Every AI workflow needs these 4 artifacts

Since we launched the community, we get questions all the time about why AI seems to get dumber with every message. It’s not just you! The only way we’ve been able to scale to thousands of articles for brands like Webflow, Ramp, and Lovable is through the artifact system we share in this week’s post.

This is a start to any AI growth engine. If you want the full course on how to build your own content system, we share everything in our course on “Win AI Search With Content Quality”

The longer you talk to ChatGPT, the worse it gets. You've felt this, and no matter how many of these you type:

"Pretend you are an SEO expert with 4 years of experience…"

"Act as a world-class copywriter who specializes in B2B SaaS…"

"You are a marketing strategist with deep knowledge of…"

…it doesn't feel like anything is getting better.

Here's what actually happens: context rot, or context drift.

Every message you send to ChatGPT or Claude pushes your original instructions further out of its working memory. 

Chroma's research found that model performance degrades by 17-35% after just 10 turns as critical instructions get pushed out. That's why your twentieth draft sounds nothing like your first, even when you're using the exact same prompt. 

Your prompt isn't the problem; it's that the model literally forgets what matters and its also why most AI-generated content feels generic, off-brand, or falls into the 'slop' category.

At GrowthX, we work with marketing teams publishing 10X more content than their competitors. The difference isn't better prompts; it's accurate, detailed, and persistent context artifacts.

Think of artifacts as living documents that don't get lost in conversation history. They stay consistent. They're version-controlled. They can be pulled into any workflow, any prompt, any time.

(nice, right?)

Instead of dumping everything into a chat and hoping the AI remembers, you build reusable context once, then reference it forever. Or as long as it's relevant and useful to you.

Here's why this matters: if you dumped your brand voice guide into a regular chat, the model would forget it by message 12.

But as an artifact? It's always there, pulling your content back to your actual voice.

The same goes for company positioning, audience research, and customer language. This is the context that separates strategic content from AI nonsense.

This anchors your content in fact. It prevents hallucinations about what your product does, who you serve, and how you're positioned.

Without it: The AI invents features, misrepresents your value prop, or writes generic "solutions" that could apply to any company.

Or worse, invents features you don't actually offer.

With it: Every piece of content references accurate product details, speaks to your actual differentiation, and aligns with your go-to-market strategy.

Example use case: Writing integration pages. If your company positioning changes—say, you shift from "design platform" to "development platform"—you update one artifact and regenerate 300 pages. Without artifacts, you're manually rewriting everything.

This is your "Voice Systems Architect." It defines style, sentence patterns, words to use and avoid.

Without it: The AI defaults to corporate-speak or mimics whatever training data it's seen most. Your content sounds like everyone else's. (boring, bland, and brand-less)

With it: Output matches your recognizable tone whether that's blunt and tactical, warm and conversational, or data-driven and analytical.

Example use case: Writing social posts. Pull your tone guide artifact into every post workflow. As your voice evolves, you iterate the artifact. No need to re-explain it in every prompt.

This forces content to tap into the specific context your audience has like their fears, frustrations, the solutions they've already tried and failed.

Without it: Content speaks to "marketing leaders" in vague generalities that don't resonate.

With it: Content feels like a direct conversation with someone who gets their exact situation.

Example use case: Every piece of content at GrowthX references our ICP artifact: VPs of Marketing who are stuck between quality and velocity. That specificity shows up in every blog intro, every case study, every workshop description.

This injects real-world language—the exact words your customers use to describe problems, benefits, and outcomes.

Without it: Content uses your marketing language, not the language buyers actually think in.

With it: Content speaks in the voice of the market. You're not selling. Instead, you're reflecting what customers already believe.

Example use case: Writing landing page copy. Pull direct customer quotes about pain points and transformations. The artifact keeps that authentic voice consistent across every page.

→ Want the exact prompt templates we use to build each of these artifacts? Our Win AI Search course includes step-by-step instructions for creating all four, plus real examples from Webflow, Augment Code, and Ramp.

Let's see this in practice with a simple example: writing an H1 for a landing page.

Good (prompt-only approach): "Write an H1 for our landing page targeting Series B marketing leaders."

Output: "Transform Your Marketing Strategy with AI-Powered Content"

Generic. Could apply to 100 companies.

Better (prompt + artifacts): "Write an H1 for our landing page. Reference the audience persona artifact for pain points and the company profile for positioning."

Output: "Get Series C Content Velocity at Series B Budget Without Sacrificing Quality"

Specific. Speaks to resource constraints and quality concerns simultaneously. Sounds like something a real buyer would care about.

The difference? Context. The artifacts provided the nuance that a simple prompt couldn't capture.

Here are two introductions written using Claude for Ramp, one of our customers.

The prompt: write a detailed, but concise introduction for Ramp. Share what it does, who it benefits, and its main differentiator in no more than 5 sentences.

With the context artifact:

Without the context artifact:

Ramp is an all-in-one finance automation platform that combines corporate cards with spend management software, bill payments, and accounting tools. It benefits employees and businesses of all sizes by automating manual tasks. 

ToV aside, the difference is obvious. The artifact-powered version is specific, differentiated, and actually persuasive.

Here's what this looks like in a real content workflow:

Research phase: Company profile + audience persona artifacts (tone doesn't matter yet; you're gathering facts about your company and their problems)

Outline phase: All four artifacts working together: company positioning, audience pain points, voice patterns, customer language

Drafting phase: Heavy reliance on voice artifact and customer quotes (this is where tone matters most)

Polish phase: Voice artifact ensures every sentence sounds like you

When you build context artifacts instead of perfecting prompts, you stop wrestling with output and start directing a system that delivers consistent, high-quality content.

One more time for the people in the back: Prompts work better once you've built the context.

You wouldn't hire a writer without a brief, a style guide, and a deep understanding of your product. Don't treat AI any differently.

And when you do it right, here’s what that simple sequence of prompts could look like when you really go production grade:

The fastest-growing software company in history is open sourcing their playbook.

Lovable hit $100M ARR in 8 months. Faster than OpenAI. Faster than Cursor. Faster than anyone.

How they did it:

This is the same approach that made them the fastest-growing software company ever.

Now they're revealing EXACTLY how to do it (aka "vibe marketing).

That's it for this week.

If this was useful, forward it to someone who needs it.

Marcel & Jason