Almost Timely News: 🗞️ How to Update Old Content With AI (2025-12-07)

AI makes old crappy content into crappier new content

Christopher S. Penn

Dec 07, 2025

Almost Timely News: 🗞️ How to Update Old Content With AI (2025-12-07) :: View in Browser

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What’s On My Mind: How to Update Old Content With AI

This week, let’s talk about revising old content with generative AI so as to make the content more valuable. There are a lot of ways to do this; at recent marketing conferences, I saw no fewer than a dozen sessions all showing how people could tune up old content using ChatGPT and similar tools.

Now, without disparaging other people, I disagree with a lot of what was shown. Here’s why: almost all of the approaches rely on the latent knowledge of AI models. Most of the approaches rely on asking AI to improve old content natively, meaning not bringing in any outside information. For example, paraphrasing one speaker, their prompt went basically like this:

Here’s a blog post about account-based marketing. Make this blog post more appealing and more interesting to our audience, and make it longer. Include a stronger call to action in it to (website URL), and make it more likely to convince our audience to convert as a lead.

Yeah, that’s going to go well. What’s happening here is that they’ve oversimplified the process to the point where it’s going to generate bad results. If you’re familiar with the term AI slop, this is going to generate AI slop.

So let’s try to fix this and do better, both for our businesses and our audiences.

Part 0: Fundamentals

Before we start, some fundamentals. All AI models today are trained on massive amounts of public (and not public) data. The amount of information in today’s models equates to a bookshelf of books that goes around the equator of the planet 8-12 times. It’s massive.

It’s also not necessarily current or correct. For every peer-reviewed paper with randomized controlled trials and bespoke research in AI’s knowledge, there’s equally complete garbage from Aunt Esther’s Healing Crystal and Flat Earth Blogspot blog. In fact, there’s significantly more garbage than high quality content because garbage is easy to make and doesn’t rely on inconveniences like facts, as capably demonstrated by many politicians.

That means that we cannot and should not rely on AI to be an arbiter of truth or facts. If we’re going to upgrade our older content, we want it to be better, not worse.

So the first principle of revising older content: make sure it’s genuinely an upgrade. And we make sure it’s an upgrade by using the highest quality data, the highest quality ingredients.

Next, we cannot lose sight of the basics of content marketing, namely that our content has to meet basics like the 3E rule: your content should entertain, educate, or engage (ideally all three). The corollary to that is the 3L rule - if, while you are creating content, you did not laugh, love it so much that you told a close friend about it unsolicited, or learn something in the process, the content is probably no good.

Why? Because we are ostensibly the subject matter experts in the content we’re making. If we, as leaders in our spaces, aren’t getting anything out of our content, then our audience isn’t either.

Here’s the bench test, the acid test of great content, borrowed from my friend Jay Baer. Would anyone - including you, if it wasn’t your content - pay you even a Euro/dollar/peso/pound/kroner for your content? I said in a recent YouTube video to try putting a tip jar on your content. If you don’t collect even the smallest unit of money in your local currency once during the year, if no one sees enough value in your content to tip you at least a pittance, then your content isn’t any good.

AI won’t fix that - and that’s a significant risk of updating content using AI. If the starting content isn’t any good, AI isn’t likely to make it any better.

As AI strategy expert Katie Robbert often says, “new technology doesn’t solve old problems.” Content that sucks, when processed by AI, will suck faster, at greater length.

With those warnings in place, let’s get our recipe together.

Part 1: Mise En Place

To do great content upgrades, you’ll need a variety of tools:

Web analytics: Assuming we’re working on public content, you’ll want some way of figuring out which content to work on. Web analytics tools of any stripe, be they tools like Adobe Analytics or Google Analytics or native measurement systems like the stats provided by Substack or Wix are where you want to start.
Large language model: ChatGPT, Google Gemini, Anthropic Claude, DeepSeek, Alibaba Qwen - pick your poison. All of today’s large models and platforms are smarter than a PhD in their field, so pick the best one you have access to. Because we’re working on public content, privacy risks are low.
NotebookLM: An AI-powered research tool like NotebookLM is essential for today’s content upgrades because we’re going to be gathering and aggregating a lot of information together, and NotebookLM does this better than most. It’s also very capable even in its free version.

In addition to the tools, you also need great ingredients. I coined the term knowledge blocks, like digital building blocks, for this process. Some of the things you’ll want to have on hand:

Ideal Customer Profile: Who is the audience you want? Who is the content for? We’re not making content for everyone. Presumably, if we’re doing this for any kind of business reason, we’re making content for a very specific kind of person.
Who you are: Who are you? What should AI know about you? For content creation, at a minimum you should have things like a detailed writing/speaking style, what you’re expert in, what jargon you know, etc. I’d recommend having both - a style guide plus a knowledge block about who you are.
What constitutes great content: What is great content, and specifically what does great content mean to you and your audience? I’ve given you two of my frameworks, but you should probably have your own, tailored to your business and your needs. Critically important, your stated goals for what your content is supposed to do for you must be in here! If your content is to generate leads, make sure that is stated explicitly. If your content is to generate newsletter subscribers, make sure that is stated explicitly. Put your goals in the great content document.

Part 2: What to Upgrade

The decision about what to upgrade hinges on what you’re trying to accomplish. If you’re trying to make your best content even better, then pick the content that represents whatever best means in your world.

That might be content that gets the most users, sessions, or page views (which is easy to measure).

It might be content that shows up the most in conversion paths (somewhat harder to measure).

It might be content in specific parts of the operational funnel, because while customer journeys aren’t linear, there’s only so many ways people can rationally and logically buy from us.

