If you’re a food blogger working with Raptive, you’ve probably heard something about Raptive Intelligence by now. Or maybe you haven’t.

I’ve been following the announcements and having conversations with people in food tech about what this could mean for recipe creators. It was news to me; maybe it’s news to you, too. I hear there’s interest in what’s being built, but also some uncertainty about how all the pieces fit together. And I can understand why.

We’re talking about AI assistants, recipe data, grocery shopping, content licensing, and new ways to monetize creator expertise. That’s a lot to unpack, especially when the technology is still emerging. So I wanted to take a closer look at what Raptive has actually announced, why it matters, and what questions I think creators should be asking. I’m writing this now, on Wednesday night, to go live tomorrow… outside of my usual schedule. I couldn’t help myself. So here’s a BONUS issue of Blueberri Pi.

I’m not giving an endorsement or a warning. Just a heads up on where the technology is heading and what that could mean for the people whose content makes it possible.

First, what exactly is Raptive Intelligence?

On June 9, 2026, Raptive announced a new business unit called Raptive Intelligence, alongside its acquisition of AlchemyAI, a food-intelligence technology company founded by John Roa, who now leads Raptive’s AI strategy.

If you know Raptive primarily as an advertising partner for publishers, this represents an interesting expansion. The company wants to make creator expertise and consumer intent useful across AI platforms, grocery retailers, consumer packaged goods companies, and other commerce experiences.

In other words, Raptive is looking at the value of food content beyond the advertisements displayed alongside it.

Think about a recipe. To a reader, it’s a set of ingredients and instructions for making dinner. To a technology platform, that same recipe can contain information about ingredients, dietary preferences, cooking techniques, substitutions, nutrition, and even potential shopping decisions.

Raptive says the technology it acquired from AlchemyAI includes a food knowledge graph that connects these different types of information. That’s interesting because it could allow recipe information to support experiences beyond the original blog post.

There are a few different products to keep straight

This is where things can get confusing. Raptive Intelligence is the broader business initiative announced in June. Its stated ambitions include licensed data access, real-time intelligence products, and commerce infrastructure.

There’s also a Raptive Intelligence WordPress plugin. Its public listing, updated October 21, 2026 at the writing of this article, describes a Raptive Assistant that can appear on eligible pages of approved publisher websites. According to the listing, the assistant is enabled by default when the plugin is activated, although site administrators can turn it off under Settings > Raptive Intelligence. When enabled, the service sends the page URL and uses page context and visitor questions to generate responses.

Then there’s Raptive Compass, a separate publisher dashboard product that uses AI to help publishers interpret their performance data and identify next steps.

All three involve AI, but they don’t necessarily serve the same purpose. An assistant helping a reader understand a recipe is different from a tool analyzing publisher revenue. Both are different from infrastructure that could make food information available to outside commercial partners.

We have to pay attention to all three when we’re discussing what information is being used and who benefits from it.

Why food creators should care

Let’s say you’ve spent ten years building a recipe website. You’ve tested hundreds of dishes, documented techniques, answered reader questions, photographed ingredients, and developed an understanding of what your audience wants to cook.

Traditionally, much of the economic value came from bringing someone to your website. A person searches for a recipe, visits your page, sees advertising, and perhaps clicks an affiliate link or purchases something you recommend.

But what happens when the recipe can also help an AI assistant suggest a substitution? Or help a grocery platform build a shopping list? Or help a food brand understand what consumers are interested in making?

Suddenly, the potential uses of your content extend beyond your website. That isn’t automatically a bad thing.

In fact, it’s something I’ve been talking about for years: content can become more valuable when it’s structured well enough to work across different platforms and experiences.

The webpage doesn’t have to be the boundary of your content’s value.

The opportunity is that creators might be able to earn from uses of their expertise that traditional advertising never captured. The challenge is figuring out how those uses are authorized, measured, attributed, and compensated.

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The opportunity is real, but the details matter too

Raptive has publicly stated that it wants creators to share in the value their work generates. It has also advocated for attribution, transparency, and creator rights as AI changes digital publishing.

Just typing out loud here, but there’s a difference between describing a business vision and explaining the terms under which an individual creator participates. For example, if a recipe helps power a shopping recommendation on another platform, what does participation look like? Does the creator receive attribution? Is the content licensed? Is compensation tied to usage, transactions, or some other arrangement?

And what happens when the information being used isn’t just the recipe itself, but also insights derived from how audiences interact with recipes? These are different categories of value, and they deserve different conversations.

I haven’t found enough publicly available detail to answer those questions for the new Raptive Intelligence business as a whole. That doesn’t mean the answers don’t exist or that anything improper is happening. It means creators should understand the applicable agreements and product terms before drawing conclusions about what they’re joining.

What about the data?

This is the part I’m really interested in as a content systems strategist. Recipe content, audience behavior, and commercial intelligence aren’t interchangeable. A recipe might contain ingredients, instructions, cooking times, and nutritional information. Audience interaction data might reveal which recipes readers view, what questions they ask, or which substitutions interest them. Commercial intelligence might involve analyzing patterns across many interactions to understand broader consumer preferences. Each can be useful, but also raises different questions about access, permissions, and ownership.

The public WordPress plugin description, for instance, explains that the assistant sends the page URL and uses page context and visitor questions to provide responses. A useful starting point for understanding the assistant, but it doesn’t explain every data practice associated with the broader Raptive Intelligence initiative. And I wouldn’t assume the same permissions or commercial arrangements apply to every Raptive product simply because they share a company name.

For creators, here are some questions to think about and maybe jot down for later!

• What information does this particular product collect and use?

• Can that information be shared with outside partners, and for what purposes?

• How are creators credited and compensated when their content creates value elsewhere?

• Is participation optional, and what happens to the information if a creator stops participating?

• What rights and controls are established in the applicable agreements?

These aren’t questions unique to Raptive. I’d ask them of any company developing AI-powered services around creator content.

There’s a bigger change happening

Food content has always been valuable to more than the person reading a recipe. It influences what people cook, what they purchase, which products they trust, and which brands become part of their routines. What’s changing is the technology available to identify, connect, and act on that information.

A well-structured recipe can become part of a larger system connecting food discovery, meal planning, shopping, and commerce. That’s why metadata, taxonomy, content relationships, and rights management matter. It’s why I’ve been paying attention to companies working on recipe intelligence, whether they’re building tools for individual creators, consumer cooking experiences, or infrastructure for larger platforms.

The technology is becoming capable of doing more with content that already exists, but the ability to use content isn’t the same thing as having the right to use it, and creating value isn’t the same thing as distributing that value fairly. Those are business and relationship decisions, not just technical ones.

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So what should creators do now?

I wouldn’t rush to adopt something simply because it uses AI. I also wouldn’t dismiss an emerging product before understanding what it actually offers, and just becuase it does use AI. If you’re a Raptive publisher, start by asking which services are available to you today, which are still being developed, and what participation requires.

Read the relevant terms. Ask how your content and audience information will be used. Understand whether there are new revenue opportunities and what would qualify you to participate. If you’re building a recipe platform or another food-tech product, pay attention to the underlying shift.

The value isn’t necessarily in generating another recipe or adding a chatbot to a webpage. It may be in helping trusted, existing content work across more useful experiences while preserving the relationships and rights that made that content valuable in the first place. A much more interesting challenge, if you ask me.

My initial thoughts are…

I see potential in what Raptive Intelligence is describing, especially if it creates meaningful new opportunities for food creators to benefit from the expertise they’ve already built. I also think it’s too early to evaluate the broader initiative solely on its ambitions. The details of implementation, permissions, attribution, and compensation will matter. I also don’t think Raptive will be the only company showing up to this party. More creator-focused AI tools are likely coming, and that’s why it’s worth shopping around. It’s a little like choosing a phone plan. Unlimited data sounds great, but I still want to read the fine print before signing up.

Structure is only part of the equation. When that content begins moving between systems, the relationships and agreements around it have to be just as intentional. The next question for food creators isn’t just where their recipes can go, it’s what happens to their value when they get there.

Are you a food creator following Raptive Intelligence? I’d love to know what you’ve heard, what you’re excited about, and what questions you still have.

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JUST SO WE’RE SUPER CLEAR: Blueberri Pi is independently published by Sandie Markle, founder of Blueberri. This article is an independent analysis of publicly available information, not a sponsored post or endorsement of any company.

In the last issue, I laid out five things I keep seeing content-first tech companies get wrong when they try to build a creator economy. Understanding the community. Messaging. Who’s delivering it. Visibility. Whether creators are treated as partners at all.

I told you I’d come back with what I’d actually do differently if I were building a creator program from scratch. I’ve seen it done wrong for years and I haven’t been keeping this to myself, either. But there’s nothing like sharing it on blast on Substack to spread the message a lot faster.

This is the Expand for Reach and Revenue stage of COSE™. Structure doesn’t create possibility by sitting there. It creates possibility when someone actually builds the systems and relationships that let it reach further.

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Tech companies that have content-first platforms need creators. You know it, I know it, they know it. The part that I want to talk about is what happens after everyone agrees on that sentence.

I spent five years growing a list of food bloggers purely off the cold email. I didn’t know how to create a funnel, I had no outreach tool, just me, refining the approach over time until I got pretty good at it. Relationships built one email at a time, one blogger at a time, one “let me tell you what we’re building and why it might be worth your time” at a time.

Then things changed with syndication.

I remember the first time I heard the word cannibalize. A blogger said it to me directly. “Why would I put myself on this platform? It will cannibalize my content.” I didn’t have a salesy-biz-dev answer for her in that moment, and, I’m not sure it’s what the moment needed. What it needed was for someone at the company to have already thought that question through before it landed in my inbox. To be on top of the changes that were happening with content and how it affected the people were were trying to reach.

I’ve spent time on both sides of this. I’ve worked with and grown a creator list from nothing. I also launched a full content partnerships program from the ground up. It didn’t take off because it stopped being a priority for the company at a moment when priorities shifted elsewhere. One of many things that I’m legit sad about. It happens. But I’ve kept the notes from that experience, and if I were building my own creator program tomorrow, I’d start with what I watched go wrong, over and over, at company after company.

These are my observations for tech companies and creators to learn from, so take from it what’s useful to you. I’ve built my framework, COSE™ around this. In COSE terms, this lives in the Expand for Reach and Revenue stage, the part of the framework about reach, revenue, and partnerships. You can have the best structured content system and still fumble the human relationships that are supposed to expand its reach. Here’s where I keep seeing that happen.

1. They don’t understand the community

Most of the time, this isn’t malicious. It’s just distance. Companies learn about their creator community through an aerial view that’s an industry report, a few conversations, the experiences of one or two people on the team who used to be “close to creators” at some point in their career. Then everyone drinks their own Kool-Aid in the form of group-think accolades, cognitive bias, and resources and tools get built based on assumptions and generalizations instead of what creators are actually doing day to day.

Here’s why this backfires. Creators can tell, almost instantly, when a tool or resource was built for a creator who doesn’t exist. The workflow doesn’t match how they actually work. The messaging answers a question nobody asked. And once a creator clocks that gap once, they start reading everything else from that company through a more skeptical lens, which makes every future attempt at outreach harder than the last.

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2. Really, really bad messaging and benefit package for joining

My biggest cringe moments come when messaging doesn’t just fall flat, it burns to the ground. Words matter.

Sometimes tech founders and execs think they are the voice of the brand. I’ve watched a founder who is great at building the product get handed the mic for creator outreach, because it’s their company, and surely nobody understands it better than they do. Except understanding the product and understanding the room are two different skills, and I’ve read outreach emails that sound like they were lifted straight out of a board deck. The language is inward-facing. It’s built around what the company needs the creator to believe, not around what the creator is actually trying to figure out, which is usually some version of “is this worth thirty minutes of my time.”

