for any content scenario. Okay? So start by giving your LLMA few great examples. Three to five pieces of strong [00:08:00] content. Sometimes even one is enough.

It could be a landing page, a video script, a social post, whatever matches the format you want to create. Then ask the model to analyze what makes these examples work. The tone, the flow, the structure, the emotional bits. This becomes your structural foundation. From there, you turn that inside into a lightweight blueprint, a pattern you can reuse in future content.

And finally, you combine that blueprint with your own core ideas. So the output still sounds like you and reflects your thinking. The AI gives you structure and speed. The essence and your core idea is always yours. To make things more concrete, let me walk you through a real example of how I built a short form editorial type of video using this exact process.

I started with a reference creator in this case. A video [00:09:00] from Eugene Healy. If you haven’t, uh, watched his videos, I highly recommend them. I transcribed one, one of his videos with the script and fed it into pic. I asked it to analyze the tone and structure so that I can understand the rhythm and the narrative techniques Eugene uses.

From there, I ask the model to write a new script following Eugene’s structure, but with my draft script. Once the script was in a good place, I moved on to the visuals. I took a few screenshots from the reference video and had the model describe the stylistic elements, lighting, framing, mood, and ev, et cetera.

Then scene by scene, I asked it to generate prompts for visuals that matched my script. I took these prompts into ideogram. And iterated until the images matched the tone I wanted. I then [00:10:00] edit titles in Canva and finally recorded the talking head portion and edited everything together. This is what I believe content creation looks like today.

A smooth blend of human taste, AI assistance, and structured iteration. Thanks for listening. My name is Inva and if you want to keep exploring these ideas, you’re more than welcome to follow me on LinkedIn or subscribe to my newsletter on my website, AI for content marketing.ai. Thank you for spending this time with me.