You decide what makes the most sense to upgrade based on your business needs. For the purposes of this issue of the newsletter, I’m going to examine some content that’s still doing well but is badly out of date.

I went to the Explore hub in my Google Analytics and found a post from 2017 called “The Power of Predictive Analytics and Social Media Data”. This post did great earlier this year, earning 480 sessions. But it’s so badly out of date. 2017 feels like it wasn’t that long ago, but it’s been 8 years since I looked at this post. That’ll be our candidate for today.

Part 3: Quality Assurance

Our first step is to do some QA. I have a 4 part QA framework that I use for nearly everything, derived from coding. This forms the basis of many of my prompts, and is a great way to kick off assessing nearly anything. It’s based on four questions:

What’s good, if anything?
What’s bad, if anything?
What’s missing, if anything?
What’s unnecessary, if anything?

When you work with anything or anyone, but especially AI, you want to cover all four questions. Asking AI what’s good about something will get you an answer about what’s good. It will not get you an answer about anything else. By asking all four questions (and adding in the vocabulary phrase ‘if anything’ from last week), we cover our bases.

So our first step is to take the existing post, our ideal customer profile, our about us, our writing style, and the post itself, and ask the machine exactly that, with the Trust Insights RACE prompting framework. Use any AI tool of your choice to perform this assessment.

You’re a CMI award-winning content marketing expert skilled at content audits, content analysis, content creation, content editing. You’ll perform a content audit today. Using the included Ideal Customer Profile as the audience, the background information about our company, our writing style guide, our content quality guide, and the content, audit the content on these four areas: 1. What is good about the content, if anything? 2. What is bad about the content, if anything? 3. What is missing from the content, if anything? 4. What is unnecessary in the content, if anything? You’ll audit for style alignment, content quality alignment, audience alignment, and strategic alignment.

Let the model produce its audit. Once the audit is done, we’ll have the necessary roadmap for upgrading our content. Here’s what Google Gemini spit back at me:

Yeah, that stings a little, but it’s also completely correct. That’s why this piece of content needs an upgrade. It’s so badly out of date, it’s more harmful than helpful.

Part 4: Deep Research and Synthesis

From the content audit, we want to understand especially what’s missing that we should have had in the original. Gemini gave me a laundry list of everything wrong in this post. While it’s identified those wrong things, the challenge is that I don’t trust the tool itself to write a new version properly. A lot has changed in 8 years, and I want AI focused specifically on rebuilding this from my expertise, but informed by real data.

What we do is straightforward. Using the Trust Insights CASINO Deep Research prompt framework, I’ll draft a deep research query that will identify new research, new methods, new tools, and new strategies that we can update the post with. For example, Crowdtangle was bought by Meta and shuttered in 2024. What, if anything, can stand in for it?

The original post also referenced the R programming language and predictive analytics. Today, the preferred language of both AI and data science, for good or ill, is Python. We’d want to know what we should replace in the original post - what’s out there?

From that Deep Research, you may or may not have enough information to proceed with updating the post. In this particular example, there was enough information in Deep Research to not need additional synthesis, but other use cases might be different.

For example, if this were a piece on attribution modeling, there might be a series of academic papers as part of the output. I’d put those into NotebookLM and run some synthesis queries on the data to better understand where the field is.

Part 5: Interactivity and Transmedia

Now that we know what our content is missing and we know what should be in it, it’s time to update. Here’s a critical oversight so many people in the AI expert space are missing: they’re advising upgrades that don’t match the world we live in.

Having ChatGPT rewrite your blog post to be a better blog post ignores the fact that things like AI Overviews reduce or eliminate the need for a blog post at all, on the part of our audience. There are very few authors that I ever want blog content from any more; I can count them on one hand. That world of static content is vanishing before our eyes.

The thing to think about is what our audience would actually find useful, especially in something more interactive than a static page. What could we create that would be of value to our audience? What could be interactive in some way that would elevate the content from being a static wall of text to something that an AI couldn’t easily summarize or substitute?

The good news is we don’t have to come up with that on our own. We go back to our source data and we ask AI exactly for that.

Here’s a research report that summarizes the current best practices which update the field and our original content from 2018. Based on our ICPs, who we are, content guidelines, and this research, consider and create 3-5 different interactive idea concepts for turning this static article into something more interactive and interesting. Available technologies include things like CDNJS, Tailwind, JS, etc. - how could we make this content more interactive, interesting, informative, and satisfying to our audience?

The language model will present you with different options. Read through them and use your subject matter expertise to proceed with one of the choices or give feedback (including saying nope, you missed the mark). Take the time to iterate through the choices as well as explain in detail, correcting the AI at every turn.

Do we update the original post? Sure. But in addition to updating the original post, we add interactivity and an experience for the user to have that satisfies their needs and is more resistant to AI simply summarizing our audience away from us.

In the video edition, you’ll see me walk through this process in detail with Gemini, constructing the concept of the interactive tool, then creating a Mermaid flowchart of how the tool will work, and then passing that information to Antigravity (Google’s coding tool) to build the interactive for the content.

Part 6: Wrapping Up

This process is obviously not something you do for every single blog post on your blog. It’s for the content that matters the most, the greatest hits of yesteryear that you want to remain relevant as time goes by. This week, every company in the world sent out their version of Spotify Wrapped, looking at your greatest hits from 2025.

While looking back is fine and fun, taking what worked and making it even better is the way to go.

What’s different about this approach, when we do it well, is that we’re not just recycling greatest hits. We’re not slapping a fresh coat of paint on them - we’re fundamentally changing their nature and making them better experiences.

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