Companies sometimes expect creators to come flocking to promote a product or service that hasn’t even entered the five stages of adoption yet. It’s still hovering at the very top of the awareness marketing funnel. Nobody knows about it, so nobody cares. And because of problem #1, the messaging is blatantly obvious about who it’s really for. The selling proposition helps the company. It doesn’t help the creator. Creators notice the difference between “here’s what this does for you” and “here’s what we need from you,” even when the words are dressed up nicely.

3. The wrong person is talking to creators

I’ve worked with and met some of the most intelligent product managers and engineers you’ll ever come across. Genuinely brilliant at what they do. But sometimes the tech speak is a bit much for the room they’re standing in.

A few years ago, I went to a creator workshop led by a tech guy. He was talking about the benefits of a product I thought was fascinating. I was locked in, picking up everything he was putting down, because I spoke his language. I’d learned it over time. But as I looked around the room, I could see he’d lost his audience. By the end of the session, about 75% of the room had quietly left.

He tried. He really did. I thanked him afterward and told him what I appreciated about the session, then told him the part he probably was supprised to hear. I gave him it in a commendation sandwich, my signature dish. It was filled with “I’m not his audience…creators are” and he lost them. He was gracious about the feedback. I want him to succeed. I want creators to succeed too. Those were the slices of bread that made up the sandwich. I still think about that room, half empty by the end, and what it means that the smartest person in the building wasn’t the right person to be standing at the front of it.

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4. Wrong use of visibility

There's a version of this problem that shows up as a line item in a budget. Spending money on a booth, on ads, on sponsorships, isn’t the only way for people to know who you are.

Before I started Blueberri, my name was already synonymous with the company I worked with, even when that didn't always translate directly into business for them. That's usually how it works in the early stage of a company, especially in tech. It's rare for a creator to turn to another creator and say, "Have you heard of this business, they're great." What actually happens is closer to, "I'm currently working with this person. They're amazing. I like them because..." The visibility that actually moves creators rarely comes from the places companies spend the most money trying to buy it.

5. Not thinking of creators as strategic partners

This one is closely related to numbers one and two, and it affects both of them. If you don’t see creators as potential strategic partners in what you’re building, that shows up in how you speak to them and what you offer them.

I get it, it’s a business. Creators are your target customer. But it’s worth sitting with the fact that this isn’t just a B2B model. It’s B2B2C, and especially in the early years, companies could use some of the feedback and guidance that doesn’t happen during sprint planning or a board meeting. Creators can be customers and advisors and early adopters and brand ambassadors, sometimes all at once, and most companies I’ve watched only ever engage them as the first one.

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Where this leaves us

Expand for Reach and Revenue, in COSE, is the stage where structure is supposed to turn into reach, revenue, and new experiences. Partnerships live right in the middle of that. But partnership only works when both sides are actually building something together, not when one side is hoping the other shows up to promote a product that hasn’t earned its awareness yet.

Next up, I want to share what I'd actually do differently if I were building a creator program from scratch, using everything I've learned from the list I built, the program that didn't get the runway it deserved, and the years since spent watching other companies make the same five mistakes in slightly different outfits.

There’s even a freebie in it for ya.

Help me get my book into your hands

Create Once, Share Everywhere™ has been taking shape for a long time. On July 20, 2027, it becomes a real book.

I've chosen to independently publish it because I want to build something that reflects the ideas I'm asking creators to believe in → ownership, longevity, and creating work that can keep growing beyond the place it started.

And I'd love for Blueberri Pi readers to be part of bringing it into the world.

Through December 31, annual Blueberri Pi subscriptions will help fund the professional production of Create Once, Share Everywhere™.

Upgrade to an annual subscription for $80 and you'll get a full year of paid Blueberri Pi. And when the book publishes next July, I'll send you a complimentary copy.

So you're not just supporting a book. You're supporting the independent thinking I publish here, the work I'm building around COSE™, and a bigger idea I've come to believe deeply that good work deserves the structure to last.

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Until next time,

I found a copy of Intelligent Content: A Primer at a thrift store this summer for $6.95. Water-stained cover, somebody’s old highlighter marks still in the margins, the kind of nerdy find that makes you stand in the aisle a little longer than you meant to.

I’ve had some time on my hands this summer, and instead of binging another cooking show, I decided to go time-traveling.

The Q4 Power-Up

Before we get into it, I’m running a limited-time Blueberri Pi Q4 Power-Up promotion through September 30.

Upgrade to an annual paid subscription, and you’ll lock in 20% off for as long as you stay subscribed, plus get a complimentary 1:1 strategy call with me, usually $150. Ask me anything about making your content work harder, monetizing what you’ve already created through partnerships and licensing, navigating AI and changing discovery, building better systems, growing beyond platform algorithms, proving your content's value, or figuring out what to prioritize next.

And there’s another reason to upgrade now. I have one of my favorite Blueberri Pi topics so far coming on October 16, exclusively for paid subscribers.

I’m not giving it away yet, but if you’ve been following my thinking on content, creators, and partnerships, you’ll want to have access to this one.

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I’ve been deep in interviews as I’m writing my book this year, working title Create Once Share Everywhere, and one name keeps coming up whenever someone asks how the writing is going. Ann Rockley.

So I did what any reasonable person would do. I went back to the original source, starting with Intelligent Content: A Primer, which Rockley co-authored with Charles Cooper and Scott Abel.

The woman who saw it coming

The story, as it’s usually told, goes something like this. Long before “omnichannel” was a slide in every marketing deck, Ann Rockley was already looking at content and seeing something most people in the room weren’t seeing yet. It was the same piece of content, structured correctly once, could show up correctly everywhere it needed to. Web, print, mobile…whatever came next. That thinking eventually became part of what Rockley called intelligent content.

Rockley actually adopted the title "content strategist" back in 1989, and was working on content strategy, reuse, and structured content long before most organizations were talking about omnichannel delivery. Kristina Halvorson, author of Content Strategy for the Web, has called her “the mother of content strategy,” and in 2023 Rockley was inducted into the Content Strategy Hall of Fame for her foundational work in the field. By the time she was defining intelligent content for the tech comm world, she'd already spent years thinking about content as something designed to move, adapt, and be reused.

She describes intelligent content as “designed to be modular, structured, reusable, format-free, and semantically rich,” and the book adds that those qualities are what make content discoverable, reconfigurable, and adaptable in the first place.

But she was never on the marketing team. This was an engineering idea wearing a content strategist’s clothes, which is probably why it held up so well for so long.

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What I actually learned building with this stuff

I worked deep inside a recipe platform’s content operations, watching a database grow well past 20,000 recipes while it fed a web app, an iOS app, an Android app, and eventually voice assistants and grocery retailer integrations with partners like Kroger and Target. Every one of those surfaces needed the same recipe to behave correctly, with the right ingredients mapped to the right products, the right substitutions, the right nutrition data, the right everything. And every surface had its own expectations for how that content needed to be shaped to work at all.

The mess was a modeling problem needing to be fixed. We’d been treating “ingredient” as a single field for years, when it was actually a small universe of relationships: name, quantity, unit, brand, substitution logic, allergen flags, retailer SKU. Once we modeled it properly, taxonomy did exactly what taxonomy is supposed to do. It let content move. Recipes that used to live and die on a single webpage started showing up in shopping lists, voice responses, and partner apps that didn’t even exist yet when the recipes were first written.

It felt novel then. Today, those kinds of connections are part of the grocery experiences people use every day. Turns out Ann Rockley already knew we’d be here. Years earlier, from a very different corner of the industry.

The building changed

The omnichannel era asked one question: can this content show up correctly on a new screen?

The current era is asking something harder. Can this content be understood, trusted, and used by a system that’s going to synthesize it into something else entirely, without a human ever clicking through to see it in its original form?

That’s a different bar. A recipe that displays beautifully on a phone can still be functionally illegible to an AI system trying to work out which step comes first, which ingredient is optional, and which line in your FAQ section is actually load-bearing versus which one is filler. Structured content got us onto more screens. It didn’t automatically get us ready to be reasoned about.

That’s the layer I keep coming back to with the food-tech platforms and content teams I talk to. The gap usually isn’t a lack of content, and it’s rarely a lack of effort either. It’s that the systems holding the content, the CMS, the taxonomy, the workflows connecting content to product, were built for a version of distribution that’s already one step behind where the traffic and the value are actually moving now. Producing more content on top of that gap doesn’t close it. It just adds more content that inherits the same structural problem.

Eventually, that stops being a content problem and becomes a business constraint. It’s the partnership your team can’t support without weeks of manual work, the product feature that takes months because the information it needs can’t be reliably retrieved, or the AI experience that misunderstands content your audience has trusted for years.

The risk isn’t that your content disappears. It’s that the opportunity moves somewhere your content can’t follow.

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Structure is also a monetization strategy

Companies tend to separate content infrastructure from monetization. One lives in conversations about CMS migrations, metadata, taxonomy, APIs, governance, and content operations. The other lives in conversations about revenue. But they are much more connected than that.

Think about that recipe again. As a webpage, its most obvious economic job might be attracting a visitor and generating advertising or affiliate revenue. Structure the underlying content, though, and suddenly the possibilities multiply. The ingredient can connect to commerce. The recipe can power a retailer integration. A collection of recipes can become a personalized meal-planning product. Nutrition and dietary attributes can support filtering and recommendations. A trusted archive can be licensed or distributed through partners. Structured expertise can support subscriptions, apps, APIs, AI experiences, or products that nobody had imagined when the original article was published.

Not every piece of content needs to do all of those things. That’s not the point. The point is that structure creates possibility, and that matters when nobody can confidently predict what the next important content surface will be.

A business sitting on 20,000 poorly structured recipes might technically own 20,000 pieces of content. A business that can reliably understand, retrieve, combine, govern, and distribute the information inside those recipes has something much more interesting: an adaptable content asset.

Content infrastructure has the potential to become revenue infrastructure. Metadata doesn’t magically make money, but structure lowers the cost of putting content to work somewhere new.

Still learning

I’m not here to tell you structured content is dead and something shinier replaced it. I’m here to tell you the opposite. The discipline Rockley helped build made content smart decades before anyone was asking AI systems to read it, and most organizations still haven’t fully finished the version they needed for the omnichannel era, let alone the one they need now.

Rockley's since stepped away from active content strategy work herself. These days she's doing health and career coaching instead. But the idea doesn't need her still in the room to hold up. The discipline she built is still running under everything I just described, whether or not she's the one consulting on it anymore.

The work in front of food-tech companies, recipe platforms, and content-rich teams can’t be a rebrand of content strategy. It’s the next chapter of it, one where your content has to work for readers, for product teams, for retail integrations, and for AI systems that are going to use your content whether or not you’ve prepared it to be used well.

That’s the throughline underneath everything I write here, and it’s a big part of what Create Once Share Everywhere is actually about. Content isn’t an asset until it’s structured, and structure is what decides whether your content can go where the opportunity actually is.

If your team is sitting on real content and real traction, but the systems underneath it are starting to strain, that’s a “structure what you have” problem, and it’s a lot more solvable than it feels like from the inside.

Rockley helped us figure out what smart content meant for the omnichannel world. Now we have to figure out what smart content means when the systems consuming it aren’t just displaying it, but interpreting it.

So am I. That’s most of why I bought the book.

Until next time,

P.S. The Q4 Power-Up ends September 30 — lock in 20% off your annual subscription + your complimentary 1:1 strategy call with me.

