Your Content Isn't an Ad. It's a Product.

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After tens of thousands of hours driving growth for brands like Ramp, Lovable, and Metronome, we realized creating content has changed from writing copy to building products.

We've watched marketing teams make the same mistake over and over. They publish more, hire more, buy more tools, and somehow end up with less to show for it.

When we dig into what's happening, the pattern is almost always the same. They're treating content like an ad. Create it once, launch it, forget it. But content should work more like a product.

It should have features, users, outcomes, and value delivery. It should be an extension of your actual product and business.

When you get it right, creating growth stops feeling like a bottomless bucket you dump money into and more like a flywheel.

This post breaks down what that shift actually looks like, how we think about it at GrowthX, what it looks like in practice, and how you can start applying it to your own work this week.

At GrowthX, we've worked with more than 50 brands and talked to hundreds of CMOs. The story is remarkably consistent.

It usually starts with a premium agency. The work is beautiful, the strategy is sound, but the output is slow.

Next comes the growth agency. They promise 10x output. And they deliver, sort of. Thin content, no original thinking, very clearly AI-generated.

Then you try the tools. But if you don’t know how to use them, the output feels generic.

Finally, you build a freelancer network. Your content manager spends 20 hours a week just managing the chaos.

Every one of these approaches fails for the same reason. They all treat content as a one-shot. A project with a deadline that you launch and forget.

The teams that win look different. They treat every piece of content like a product. Something that gets maintained, iterated, and improved over time. Something someone actually owns.

This matters especially for extensible products. Tools like Webflow, Airbyte, or ChatGPT are incredibly powerful, but users constantly get stuck on implementation.

Broad, flexible use cases create decision paralysis. Users don't know what they don't know. They don't have the time or patience to figure it out themselves.

The solution is content that gives users ideas. Catalogs of use cases. Guides that show exactly how to implement. Integration guides are particularly popular because they show how your tool works with systems users have already invested in.

Say you're building a developer tool and you need integration pages. Guides that show how your product works with Salesforce, HubSpot, Slack, and a hundred other tools your users already have.

The traditional approach: You hire a technical writer. They research the Salesforce integration, write the guide, publish it. Then they move to HubSpot. One page at a time, maybe two or three a week if they're fast. At that pace, covering your full integration landscape takes months. And by the time you finish, the early pages are already outdated because Salesforce shipped a new API version.

The product approach: You build a system. That system ingests your product documentation and understands what your tool actually does. It processes Salesforce's docs, HubSpot's docs, Slack's docs, learning how each platform works. It pulls from your support tickets and sales calls to understand which integrations users actually care about and where they get stuck.

Now when you need a Salesforce integration page, you're not starting from scratch. The system already has context. A human still owns the quality bar, still decides what "good" looks like, still makes sure the page actually helps users.

Say you notice your integration pages aren't ranking well because they lack real-world examples. In the traditional model, you'd rewrite every page. In the product model, you upgrade the system. You add a step that pulls in Reddit discussions about each integration, filtered by upvotes so you're only getting the good stuff. Now every page you publish, past and future, benefits from that upgrade.

We recorded a walkthrough of this process. It's the messy, real version of how we build using AI. ChatGPT, Claude, and a systematic approach that breaks content creation into manageable pieces.

If you're trying to create technical content at scale, you need workflows, not just prompts. This video shows you how to build them.

Carrie Chowske is a Senior Managing Editor at GrowthX. She's been working with AI tools for content production longer than most, and she's developed a workflow that captures what product thinking looks like in practice.

Recently, she needed to migrate a Claude project to a new account for a client. The problem was that all the context she'd built up over months of working with Claude would be lost in the migration. The patterns it had learned, the mistakes it knew to avoid, the voice it had internalized.

Instead of starting from scratch, she asked Claude to write an onboarding guide for itself. As if it knew nothing about the client. As if it were a new hire.

She prompted:

"What are some of the most common mistakes I ask you to correct?"
"What would you need to know in order to help me write and edit content?"
"Based on our previous interactions, compile an editing checklist that looks for the most common writing errors I ask you to fix."

The result was a self-generated artifact. A document that captured everything Claude had learned from their working relationship, distilled into something she could carry forward.

Carrie was treating Claude like a junior writer she'd been training for months. And when it was time to move on, she asked that junior writer to document everything they'd learned.

She uses a similar approach for building voice guidelines. Instead of trying to describe a client's voice in the abstract, which never works, she gives Claude two versions of the same piece of content. The rough draft and the polished final.

"Doc A is my draft. Doc B is my final version. Create writing guidelines based on the changes between the two."

Claude analyzes the differences. What got cut, what got added, what got rewritten and why. The output is a style guide grounded in real examples, not abstract descriptions.

As Carrie put it when we talked about this: "Once you unlock how to prompt it, what to give it, what it can do, AI becomes a thought partner, not just a tool."

That's the product mindset in action. The artifact learns from every interaction. It improves over time. And someone owns it. Someone who's actively making it better.

→ Want the exact prompt templates we use to build our context artifacts? We’re sharing inside the AI-Led Growth community. Become a member today.

Inside the AI-Led Growth community, we're sharing the prompts our team uses to build and refine context artifacts.

If you want to see how this works in practice, join us there.

That's it for this week.
If this was useful, forward it to someone who needs it.

Marcel & Jason

PS There’s still time to join our free workshop with Lovable on December 9th! When you register, you’ll also get access to the replay! Attendees will receive a special surprise offer!