It’s been a while since you’ve seen an issue of Blueberri Pi land in your inbox, and I want to own that instead of pretending it didn’t happen. I gave myself a summer reset. Actual rest, actual recovery, the kind where I stayed off my laptop more than I stayed on it. What I didn’t do was stop paying attention. I was still reading, still watching what was shifting under the surface of search and content and AI, just not writing about it in real time.

If you’re new here, welcome. Blueberri Pi is where I write about the systems, people, and platforms shaping how content actually works, not just this week’s algorithm update. If you want the fuller picture of what this newsletter is trying to do, I put together a Start Here post that gives you an overview of what

I’m back with a story that landed right in the middle of my break, one that felt too relevant to Blueberri Pi to let pass quietly. It involves Google, recipes, and an experiment that says more about where this is all headed than most of the AI headlines I’ve read this year.

Meet Riley

Riley bought the peaches twice.

The first batch looked perfect at the farmers market, and then they weren’t. Too soft, and by the time she’d tested the filling, photographed the finished cobbler, cleaned the kitchen, and pulled the images up on her laptop, she already knew she’d be doing it all again. So she bought more peaches, adjusted the cornstarch, changed the baking time, and shot it a second time. Then came the actual writing. She wrrote the ingredients, instructions, timing, substitutions, storage tips, the FAQ section nobody reads until they need it, alt text, metadata, and schema. She edited the photos, uploaded everything, formatted the post, and hit publish.

That was four years ago.

Last week, I was surprised to see that Google tested AI-generated images inside AI Overviews for recipe searches. There were no links to a creator’s step-by-step photography. AI-generated images showing the cooking process, built without a kitchen, a camera, or a Riley anywhere in sight. I didn’t even know an experiment had begun, to be honest.

And in the same stealth fashion, Google ended the experiment, calling it a small test. Right. Technically, that means the feature is gone. For now. I don’t think the interesting part of this story is that it ended. I think it’s what Google thought was possible in the first place, especially the same week Google kept expanding AI Overviews more aggressively, pushing traditional links even farther down the page.

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The internet used to need the page

The process used to be so simple. A blogger created a recipe and Google helped someone find it. That person clicked, maybe saw an ad, maybe joined an email list, maybe came back the following week. The system was never perfect, but there was a recognizable path between creating value and receiving some of it back. That path is changing. AI systems can pull information from across the web to build an answer before anyone reaches the original source. And now we’re starting to see what that looks like beyond text.

If we’re really gonna get technical (which I love to do) a recipe was never just a title and a list of ingredients. It’s a dense package of structured knowledge: ingredient relationships, quantities, sequence, timing, temperature, technique, substitutions, dietary information, images, video, and years of small decisions that add up to expertise. Most of that sits invisibly inside what looks, from the outside, like one ordinary webpage. Your content isn’t just something people read. It’s something machines can now interpret and act on.

This is bigger than traffic

We all know where this conversation usually goes next. Traffic. Will AI Overviews decrease clicks even more, and by how much? Will Google send fewer people to recipe sites? A creator’s business runs on ad revenue. It’s your bread and butter, but focusing only on traffic makes it easy to miss the bigger shift, which is that the unit of value itself is changing.

Owned platforms are extremely valuable but creators treat the webpage as the only asset. You create the post, rank the post, drive traffic to the post, monetize the traffic. But the webpage was always just one container for the thing that actually mattered underneath it, which is the content itself. The systems around us are getting much better at separating the two.

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Your instructions can become an answer somewhere else. Your ingredient list can become a shopping list. Your expertise can inform a recommendation you never see. Your video can become source material for a format you didn’t make. Your recipe can be useful in a place you never published it. That opens up real opportunity. It also raises the uncomfortable question of if your content can travel without your webpage, what travels with it. Your name, your authority, your attribution, your rights, your business model. Or just the information, stripped of everything that took years to build.

And then, something else happened

It’s been a busy few weeks.

The Wall Street Journal reported on something called creator-first answer engine optimization. Yes, we have apparently reached the point in the internet’s evolution where AEO needed another modifier attached to it. 😅

Okay, so we now have this slightly absurd new acronym, but stay with me. This means that brands are starting to study which creator content shows up inside AI-generated answers, so they can understand, and potentially influence, what those systems recommend.

I hate the doom narrative, and this isn’t supposed to be one. Creator content isn’t becoming less valuable just because AI can answer questions on its own, but more valuable. The problem is that the mechanisms for capturing that value haven’t caught up yet. Creators are still largely trained to measure success through pageviews, followers, likes, and reach. Meanwhile, companies are starting to look at that same creator content as input into recommendation systems. Those are two very different ways of understanding the same asset, and right now most creators are only equipped to think in one of them.

You don’t need another platform strategy

You need a content infrastructure strategy, and those are not the same thing.

A platform strategy asks what to post on Instagram, whether to make more video, how to optimize for Google, whether TikTok is worth the time, and what on earth to do about AI. A content infrastructure strategy asks what have I already created, how is it structured, where can it travel, and how does value make its way back to my business when it does.

That second question is a lot more substantial, because platforms will keep changing. Google will run another experiment. (Keep your eyes out for that!) AI systems will introduce new interfaces. Social platforms will shift their distribution again. New devices will show up that nobody’s fully planned for. And creators will keep being told they need to build something new for each one.

Creating something new for every platform isn’t sustainable and definitely not necessary.

Your archive may be more valuable than you think

Picture Riley’s site a little differently. Not as 600 old blog posts, but as a structured library holding 600 tested recipes, thousands of ingredient relationships, years of seasonal expertise, thousands of original photographs, hundreds of cooking techniques, dietary adaptations, substitution knowledge, video, stories, and audience insight built up over years of trial and error.

That’s a very different sentence than “I have a bunch of old blog posts I need to update.” One sounds like maintenance debt and the other sounds like intellectual property.

That’s the reframe I want creators sitting with. The people best prepared for whatever comes next probably won’t be the ones publishing the most. They’ll be the ones who actually understand what they already own, how it’s structured, where it can be reused, where it’s already showing up, and increasingly, under what conditions someone, or something, gets to use it.

Don’t ignore the signal

I have no idea whether Google brings AI-generated recipe images back. Maybe it does, maybe it doesn’t, and honestly, that’s not really the point.

The experiment showed us the internet is moving from systems built primarily to find content toward systems that can interpret, assemble, and present content on their own. That changes what it means to create for the internet in the first place, and it makes something I’ve believed for a while now feel a lot more urgent: creators need to stop thinking of their archive as a pile of webpages. It’s a library of structured knowledge, and the more capable machines get at understanding that knowledge, the more important it becomes for creators to understand it too.

Riley shouldn’t have to buy the peaches twice just so the internet has something new to consume next Tuesday. She already did the hard part. She created something valuable. The real question now is whether she’s built the infrastructure to make sure that value keeps working for her, and not just for whatever comes looking for it next.

Until next time,

I started Blueberri Pi because after over a decade working in content, food, and technology, I noticed we talk a lot about the content people see, but we don’t talk nearly enough about everything happening underneath it.

I spent years woirking behind the content

My career started in food, but it didn’t stay neatly inside editorial. Over the years, my work moved across content, product, partnerships, operations, and technology. Eventually, I led content engineering at SideChef, working on the taxonomy, metadata, and ingredient systems supporting a database of more than 20,000 recipes.

Today, I work with food tech platforms, creators, and content teams through Blueberri. I also spend an unreasonable amount of time thinking about metadata, publishing systems, the future of food content, why content teams struggle to explain what they do, and whatever strange new thing the internet has decided we all need to understand this month.

Welcome to the messy middle

Some publications focus on content creation. Some focus on technology. Others focus on media and the creator economy.

Blueberri Pi lives in the messy middle where all three meet.

On Fridays, (that’s goal) I explore the systems shaping how content is created, managed, discovered, distributed, and experienced. That can mean structured content one week, AI search the next, a creator-platform shift after that, and occasionally a deep dive into why a recipe database is much more interesting than it sounds.

I’m less interested in telling you how to chase the latest algorithm than understanding what’s happening behind the scenes. I don’t think creators and content professionals need another person yelling that everything they know is dead every six months. We need better ways to understand what’s actually changing. That’s what we’re doing here.

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What you’ll find here

Three big conversations are running through Blueberri Pi.

Content + systems
Structured content, content operations, content engineering, workflows, governance, publishing infrastructure, and the invisible machinery behind what eventually appears on a screen.

Content + technology
AI, search, discoverability, platforms, recommendation systems, emerging interfaces, and what happens as machines increasingly interpret information before people consume it.

Content + media
Food media, creator ecosystems, digital publishing, platform economics, partnerships, audience behavior, and the increasingly blurry line between creators, publishers, platforms, and technology companies.

If you’re new, start here

You absolutely do not need to work your way through the archive from the beginning.

Here are a few places I’d send you first.

If you’re thinking about discoverability

Old MacDonald Had an Optimization Strategy (A-E-G-E-O)

SEO. AEO. GEO. LLMO. Every new optimization acronym promises to explain the future, but they’re all circling a much bigger question about how information gets discovered and what makes content useful after the next acronym arrives.

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If you work with content systems

Structure Existed Long Before the Internet

A surprisingly human introduction to structured content, using recipes, libraries, grocery stores, and content management systems to show why structure helps information remain understandable, reusable, and useful as it moves between systems.

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A Token of My Appreciation

A look beneath the AI conversation at tokens, BERT, machine interpretation, and the real infrastructure required for AI systems to understand and generate information. It also connects your SideChef experience directly to why you think about AI and content differently.

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If you’re a creator

Blueberri Pi isn’t about teaching you how to post more. These issues are a good place to start if you’re thinking about how to make the content you’ve already created more discoverable, durable, and valuable.

Zero Click Discovery

What happens when people are still searching, cooking, and consuming content—but aren’t clicking like they used to? This issue follows food creator Nelly to explore why structure matters when discovery increasingly happens beyond your website.

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The Myth of Consistency

A challenge to the idea that creators have to keep publishing to stay visible. It explores the difference between momentum and infrastructure—and what continues working when you stop creating for 30 days.

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When Pageviews Aren’t Enough

An exploration of what happens when the old traffic-equals-revenue equation starts breaking down, and why creators need to think beyond advertising toward partnerships, diversification, and content that can create value in more than one way.

Read More

Want to go deeper into AI + creator platforms? Read The AI That Isn't Writing Your Recipes and Agents, Advocacy, and BBQ.

There’s also a podcast

Some ideas need more room than an essay. Others are simply more interesting when you can hear people think through them.

The Blueberri Podcast gives me space to go deeper into the questions I’m exploring in the newsletter. Sometimes that’s a conversation with someone working inside the industry. Sometimes it’s me pulling apart an idea that deserves more than a paragraph in Friday’s issue.

If you like the essays but find yourself thinking, OK, but I want to hear more about that, the podcast is probably where you should go next.

Listen to the Blueberri Podcast

What’s changing about content work that you can’t quite make sense of yet?

Leave a comment and tell me.

Maybe it’s AI search or your role. Maybe your traffic disappeared or your content team has seven tools and somehow still needs three spreadsheets. Maybe everyone at work keeps saying “content strategy” while meaning five completely different things.

I read the comments, and those questions help shape what I investigate next.

I don’t think anyone has the entire future of content figured out, but we can get much better at seeing what’s coming.

Welcome to Blueberri Pi.

AI transparency just became the industry standard

Substack launched an AI detection feature this week, built with Pangram. Readers can now scan any post over 100 words to get an estimate of how much was written by a human versus AI. LinkedIn followed almost immediately with its own “seems like AI slop” flag, letting users report posts they think were AI generated.

(I tried to do a screenshot of Linkedin drop down but I accidently clicked the option on someone’s post. Not sure whose it was, ah! It won’t show the “AI Slop” option on your own post. I tried. Or on any of LinkedIn’s own posts, interestingly.

I want to be upfront about where I stand on this, because I’ve never been shy about it. I use AI as a tool in my work. My headers and footers say so, and I keep an AI Usage Policy on my about page and on my website so you always know what you are getting from me. Nothing about these new detection tools changes how I operate. If anything, they confirm that the transparency I’ve already been practicing was the right call. And I do think there should be guardrails and protection on sites so that no one is deliberately deceived, so I appreciate Substack and LinkedIn’s advancements on this front. This is just the first version of these tools, so let’s see how it enhances content experiences for creators and consumers.

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The other thing I want to be honest with you about

I’m still recovering and resting. I am doing okay, and I am giving myself the time I need without apology. That means there won’t be another issue for the next 30 days.

So this one has to hold you over, and I think it will. There were some fun things that I did at the very beggining of summer that are finally live, so I’m excited to share. So ICYMI…

1. I sat down with Megan at Eat Blog Talk

Megan and I go way back, and I am always happy to get an invite back to her show. This time we talked about why recipes are not showing up on Google the way they used to, even when creators are doing SEO right. We got into how search behavior is changing and why structured content matters for the next phase of food blogging, including AI tools, meal planning apps, and voice assistants.

Listen to Episode 809 on Eat Blog Talk

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2. A guest post for Food Blogger Pro on tech partnerships

I wrote a guest post for Food Blogger Pro on how food bloggers can turn their recipe libraries into tech partnerships. This is a topic I care a lot about because tech partnerships are different from sponsor partnerships in some big ways that often get overlooked. Recipe licensing, product testing, content consulting, syndication, and AI and personalization deals all work differently than the sponsored post playbook most creators already know. Your content is an asset that you can leverage; in this article I share how.

Read the full post on Food Blogger Pro

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A freebie to tide you over

Tech partnership conversations come with their own vocab.

I spent years googling words and scribbling them down in my notebook during meetings, and I don’t want language to be the thing standing between you and a good deal.

So here’s a FREE mini glossary to help you have a leg up on the tech language in conversations and even in contracts.

Grab the Tech Lingo Mini Glossary

One more thing before I go quiet

I wanted to remind you that now you can get 20% off an annual subscription. That gets you a full year of freebies plus full access to every past issue in the archive, so there is no gap in what you can read while I am out.

The sale ends August 21, so grab it before then if it’s something you have been thinking about.

Get 20% off an annual subscription

That’s everything for now. I’ll see you soon with more great insights to share! Thanks for reading.

-Sandie

Instead of writing this week’s Blueberri Pi, I’ve been hanging out in the hospital collecting bracelets like they’re souvenirs.

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That also means no Friday issue this week and no paid podcast episode for next Monday. I’m pretty bummed because I had to reschedule a content ops with AI webinar I was really excited about. New date and time is TBD.

The good news: I’m okay and on the mend. Once I’m back on my feet, Blueberri Pi will be back to its usual mix of content systems, creator strategy, and the occasional deep dive into structured content.

In the meantime, here are five of the most popular Blueberri Pi articles from the past year. Still super relevant

The Social Shift

https://blueberripi.blueberri.co/p/instagram-search-openai-agents-creator-strategy

Does Your Blog Still Sound Human?

https://blueberripi.blueberri.co/p/does-your-blog-still-sound-human

The AI That Isn’t Writing Your Recipes

https://blueberripi.blueberri.co/p/ai-for-food-creators-without-losing-your-voice

Creators Belong on LinkedIn

https://blueberripi.blueberri.co/p/creators-belong-on-linkedin

Medata Gone Missing

https://blueberripi.blueberri.co/p/metadata-recipe-schema-food-bloggers

Thanks, as always, for reading, subscribing, and cheering me on. This community means a lot to me.

Hopefully next week the only thing bursting will be my notebook full of new ideas!

See you next Friday,

xoxo

Sandie

Sure, there were endless debates about keywords, backlinks, and meta descriptions, but at least everyone was arguing about the same acronym. Then things got complicated.

First came AEO (Answer Engine Optimization). Then GEO (Generative Engine Optimization). Then LLMO (Large Language Model Optimization).

Depending on which corner of the internet you’re standing in, there are probably three more acronyms being invented as you read this.

Every few months, a new acronym arrives promising to explain the future of discoverability, and content creators, marketers, publishers, and content teams wonder whether they need to learn an entirely new set of rules. The good news is that the core change is much simpler than the acronym explosion suggests.

Meet Nik

Nik is a 26-year-old food creator living in Manchester. His YouTube channel focuses on approachable Indian-inspired meals for busy professionals who want something more exciting than another meal deal sandwich or frozen pizza. He films in a compact apartment kitchen, edits videos after work, and spends far too much time trying to understand what the internet wants from creators this week.

A few years ago, the advice seemed manageable. Learn basic SEO. Write clear titles. Create useful content. Publish consistently. There were certainly nuances, but most creators felt like they were operating from the same playbook.

Lately, Nik feels like he’s showing up to a game where the rules change every quarter. One LinkedIn post insists that GEO is the future. A webinar claims traditional SEO is dead. A podcast guest says every creator should be learning LLMO. Before he can figure out what one acronym means, three more have arrived.

The strange part is that Nik isn’t trying to manipulate search engines. He’s trying to help people make dinner. His audience wants practical recipes, cooking confidence, and ideas they can actually use after a long day at work. Yet increasingly, discoverability feels like a full-time job layered on top of content creation.

The acronym economy

The content industry has always loved naming things. Frameworks, methodologies, and emerging trends often arrive wrapped in a memorable acronym that promises to explain the future. Sometimes that language is useful because it gives people a shared vocabulary for discussing change.

Other times, however, new terminology creates the impression that an entirely new discipline has emerged. A creator learning about GEO today is often trying to solve the same fundamental problem they were solving when learning SEO years ago. They want their work to be found by the people who need it.

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The pace of technological change amplifies this tendency. Search engines evolve. Social platforms shift priorities. AI systems introduce new ways of interacting with information. As these changes occur, the industry naturally attempts to describe them, categorize them, and package them into something understandable.

Nik notices this every time he scrolls through his feed. Everyone seems convinced they’ve identified the next major shift. Few people stop to ask whether these acronyms are describing separate futures or different perspectives on the same underlying reality.

What changed?

The reason new acronyms keep appearing is that something genuinely important is changing beneath the surface.

For most of the internet’s history, discovery was relatively straightforward. Search engines helped people find information. Websites served as destinations. The path between creator and audience was not always simple, but it was generally visible.

Today, that path looks very different. Information moves through recommendation systems, social algorithms, AI assistants, aggregators, voice interfaces, and machine-generated summaries before it reaches a person. Increasingly, content passes through multiple layers of interpretation before anyone clicks a link.

That shift creates uncertainty because nobody fully controls the journey anymore. Creators aren’t simply publishing content for readers. They’re publishing into an ecosystem of systems that decide what gets surfaced, summarized, recommended, and remembered.

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The acronyms are attempts to describe this new reality. The problem is that focusing only on the acronyms can distract us from understanding the larger transformation taking place.

The internet is reading before humans do

One of the most significant changes in digital publishing is that machines increasingly encounter content before people do.

By the time a human sees a piece of content, several systems may have already processed it in different ways. Each system is attempting to determine what the content is about, who it might help, and whether it deserves visibility.

For creators like Nik, this can feel intimidating. It sometimes sounds as though success depends on understanding every algorithm, every platform, and every emerging technology. That’s an impossible standard because the systems themselves continue to change.

The mistake many creators make

When a new optimization trend appears, many creators immediately begin asking tactical questions.

• Should I rewrite old posts?

• Should I change my titles?

• Should I restructure my content?

• Should I learn a new framework?

Those questions are understandable, but they often focus on short-term adaptation rather than long-term value.

Nik notices this pattern in creator communities. Discussions quickly become dominated by tactics, checklists, and optimization tricks. Meanwhile, the more important conversation often gets overlooked.

The creators who survive multiple platform shifts rarely succeed because they mastered every tactic. Instead, they build durable assets that remained useful as technology evolved around them.

Durable content versus disposable content

Nik’s recipe for masala roasted potatoes may be discovered through Google today, YouTube tomorrow, and an AI assistant next year. The mechanism changes, but the usefulness remains. Someone searching for a reliable recipe still has the same need regardless of how they arrive.

This distinction matters because discoverability systems are temporary. Platforms change. Features come and go. Entire channels rise and fall. The internet is littered with examples of once-dominant platforms that now occupy only a small corner of digital history.

Useful content, however, often finds new paths to audiences. It adapts because its value isn’t dependent on a single discovery mechanism.

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The question beneath every acronym

When viewed through this lens, GEO, AEO, SEO, and LLMO begin to look less like competing ideas and more like different attempts to answer the same question.

• How does information move?

• How does information get understood?

• How does information reach the people who need it?

These are worthwhile questions. In fact, they’re becoming more important as content ecosystems become more complex.

Discoverability is not the goal. We’ve been programmed to think it is, but discoverability is a means to an end. The goal is to help someone solve a problem, learn something new, make a decision, or accomplish a task. The acronym may change. The purpose doesn’t.

Thinking beyond the platform

At some point, Nik stops worrying about which acronym will win. Instead, he starts asking a different question. What would make this content valuable five years from now?

Instead of optimizing exclusively for the platform, he begins thinking about usefulness. Instead of chasing every trend, he starts focusing on clarity, expertise, and structure. Instead of asking how content will perform this month, he considers how it might continue creating value in the future.

Ironically, this mindset often produces better results in the present as well. Content that is clear, trustworthy, and useful tends to perform well across multiple systems because it was designed around the audience rather than the algorithm.

Expand beyond discoverability

Content should be able to travel. It should move across platforms. It should adapt to different formats. It should remain useful in different contexts. Most importantly, it should continue creating value long after its original publication date.

This idea sits at the heart of the final stage of the COSE™ framework: Expand for Reach and Revenue.

The deeper purpose of Expand is longevity.

A recipe that helps someone today is useful. A recipe that continues to help people 10, 15, 20 years from now becomes more valuable. The same is true for articles, videos, frameworks, tutorials, and educational content. The most impactful content often extends beyond the moment it was created for.

Nik eventually realizes that this is the question he should have been asking all along. Not whether GEO will replace SEO. Not whether AEO is more important than LLMO. Not even whether his next video will perform well next week.

“Will this still be useful after the next platform update?”

A great recipe can move from a blog to YouTube, from YouTube to an AI assistant, from an AI assistant to a newsletter recommendation, and eventually into someone’s family recipe collection.

The platform changes, and the value remains.

In that sense, Expand is not simply about reaching more people. It is about extending the life, usefulness, influence, and impact of content over time. It is about creating work that can outlast the algorithm, the trend and perhaps even the platform itself.

That’s why I think of Expand as a question of legacy.

Not what content performs best today. What content continues to matter tomorrow?

Who cares about the acronym

The history of the internet suggests that more acronyms are coming. There will be new platforms. New systems. New interfaces. New ways of discovering information. And inevitably, new labels designed to explain them.

Some will be valuable. Some will be forgotten. Most will represent attempts to make sense of a rapidly changing landscape.

The creators who thrive won’t necessarily be the ones who predict every trend. They’ll be the ones who understand that beneath every technological shift is a remarkably consistent human need. People are still looking for answers, ideas, inspiration, and expertise.

Honestly, who cares whether GEO replaces SEO? Why not focus more on what you are creating and if it will still matter after the next acronym arrives?

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If you enjoy essays like this, subscribe to Blueberri Pi for weekly explorations of content systems, digital publishing, food media, and the future of content work.

Enjoying Blueberri Pi? Try an annual subscription. Annual members receive member-only resources, access to my exclusive podcast, deeper dives into industry shifts, and help support the independent research and writing behind every issue.

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While acronyms come and go, thoughtful ideas are worth investing in.

What do you think?

Are GEO, AEO, and LLMO genuinely different disciplines, or are they different names for the same underlying challenge?

Leave a comment and join the conversation. I’d love to hear how you’re thinking about discoverability, AI, and the future of content.

The future of content work won’t be shaped by a single platform or the next trending tool. It’ll be shaped by the systems, ideas, and people willing to understand what’s changing beneath the surface.

If that sounds like the kind of conversation you want to be part of, you’re in the right place.

See you next Friday.

— Sandie

In this episode of The Blueberri Podcast, I share how I went from completely confused by MCPs to realizing they’re part of a much bigger story about content, …

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In the AI world, the MCP has become one of the trending terms this year. Some people have even started calling it the “USB-C for AI” because it creates a standardized way for AI systems to connect to tools, services, and data sources. As AI agents become more capable, companies are focused on how those systems interact with the outside world, and how to govern, monitor, and secure those interactions.

None of that is particularly surprising to me.

I’ve been hearing about MCPs for the better part of a year. If you’ve spent any time around content intelligence, content engineering, or AI conferences lately, you’ve probably heard the term too. It seems like every event I’ve attended has included at least one conversation about MCPs, agentic systems, APIs, or the future of AI-powered workflows.

But until recently, it still felt like something happening somewhere else. The conversations were largely happening among developers, AI researchers, enterprise software companies, and technology leaders trying to prepare for what comes next.

Then Kit announced MCP support, and I thought that was pretty cool.

Suddenly, a concept that had been living in the conference rooms, webinars, white papers, and technical presentations showed up inside a tool many creators already use every day. Whenever that happens, I pay attention.

(This is not a sponsored issue, btw. But I just started using Kit and thought this was really cool, so here we are.)

When technical concepts start appearing inside creator tools, they’re usually signaling a larger shift.

Publishing keeps changing

For most of human history, publishing was relatively simple. You created something and shared it with people. A poem became a book. A recipe became a recipe card. A newsletter became an email. The content had one destination and one audience.

The internet changed that.

Today, a single piece of content might appear on a website, inside a newsletter, in search results, on social media, inside recommendation engines, and inside AI systems. The content itself hasn’t become more complicated. The ecosystem around it has. MCPs hint at a future where content, creator tools, audience data, and AI systems work together in ways that weren’t previously possible.

The future is coming fast, so what should creators do about it?

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Most recipes follow a familiar pattern. There’s usually a title, a list of ingredients, a set of instructions, a serving size, and sometimes notes or substitutions. Whether you’re reading a handwritten recipe card from a grandparent or browsing a modern food blog, the format feels so natural that most of us never stop to question it.

But that structure didn’t happen by accident.

Someone, somewhere, decided that ingredients should be separated from instructions. Measurements should be listed before cooking begins. Steps should follow a logical order. Over time, those conventions became expectations. And because they became expectations, recipes became easier to read, easier to share, and easier to reproduce.

Before anyone talked about metadata, content models, or structured content, people were already organizing information.

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Humans have always organized information

One of the biggest misconceptions about structured content is that it’s a technology concept. It’s a human concept.

Libraries use structure. Grocery stores use structure. Maps use structure. Museums use structure. Even your kitchen probably uses structure. There’s a reason spices aren’t mixed randomly with canned goods and baking supplies aren’t stored in six different rooms.

Structure reduces effort. It helps people find things faster. It helps information make sense. It helps knowledge survive beyond the person who created it.

When librarians created classification systems, they weren’t trying to optimize for search engines. They were trying to solve a human problem. As collections grew larger, finding information became harder. Structure was the solution.

The internet didn’t invent this challenge; it just made it bigger.

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What changed when information became digital?

The internet dramatically increased the amount of information being created and shared. Suddenly, content wasn’t living in a single book, filing cabinet, or library shelf. It was spread across websites, apps, databases, search engines, social platforms, and devices.

The old challenge remained. People still needed to find things. The difference was scale.

A cookbook might contain a few hundred recipes. A recipe platform might contain hundreds of thousands. A library might catalog millions of books. Search engines now organize billions of pages. At that scale, structure becomes less of a convenience and more of a necessity.

That’s why so many conversations today involve metadata, taxonomies, schemas, content models, and structured content. These aren’t entirely new ideas. They’re modern solutions to a very old problem.

How do we organize information so people can actually use it?

The recipe card and the CMS

A few years ago, someone asked me what structured content actually is. I could have given a technical answer. Instead, I showed them a recipe card. A recipe card is surprisingly close to a content model.

It has a title, ingredients, instructions, preparation time, serving size (yield), and notes.

Each piece of information has a purpose. Each piece belongs somewhere specific. If someone wrote the instructions where the ingredients should go, the recipe would still contain the same information, but it would become much harder to use.

Modern content management systems work the same way.

Imagine entering a recipe into a CMS. Instead of pasting everything into one giant text box, the system gives you separate fields for the recipe title, ingredients, instructions, cooking time, nutrition information, cuisine type, and categories. Each piece of information is stored independently.

At first, that can feel like extra work. But separating the information creates possibilities. A recipe platform can display cooking time in search results. A shopping experience can pull ingredients into a grocery list. A mobile app can show only the instructions while someone is cooking. A recommendation engine can suggest similar recipes based on cuisine or dietary preferences.

None of those experiences are possible if everything is trapped inside a single block of text. The recipe itself doesn’t change. The structure does.

That’s why content management systems aren’t really managing pages. They’re managing information. The more clearly information is organized, the easier it becomes to find, retrieve, reuse, and adapt for different experiences.

That’s also why structured content often feels invisible when it’s working well. The structure fades into the background, allowing the information itself to take center stage.

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People often use the terms interchangeably because they’re closely related. Structured data is usually built from structured content. If information isn’t organized first, it’s much harder to describe consistently later.

That’s why content professionals, developers, SEO specialists, and platform teams sometimes use different terminology. They’re often talking about different layers of the same system.

Why everyone is talking about structure again

If you’ve been paying attention to content and AI conversations lately, you’ve probably noticed that structured content keeps coming up.

Adobe has been discussing structured content as a foundation for automation and personalization. Content operations professionals talk about modular content. Technology companies are investing heavily in content systems that make information easier to manage, retrieve, and reuse.

At first glance, it might seem like AI created this renewed interest. I don’t think that’s what happened. I think AI reminded us why structure mattered in the first place.

The more information moves through systems, the more important it becomes for that information to retain its meaning. Search engines, recommendation engines, shopping experiences, recipe platforms, voice assistants, and AI tools all need ways to understand what information represents.

The challenge isn’t new. What’s new is the number of systems interacting with content. And that number is growing quickly.

When structure becomes a business advantage

For a while, creators could think about content as a destination. Someone visited a website. Read an article. Made a recipe. Clicked an ad. The experience began and ended on a webpage.

That model is starting to change. Recent reporting has highlighted growing concerns among food bloggers as AI-powered search experiences provide recipe answers directly within search results. Whether creators like this shift or not, it reveals something important.

Content is being separated from the place where it was originally published. Information is traveling.

The question is whether it can travel well.

Ann Rockley, one of the pioneers of intelligent content, described intelligent content as content that is discoverable, reusable, reconfigurable, and adaptable. She argued that structured, semantically rich content becomes easier to find, personalize, deliver, and reuse across different channels and experiences.

Those ideas were originally developed for enterprise content systems, but they’re becoming more relevant to creators.

If someone asks an AI assistant for a high-protein Malaysian-inspired dinner, or a personalized recipe recommendation based on dietary preferences, the system is looking for information it can understand.

The easier your content is to understand, the easier it becomes to retrieve, connect, personalize, recommend, and reuse. That doesn’t guarantee revenue, but it does create opportunity.

A recipe that more systems can understand can potentially appear in more places. It may power search experiences, shopping integrations, recipe collections, recommendation engines, personalized meal planning, future AI experiences, and opportunities that don’t exist yet.

That’s one reason I believe structure matters more today than it did five years ago. Personalization is becoming normal, AI is becoming a discovery tool, and content moves through systems before it reaches people. As those systems become part of how information is discovered and delivered, the ability for content to retain its meaning across different experiences becomes more important.

The creators who benefit most from future platforms will be the ones whose content can travel the farthest while retaining its meaning.

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Meet Kami

Kami is a food creator in the Bay Area who specializes in Malaysian fusion cooking. Some of her recipes are inspired by dishes she grew up eating, while others blend traditional Malaysian flavors with ingredients and techniques she discovered in California. On any given week, she might be filming a recipe video, testing a new dish, writing a newsletter, or responding to questions from readers who have made her recipes at home.

Like many creators, Kami didn’t spend much time thinking about structure. She thought about whether the recipe worked, whether the instructions were clear, and whether the finished dish looked delicious. If someone could successfully recreate the recipe in their own kitchen, she considered it a success.

For a long time, that was enough.

The recipe started showing up everywhere

One day, Kami noticed that the same recipe was appearing in far more places than she originally intended. It lived on her website, but pieces of it were also showing up in newsletters, social media posts, recipe collections, search results, and cooking apps.

Readers were saving screenshots of ingredient lists. Search engines were displaying cooking times and ratings directly in results. AI tools were summarizing recipes when users asked questions. The recipe was no longer just a webpage. It had become information moving through multiple systems.

That’s when Kami started seeing her content differently. The ingredients weren’t just ingredients. The cooking time wasn’t just a helpful detail. The instructions weren’t simply a block of text. Each piece of information served a purpose and could be reused independently of the recipe itself.

The structure in the recipe had become visible.

For most of human history, structure has helped people find information, share knowledge, and make sense of complexity. Today, those same principles help information move through search engines, recommendation systems, shopping experiences, and AI tools. The technology may be new, but the underlying idea isn’t. The recipe wasn’t structured because a machine needed it; it was structured because people did. The machines just arrived later, and as more systems begin interacting with content, that old lesson feels surprisingly relevant again.

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Blueberri Pi will always include free issues because I believe these conversations should be accessible to anyone interested in content, technology, and the future of publishing.

For readers who want to go deeper, paid subscriptions help support the research, writing, podcast production, and educational resources that make this publication possible.

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The newsletter is where I share ideas. The podcast is where I unpack them in more depth.

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One thing to think about this week

The next time you follow a recipe, walk through a grocery store, browse a library, or search for something online, pay attention to the structure hiding in plain sight.

You might discover that some of our most important systems aren’t built on entirely new ideas.

They’re built on old ones that still work.

See you next Friday.

— Sandie

I was talking with my manager about what growth might look like and where I wanted my career to go next. We were brainstorming possibilities when she suggested something that completely caught me off guard.

“What if we renamed your team the Content Engineering team?”

That’s not a real thing.

I genuinely thought it sounded like a startup gimmicky buzzword. Something somebody had invented five minutes earlier and hoped everyone else would accept without asking questions.

In this first episode of The Blueberri Podcast, I share the story of how working alongside engineers changed the way I think about content, structure, publishing systems, and the invisible layers behind digital experiences.

This episode is also kind of an introduction.

You’ll learn how I found my way into this corner of the content world, why I wanted to create an audio-only podcast, and what kinds of conversations we’ll be exploring together going forward.

If you’ve ever heard the term content engineering and wondered what it actually means, or if you’ve ever found yourself translating between content, product, and engineering teams.

And if the episode sparks a thought or a question, leave a comment. Some of my favorite conversations start exactly that way!

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Because it’s the first episode, it’s completely free.

After that, new episodes of The Blueberri Podcast will be delivered to paid subscribers every Monday morning.

Listen to Episode 1: Content Engineering Is a Real Thing

Resources Mentioned:

• Read Designing Connected Content: Plan and Model Digital Products for Today and Tomorrow

• Check out Blueberri.co

Certain words kept appearing throughout the presentation. The presenter moved through them naturally, assuming the audience understood what they meant. Maybe they did. AI has become so ingrained in everyday conversation that it’s easy to forget how quickly the language around it has become normalized. Still, I couldn’t help wondering if everyone listening actually knew what a token was or why they should care.

I thought about my own relationship with AI that started in a very different place than it does for most people today. My first experience with a machine learning model wasn’t ChatGPT. It wasn’t Claude. It wasn’t even the early versions of generative AI that dominate headlines now.

It was BERT.

Before ChatGPT, there was BERT

Back in 2019, I was leading the Content Engineering team at SideChef. We were building shopping experiences around recipe content, and the problems we were solving looked very different from the AI conversations happening today. Nobody was debating whether machines would replace writers. Nobody was creating AI agents. Instead, we were trying to understand how machines interpret information and why they so often got it wrong.

One of the questions we ran into all the time sounded simple. How does a system know that canned tuna and tuna in water are describing essentially the same thing?

Multiply that problem across thousands of ingredients and hundreds of thousands of grocery products and you begin to see the challenge.

Looking back, I realize we weren’t actually teaching machines about ingredients. We were teaching them about relationships. We were defining how information connected to other information. We were creating structure that allowed systems to interpret meaning more accurately. BERT represented a major step forward because it helped machines understand language in context.

BERT was a machine learning model introduced by Google that helped computers better understand the meaning and context of language.

Unlike ChatGPT, Claude, and Gemini, which are designed to generate answers and create new content, BERT’s primary job was understanding what existing text meant. In many ways, BERT helped machines become better readers, while today’s large language models are designed to be both readers and writers.

That experience fundamentally changed the way I think about content.

In many ways, it also explains why I see today’s AI conversation differently than most people do.

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From the Blueberri Podcast

While writing this issue, I kept thinking about a conversation I had with myself while recording the very first episode of The Blueberri Podcast.

The episode starts with a simple question.

How did we get here?

Not just to ChatGPT, Claude, and Gemini, but to a world where content, search, recommendation engines, grocery apps, voice assistants, and AI systems all rely on structured information to function.

In the trailer, I share why I started the podcast and what listeners can expect. We’ll talk about content strategy, structured content, creator ecosystems, publishing systems, and the invisible infrastructure that shapes how information moves through modern platforms.

If you’ve ever found yourself exc ited by the systems behind the content, you’re probably going to enjoy what’s coming.

The first full episode launches Monday.

Why do they call it a token?

The name actually makes more sense than it first appears.

Depending on the model, a token might be a whole word, part of a word, punctuation, or even a space. When you type a question into ChatGPT, Claude, or Gemini, the system breaks your request into tokens before it can understand and respond to it.

Every question consumes tokens. Every answer generates more tokens. The longer the conversation, the more tokens are processed. In other words, tokens are how AI companies measure the work being performed behind the scenes.

The technical details are interesting, but the bigger takeaway is what tokens represent. They represent computation. They represent processing power. They represent real infrastructure running somewhere in a data center. Every summary, recipe rewrite, customer support answer, or content recommendation requires resources to generate.

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I still love creating Your Friend in Food. Those conversations are personal. They’re about food, creativity, memories, identity, and the human stories that connect us.

But this podcast is different.

The Blueberri Podcast is where I get to explore another side of my world—the side that’s fascinated by content systems, digital publishing, structured content, content operations, and the invisible infrastructure that shapes how information moves through organizations and across the web.

This trailer is free because I wanted to give you a taste of what’s coming. In the first episode, I share the story of the first time I heard the term content engineering, a moment that completely changed how I think about content.

After that, the rest of the podcast is available to paid subscribers.

I do realize there’s something wonderfully meta about asking content professionals to pay for content about content.

If you’ve ever found yourself fascinated by the systems behind content, curious about where publishing is headed, or wondering why content work feels more complicated than it did five years ago, I think you’ll feel right at home here.

Thanks for listening.

Welcome to The Blueberri Podcast.

Let’s make the invisible visible.

I’ve been to five of the seven continents so far, and my passport is slowly running out of room for stamps and visas. Somewhere in my early twenties, I decided I was going to see the world. I didn’t have a detailed plan. I just knew I wanted to go.

All I needed was a passport and a willingness to move.

To this day, I’m still trying to figure out how to get to Antarctica. It’s going to happen.

The thing I love most about travel isn’t necessarily the destination. It’s the movement. The idea that a single person can wake up in one place and find themselves somewhere completely different a day later. The journey changes you, but it also changes how you see the world around you.

Lately, I’ve been thinking about content the same way.

For years, most of us created content as if it would live in one place. A blog post belonged on a blog. A newsletter belonged in an inbox. A social post belonged on a social platform. Each piece had a destination and stayed there.

That isn’t how the internet works anymore.

Content increasingly moves between websites, newsletters, apps, recommendation engines, AI systems, voice assistants, social platforms, and experiences that often reinterpret information before audiences ever see it. In many ways, content is traveling farther than ever before.

Most content was never designed to travel

Brooke lives in Raleigh, North Carolina, where her lifestyle blog, The Sunday Suitcase, has grown into a full-time business. What started as a place to share travel stories, home projects, routines, and everyday moments now supports a newsletter, social channels, brand partnerships, digital products, and a growing archive of content that reaches people in dozens of different ways.

For a long time, she would publish a blog post, share it on social media, send it to her email list, and move on to the next idea. The content lived in a few predictable places, and keeping everything updated felt manageable. Then the business grew.

A single travel guide became a blog post, a newsletter feature, multiple Pinterest pins, a Reel, a downloadable resource, and a collection of social posts. The same information started appearing across more channels, more platforms, and more systems than Brooke could easily keep track of.

One afternoon, she needed to update a hotel recommendation in an older travel guide. The change itself took less than a minute. Finding every place that recommendation appeared took nearly an hour. Her content now had more places to go than ever before.

The internet had changed. Content now moved through websites, newsletters, social platforms, recommendation engines, apps, and increasingly, systems that repackaged information before audiences ever saw the original source. Most content was never designed for that kind of journey. But that’s exactly the journey modern content is expected to take.

The content became the source

Brooke didn’t solve the problem by working longer hours or adding another tool to her stack. Instead, she started looking at her content differently and started treating her entire content library and channels as different versions of the same idea. The destination changed, but the information often stayed remarkably similar.

A travel guide wasn’t just a blog post anymore. It had recommendations, photos, packing tips, itineraries, and personal stories. Once she started thinking about those pieces separately, repurposing became easier because she wasn’t constantly rewriting content from scratch.

Her blog became the source; everything else became an adaptation.

The copy-and-paste internet

Since the twenty-teens, creators were taught to think about content as finished pieces. A blog post was a blog post. An email was an email. An Instagram caption was an Instagram caption. Every channel got its own version.

That approach worked when content lived in fewer places.

Today, creators are publishing into ecosystems rather than individual channels. A single recipe might appear in a newsletter, an app, a recommendation engine, a social feed, and an AI-generated summary.

The irony is that creators are often doing more publishing work than ever while producing roughly the same amount of information. The content isn’t multiplying. The destinations are.

Many content teams are discovering that the old copy-and-paste model simply doesn’t scale anymore.

What brands figured out first

While creators are debating SEO, AEO, AI Overviews, and traffic declines, some of the world’s largest organizations are quietly changing something much bigger. They’re changing how content gets created.

Instead of building content separately for every channel, many brands are moving toward modular content systems. Product descriptions, FAQs, images, specifications, and promotional copy are being broken into smaller reusable components and stored in central repositories.

They’re not creating content for websites, apps, kiosks, voice assistants, and future platforms individually; they’re creating content once and distributing it everywhere. The content stays consistent, updates happen faster, and teams spend less time rewriting and more time creating. Most importantly, the content becomes easier to reuse.

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Why this matters beyond enterprise

At this point, you might be thinking, “That’s great for large organizations, Sandie, but I run a blog.”

That’s exactly why it matters.

The same forces driving enterprise content transformation are affecting creators too. The number of places your content can appear keeps growing. Your content might show up on your blog, in your newsletter, inside a recommendation engine, in a voice assistant response, on a mobile device, or inside an AI-generated summary.

So it’s not whether content will travel. It’s whether your content is prepared for the journey.

The COSE™ connection

This trend connects directly to the COSE™ Framework. It’s the framework I created to help creators and content teams operationalize all the advice I give.

Create with Structure, the first pillar, means building content intentionally so it can be reused later. Organize for Reuse means storing information in ways that make that reuse possible. Those two ideas create the foundation for everything that comes next.

When content is structured and reusable, it becomes easier to Share with Intention across multiple channels. It also becomes easier to Expand for Reach and Revenue because the same content can support more experiences without requiring more work.

The more places content needs to go, the more structure matters. That isn’t just a COSE™ principle. It’s increasingly becoming a publishing reality.

The future may look more modular than we think

I don’t think most creators need to rush out and implement enterprise content management systems. What I do think is that creators should start paying attention to the direction the industry is moving.

The internet increasingly rewards content that can move. AI systems prefer structured information. Platforms prefer consistency. Audiences expect content to appear wherever they happen to be. Every year, the number of destinations continues growing.df

Meanwhile, most workflows still assume content lives in one place.

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Discovery has places to go, too

Content isn’t the only thing becoming more distributed.

The way people discover content is changing as well. While Google remains the dominant search engine, users are increasingly finding information through AI assistants, recommendation engines, social platforms, communities, and alternative search tools.

One example is DuckDuckGo. Unlike traditional search engines, DuckDuckGo takes a different approach to search and privacy while still delivering results from a variety of sources. As creators think about the future of discoverability, understanding alternative discovery channels becomes increasingly important.

If you missed it, I recently published a guide explaining how DuckDuckGo works, where its results come from, and why it matters in today’s evolving search landscape. Keep an eye out, because I’ll be exploring more search engines soon.

Read the complete guide to how DuckDuckGo works and where its search results come from.

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Blueberri Pi updates

Starting with the next issue, I’ll begin introducing paid content for Blueberri Pi.

Free subscribers will continue receiving the full weekly issue every Friday. Paid subscribers will receive additional resources designed to help put these ideas into practice, including framework guides, visual explainers, worksheets, templates, and behind-the-scenes notes.

More details next week.

I’m also excited to share that the Blueberri Podcast is launching soon.

This voice-only podcast will explore the future of content work, creator ecosystems, food media, structured content, publishing systems, and the invisible infrastructure shaping how information moves through the modern internet. Think of it as the conversational companion to Blueberri Pi.

Some ideas work best as essays. Others deserve a conversation.

Thanks for reading.

See you next Friday!

A lot of creators and content teams still think they’re solving traffic problems, ranking problems, or consistency problems. Sometimes they are. But now more than ever, what they’re really navigating are more interpretation problems. The systems surrounding content are changing faster than the publishing habits most people built their businesses around, and many of these shifts still look deceptively familiar on the surface. That’s why so many creators continue optimizing for behaviors the internet itself is slowly moving away from.

Meet Maya

Maya lives in Phoenix, Arizona, where most mornings begin with coffee, analytics dashboards, and a growing number of browser tabs she swears she’ll close eventually. Five years ago, she started Casita Table, a food blog documenting weeknight recipes inspired by her Puerto Rican grandmother and the practical reality of cooking for two after long workdays. At the time, she was still working full-time in healthcare administration, testing recipes at night in a small apartment kitchen while trying to learn WordPress, Pinterest, and food photography all at once. What started as a creative outlet slowly grew into something much bigger.

Today, Casita Table is Maya’s full-time business. Her income now comes from a mix of display ads, affiliate links, sponsored partnerships, newsletters, and digital products tied to meal planning and pantry cooking. On the surface, the business looks stable. Her recipes still rank well, traffic is still coming in, and brands continue reaching out for partnerships. But despite all of that, Maya still feels like she’s managing an entire publishing operation instead of simply running a blog.

Most of Maya’s workday no longer revolves around cooking. It revolves around maintenance. Updating old posts. Rewriting metadata. Troubleshooting Pinterest performance. Reviewing analytics. Formatting newsletters. Repurposing recipes for Instagram and short-form video. Managing plugins. Responding to algorithm changes. Keeping older content discoverable while trying to publish new recipes fast enough to stay visible online.

A few years ago, Maya became almost obsessive about FAQ sections because every food blogging conference, SEO webinar, and optimization guide seemed to repeat the same advice. Add FAQ schema. Answer common questions. Increase your chances of appearing in rich results. She spent hours researching what readers might ask, rewriting questions to match search behavior, and formatting every recipe carefully enough for Google to interpret clearly. Some nights, the FAQ section took longer to write than the recipe introduction itself because it felt directly connected to visibility and traffic.

At the time, the effort felt worth it. FAQ rich results made recipes stand out in search, and structured answers felt like a competitive advantage in an increasingly crowded publishing environment. Maya genuinely believed she was building discoverability into her content one question at a time. But lately, the traffic patterns have shifted, AI-generated summaries increasingly answer questions before users click, and many of the carefully structured FAQs she spent years optimizing no longer seem to create the same impact they once did.

By 11:48 PM on a Tuesday night, Maya wasn’t asking whether FAQ sections still helped readers. She was wondering whether search itself still worked the way her business was built around. These days, fewer people seem to click. They ask questions, but machines answer first. The internet doesn’t search like it used to, and I think creators like Maya are starting to feel that emotionally long before they can fully explain it strategically.

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The shift from search to answers

I recently came across an article from Content Science titled What Is Answer Engine Optimization (AEO)? The article defines AEO as the practice of structuring and optimizing content so AI-driven systems can extract, summarize, and deliver it directly in response to user questions.

For nearly two decades, creators built content around search behavior. That’s twenty years. Let that sink in. People searched, search engines ranked pages, and websites competed for clicks. Entire publishing systems evolved around that environment through keywords, metadata, search intent, backlinks, featured snippets, FAQ sections, and evergreen optimization. Creators learned how to structure content for search engines because visibility depended on it. But answer engines change the relationship between questions, answers, and websites themselves because increasingly people are not searching for pages. They are searching for answers, and increasingly, AI systems are delivering those answers directly.

The goal used to be “How do I rank?” but now the question that is showing up more is, “How do I become interpretable?” That is a very different kind of publishing environment, and I think we are still underestimating how much this changes the internet. The shift is not only technical, but it’s also operational, behavioral, and structural all at once.

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Why FAQ sections suddenly feel different

Google itself has already started quietly signaling parts of this transition. Its updated FAQ structured data guidance now limits FAQ rich results primarily to authoritative government and health websites instead of broadly supporting FAQ-rich experiences across general publishing sites. For years, creators treated FAQ schema almost like a required SEO ingredient because it visibly improved search experiences. Now the incentives are changing, not because structure stopped mattering, but because the systems interpreting content are changing.

This is where conversations about AEO sometimes become too basic. The narrative quickly turns into “SEO is dead,” “websites are dead,” or “optimize for AI,” but I don’t think that’s what’s actually happening. What’s happening feels more operational than apocalyptic because the internet is shifting from retrieval to interpretation. Search engines were designed to retrieve pages, while answer engines are designed to synthesize information. That distinction changes the role content plays online because content no longer competes only to be found. It competes to be understood.

That’s why structure suddenly matters now for machine readability, semantic clarity, contextual understanding, authority, trust, citation, and answerability. Not sure if that last one is a word, but we are gonna roll with it.

The irony is that creators spent years learning how to structure content for search engines only to arrive at a moment where machines may not need users to click the page at all. Instead, machines are starting to extract, summarize, and reinterpret information before audiences ever interact with the original source directly.

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Authority is becoming distributed

Authority is now coming from ecosystems instead of isolated websites. It’s not just about what you publish yourself, but who references you, where your expertise appears, whether communities trust you, and whether your ideas consistently show up across platforms. That feels incredibly important because AI systems do not just interpret webpages anymore. They interpret patterns.

YouTube videos, Reddit discussions, LinkedIn posts, podcasts, forums, and community conversations are shaping how information gets interpreted online. Visibility is becoming distributed across ecosystems instead of concentrated in single destinations. I think creators already feel this shift emotionally because one piece of content now has to perform in search, adapt for social platforms, support newsletters, survive algorithm changes, appear in AI summaries, and move across multiple formats at once. Modern content stopped existing in just one place or moving in one direction.

This also connects directly to something I wrote about recently in Content Work Was Never Designed for the Internet We Have Now. Most content workflows were built for a simpler publishing environment with one website, one destination, and one primary discovery channel. That’s not the reality creators operate in because content now moves across fragmented systems, AI interfaces, recommendation engines, feeds, summaries, search experiences, and platform ecosystems at the same time. The systems surrounding content keep getting more complicated, and structure is increasingly the thing helping content move clearly across all of them.

The end of the chase

Maya didn’t completely remove her FAQ sections overnight, but she stopped treating them like the center of her visibility strategy. What changed first was her mindset. She focused less on adding separate FAQ blocks and more on improving clarity throughout the entire recipe itself. Instructions became more structured. Ingredient notes became more specific. Substitutions, storage guidance, and cooking context became easier to scan naturally within the recipe instead of being buried at the bottom purely for search optimization.

She also stopped depending so heavily on Google as the center of her discoverability strategy. Instead of creating content only for search rankings, Maya started building stronger connections between her newsletter, Instagram, Pinterest, short-form video, and community conversations. A question someone asked in her newsletter might become a future recipe update. A comment from Instagram could turn into a short-form cooking tip. Instead of optimizing isolated blog posts, she started thinking more intentionally about how knowledge moved across her entire content ecosystem.

Before, every algorithm update felt personal because her visibility depended so heavily on one platform continuing to behave predictably. Once she stopped treating FAQ tactics as the foundation of her business, the pressure started easing. Her content became less about chasing search features and more about building a clearer, more adaptable publishing system underneath the work itself. Ironically, that structure ended up making her content stronger for both readers and machines anyway.

Maya still pays attention to SEO because search still matters. But now she sees structure differently. It’s the thing helping her recipes stay understandable, reusable, and discoverable as the internet keeps changing around them.

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The future may belong to interpretable content

Maybe FAQ sections were never really about FAQs. Maybe they were one of the earliest signs that creators were already learning how to structure information for machine interpretation long before most people realized that was happening. The systems doing the interpreting are evolving again, and honestly, I think we are entering an era where content strategy starts looking a lot more like knowledge design than traditional publishing.

This shift changes how creators think about authority, visibility, and even the purpose of content itself. Content increasingly needs to move clearly between humans, systems, and platforms without losing meaning along the way. The creators and organizations that adapt best probably will not be the ones producing the most content. They will be the ones building the clearest, most structured, most trustworthy, and most interpretable systems around their knowledge.

Maybe the FAQ section is not disappearing at all. Maybe it is evolving into proof that modern content now needs to communicate with both humans and machines at the same time. That’s a very different publishing environment than the one most creators originally learned to work within, and I think we are still early. We’re only just starting to see where this goes. Which means creators still have time to build more resilient systems before the next version of the internet fully settles into place.

Until next time…

See you next Friday.

A lot of creators and content teams still think they’re dealing with visibility problems, quality problems, or consistency problems. Sometimes they are. But as time goes on, what they’re really dealing with are interpretation problems and operational problems that are much harder to recognize. The frustrating part is that these issues rarely look structural at first, which is why so many people keep trying to solve them by producing more content instead of looking at the systems underneath the work itself.

Meet Daniel

Daniel lives in Tampa, Florida, where most mornings start the same way. Coffee on the counter. Laptop open before the sun fully settles over the water. Slack notifications already waiting for him before he’s even had breakfast. A few years ago, he was a marketing major trying to figure out how to combine his interest in branding, wellness, and digital storytelling into something that actually felt meaningful. That eventually became Pulse & Pine, a wellness brand focused on functional drinks, supplements, and educational content on everyday health routines.

At first, the business felt simple. Daniel handled the Instagram account himself, wrote the emails late at night, filmed short videos for TikTok, and answered customer DMs between packing orders. The content felt personal because it was personal. Every caption, campaign, and product page lived inside his head, which meant the business could move quickly without needing much structure. But as the company grew, so did the complexity surrounding the content.

Now Daniel is the content team, even though technically there are other people involved. There’s a freelance designer helping with social graphics, a contract copywriter handling newsletters twice a month, a part-time operations assistant scheduling content, and an agency supporting paid campaigns. Everyone contributes something to the workflow, but Daniel still acts as the central connection point between all of it. Every approval, update, clarification, and messaging adjustment eventually flows back through him.

By Tuesday morning, he already has multiple Slack threads open with people asking questions about approvals, messaging, timelines, and which version of the copy is actually the latest one. One person is updating the website while another is scheduling the newsletter, and social media is still using older messaging because nobody realized the positioning changed during yesterday’s meeting. A product launch graphic is using outdated language from two weeks ago because the latest revisions were buried in comments inside a Google Doc nobody reopened. Everyone on the team is smart, capable, and working hard, but the workflow itself keeps creating confusion.

Nothing inside Pulse & Pine looks broken from the outside. Campaigns still go out, gets published, and meetings still happen. But underneath all of that, it’s still pretty messy because the operational system supporting the content was never designed to handle the level of coordination modern content requires. After a while, Daniel starts treating constant clarification as a normal part of the job instead of recognizing it as a sign that the system itself is struggling to keep up.

Why this is becoming more common

One of the biggest changes happening right now is that content no longer lives in one place or moves in one direction. A blog post might also become a newsletter, a social campaign, an AI summary, a product recommendation, a shopping integration, or part of an internal knowledge system. The problem is that many workflows still operate as if content only has a single destination. That disconnect creates operational stress that most teams feel long before they fully understand what’s causing it.

What makes this difficult is that operational complexity rarely announces itself clearly. Most people experience it as duplicated work, endless revisions, unclear ownership, inconsistent messaging, or the feeling that everything somehow takes longer than it should. When that pressure builds, the instinct is usually to publish more, move faster, add another platform, or introduce another tool into the workflow. But scaling output does not fix systems that were never designed to scale in the first place.

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Structure is becoming something much bigger

Before we get into what “Create with Structure” looks like in practice in the COSE™ framework, I think it’s important to pause on why this matters beyond formatting or workflow optimization. A lot of creators and teams are trying to improve outputs without realizing the environment around content has fundamentally changed. If we skip that part, structure can start sounding like just another publishing tactic instead of what it’s increasingly becoming: operational infrastructure for modern content systems.

This is why I keep coming back to structure, even though I think the conversation around it is starting to outgrow SEO and formatting entirely. Structure is increasingly about helping people, systems, and platforms interpret the same information consistently as content moves across different environments. Without that understanding, every platform, team member, and workflow has to reconnect meaning manually every single time content changes. That hidden coordination work is becoming one of the biggest sources of friction in modern content operations.

I also think this explains why so many content professionals feel exhausted right now, even when they’re incredibly good at what they do. A lot of people entered content work expecting to focus on storytelling, publishing, creative campaigns, or audience growth. Instead, many now find themselves navigating workflows, governance decisions, platform limitations, AI tools, and cross-functional coordination challenges they were never really trained to manage. The work evolved faster than the language around it did.

The role itself is changing

There’s a strange identity shift happening across content work right now that I don’t think we talk about enough. Teams are still using old titles and old expectations to describe work that has become much more operational and systems-oriented underneath the surface. Creators are expected to think strategically, strategists are expected to understand platforms and workflows, and content teams are increasingly managing infrastructure whether they realize it or not. A lot of people are carrying systems-level responsibility inside roles that were originally built around publishing.

The creators and teams that stand out right now are the ones building systems where content can stay understandable, adaptable, and reusable as platforms continue changing around them. They understand that visibility is no longer just about publishing constantly but making sure content can move clearly between systems, audiences, and environments without losing meaning along the way.

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The future may belong to translators

I keep thinking that the future of content work may belong to translators more than specialists. Not translators in the language sense, but people who can connect creative thinking, operational systems, platforms, and human understanding in ways that reduce friction instead of adding more of it. The teams that adapt well will probably be the ones capable of building shared understanding across departments, workflows, and technologies without creating confusion every time something changes. That kind of clarity is becoming increasingly valuable.

Content is no longer operating inside one format, one channel, or one destination. The systems surrounding content now shape how it gets interpreted, distributed, reused, and surfaced long before audiences ever engage with it directly. The people who thrive in this environment will not simply be the fastest publishers. They’ll be the people who understand how content, systems, platforms, and communication all connect beneath the surface.

Join the early reader group for Create Once, Share Everywhere™

One of the hardest parts of writing this book has been making sure the ideas connect clearly across creators, teams, workflows, and systems without making the conversation feel overly technical. I want the book to feel useful for people actively navigating modern content work, not just theoretically interesting. That’s why I’m opening up an early reader group before the manuscript is finalized.

If you join the group, you’ll get early access to the manuscript before publication along with a short feedback survey. I’m not looking for polished reviews or praise. I want honest reactions about what feels helpful, what feels unclear, and what ideas genuinely shift the way you think about content systems and workflows. The goal is to make sure the book actually helps people navigate the complexity modern content work now requires. Sign up here.

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Paid subscriptions are coming June 1

Starting June 1, Blueberri Pi will introduce a paid subscription tier for readers who want to go deeper into the operational, strategic, and systems-thinking side of modern content work. The free edition will continue, but paid subscribers will get additional essays, behind-the-scenes framework breakdowns, practical system maps, workflow analyses, and deeper dives into frameworks that relate to structured content. I also plan to share more of the thinking, observations, and industry patterns that don’t always fit cleanly into the public Friday editions.

Paid subscriptions will launch at $8/month or $80/year. Founding subscribers will also receive early access to selected book materials, future workshops, and subscriber-only discussions around content systems, operational clarity, and the future of content work. If Blueberri Pi has helped you think differently about content, platforms, workflows, or visibility, upgrading will help support the research, writing, and long-form work I’m building this publication around.

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If we haven’t met, I’m Sandie.

Blueberri Pi is a systems-aware publication about content, platforms, operational clarity, and the people navigating the future of content work.

See you next Friday.

We’re moving from a world where visibility depended almost entirely on search, to one where systems now sit between you and your audience. People aren’t just searching anymore, they’re asking. And those systems are responsible for finding, interpreting, and delivering content in response.

This isn’t theoretical. AI tools are quickly becoming the starting point for discovery, not just an alternative to search. Instead of typing keywords into Google, users are asking full questions and expecting complete answers.

This week, I want to slow that down and make something clearer. Your content isn’t being understood.

Meet Leah

Leah’s based in San Antonio, filming out of her teal kitchen, the kind that feels warm even before the oven’s on. She didn’t think there was any problem with her content. Her recipes are solid. Her videos are clean. She’s consistent. Thoughtful. The kind of creator people should find.

This week, she’s filming a pistachio chocolate cake. Ring light on. Phone angled down.

Check. Check.

She’s smiling as she sprinkles crushed pistachios over the top, catching that perfect final shot she knows will land on Instagram. She’s done this hundreds of times. She’s what I call a High Output Creator.

But still, later that night, she’s staring at her numbers thinking, Why isn’t this working? That’s where you saw her last week. From the outside, everything looks right, but under the surface, her content is doing what most content does.

It’s being created to be watched…
not to be understood.

Her ingredients are in a paragraph.
Her steps live inside a story.
Her metadata is inconsistent.

To a person, it feels natural, but to a system, it’s unclear. And right now, systems are the ones deciding what gets seen.

Why “not understood” changes everything

The systems now shaping discovery don’t interpret content the way people do.

They don’t read context, infer meaning, or connect ideas across paragraphs. They rely on structure to make sense of what’s in front of them.

And we’re already seeing the effects of this. As more queries are answered directly by AI systems, click-through rates are declining. In some cases, content is being used without ever being visited.

When that structure isn’t there, things start to break down.

Ingredients get buried in paragraphs instead of being clearly defined. Steps are written as narratives instead of distinct actions. Important context is implied rather than explicitly labeled. Metadata is inconsistent or missing entirely.

To a human reader, this often feels natural, even engaging. To a system, it creates friction.

And that friction makes content harder to surface, harder to adapt, and harder to reuse across the environments where discovery is increasingly happening.

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Why more content isn’t fixing it

One of the most consistent patterns I see is how many creators are caught in a loop of producing more, posting more, without seeing the results they expect. There’s almost a fear of stopping. Even for a day. When performance dips, the instinct is to increase output.

But more content doesn’t fix a structure problem. It just scales the inefficiency behind it. That’s why this doesn’t feel like a structure issue. It feels like a visibility issue, or a platform issue, or even a quality issue. But underneath all of that, content is being created for people, but not for the systems now responsible for distributing it.

Where COSE™ actually starts

Last week, I introduced COSE™ as a framework: Create Once, Share Everywhere. But the shift doesn’t start with sharing. It starts with how content is built.

Structure isn’t something you layer on later. It’s the foundation that determines whether your content can move, adapt, and extend beyond a single format or platform.

And that matters even more now, as platforms begin to turn content into action. Tools like ChatGPT and Claude are already integrating with services like Instacart, allowing users to go from recipe discovery to grocery checkout in a single flow.

​​Without structure, your content can’t participate in that flow.

Without it, everything stays fixed in place. With it, your content becomes something that can be understood, reused, and distributed in ways that weren’t possible before.

A simple way to think about the difference is that most content is created in a linear flow—write, format, publish. Structured content takes a different approach—define, organize, then express.

What to look at this week

Take one piece of your content and look at it through this lens.

• Are the ingredients clearly defined?

• Are the steps separated and structured?

• Is key information labeled, or embedded in paragraphs?

• Could a system interpret this without guessing?

Those questions will tell you more than any metric right now.

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The book is coming together (and you can be part of it)

My favorite part of writing this book is also the hardest. Stepping back and making sure the ideas actually make sense, build in the right order, and are genuinely useful.

The next step is sharing the manuscript with an early reader group. If you join, you’ll get exclusive access to the manuscript before it’s published.

Quick SPOILER: It will have typos. It will have grammar issues.

That’s intentional. This isn’t about a perfect draft. It’s about making sure the ideas land.

Here’s where I need your help:

• You’ll have about two weeks to read it

• You’ll answer 10–15 questions afterward

And I’m not looking for praise.

I want to know:

• Is this helpful?

• Does it make sense?

• Does it actually move you forward as a creator?

If that sounds like something you’d want to be part of, you can sign up here.

In the next issue, I’ll break this down further and walk through what “Create with Structure” actually looks like in practice and how to start applying it without rebuilding everything from scratch.

We will focus on making sure what you already create works better.

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If we haven’t met, I’m Sandie.

Blueberri Pi is where I break down how food creators and content teams can make their work more structured, more discoverable, and more sustainable.

See you next Friday.

Not because nothing was happening—but because a lot was.

April pulled me out of writing mode and into rooms, conversations, and stages where I got to hear, in real time, what creators and content teams are actually dealing with right now.

I spoke at ConVex in Pittsburgh, led an Instacart Developer Masterclass, presented at Growing in Content, and went live on Substack with Yvette Marquez-Sharpnack, award-winning Mexican-American cookbook author, founder of Muy Bueno, and author of Cocina to Career. (Subscribe if you haven’t already!)

Even though they were different audiences and different formats, the same conversations kept coming up.

Creators are working harder than ever.
And still asking: why isn’t this working?

That’s the part I can’t ignore, because at the same time all of this is happening… the ground is shifting under the way content gets discovered.

A quick reality check

Instacart is now available inside Claude.

And it’s been integrated into ChatGPT since December. Which means something pretty simple, but easy to underestimate:

Home cooks aren’t just searching anymore. They’re asking.

They’re asking tools to:

• Find recipes

• Adapt recipes

• Build grocery lists

• Walk them through cooking

And those tools are pulling from structured, machine-readable content to do it.

So now your recipe doesn’t just need to rank on Google.

It needs to be understood by systems that:

• Don’t “see” your blog the way a human does

• Don’t scroll

• Don’t guess

They rely on structure.

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Why this matters (more than you think)

If your content isn’t clearly structured:

• Ingredients get missed

• Steps get flattened

• Context gets lost

And your recipe becomes harder to surface, adapt, or recommend because it’s not legible to the systems now shaping discovery.

This is what I kept hearing and speaking about, over and over again in April, just from different angles.

Creators are talking about traffic drops and inconsistent RPMs from ad revenue. Teams are talking about distribution challenges. Platforms are talking about integrations, but the same underlying issue persists.

Content is being created for people…
but not for the systems that now sit between you and your audience.

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This is where COSE™ comes in

If you’re new here, a quick orientation.

COSE™ stands for Create Once, Share Everywhere.
But more importantly, it’s a framework—not a tactic.

It’s a way to think about your content as something that:

• Starts with structure

• Can be reused without starting over

• Works across platforms (not just your blog)

• And actually connects to revenue

Most creators are stuck in a loop of:
create → publish → repeat

COSE™ breaks that loop.

It helps you:

• Make your content easier to understand (by both people and platforms)

• Easier to reuse (without rewriting everything)

• Easier to distribute across places like search, apps, and now AI-driven tools

Because the goal isn’t to create more content.

It’s to make the content you already create go further.

If you want a deeper breakdown, start with this guide to the COSE™ framework.

Over the next few issues, I’ll walk through how this actually works in practice. I want to give creators a better way to make their existing ideas work in more places.

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A quick update on the book

As you know, the first draft of Create Once, Share Everywhere™ was done last fall.

Since then, I’ve been heads down in developmental editing, which is less about fixing grammar and more about strengthening the thinking behind the book.

It’s where I step back and ask:

• Does this actually make sense for the reader?

• Are the ideas building in the right order?

• Am I explaining this in a way that’s clear, not just correct?

It’s slower work, but it’s the part that turns a draft into something genuinely useful.

The manuscript is coming together, and I’m planning to send it to an early reader group in early summer. This part matters to me. I don’t wanna just get feedback; I wanna make sure what I’m building actually reflects what creators need right now, not what I think they need.

Over the next few weeks, I’ll be reaching out to creators who want to be part of that early reader group. If that’s you, keep an eye out.

Don’t call it a comeback. I’ve been here for years, and I’m just getting started.

If we haven’t met, I’m Sandie. Blueberri Pi is where I break down how food creators and content teams can make their work more structured, more discoverable, and more sustainable.

See you next Friday.