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How to scale messaging without losing control

It’s a question I get a lot, and a problem I see all the time.

Usually the reason is twofold:

1. Marketing, Product, and Sales keep passing the ball on who owns messaging.
2. They struggle to manage it across the entire customer journey.

It’s like a highway where alignment depends on everyone knowing their lane. Except no one knows where their entry or exit is — and someone’s always stuck circling the roundabout, flashing their lights.

So how do you make sure your teams can move from start to finish (and back into the loop) without crashing into each other?

Let’s get into it.

Step 1: Understand the motion you’re in

There are two main growth motions: Product-Led (PLG) and Sales-Led (SLG).

For a growth-stage SaaS, the difference is huge:

In a PLG motion, your product is the message.Marketing and Sales put into words what users experience, then feed it back into the machine.

In a SLG motion, your message is the product.Marketing and Sales craft the narrative that sets up the experience, and Product uses that to match expectations and optimize.

When you’re running both at once — a hybrid GTM model — it’s easy to lose the thread. Messaging gets diluted, slack threads multiply, and you end up with random custom GPT slop.

But the real reason messaging breaks isn’t crap AI output, scale, or motion.

It’s missing foundations.

We’re literally looking at the wrong problem (copy), when we should be asking ourselves how we came up with it in the first place.

Step 2: Build the foundation before you build speed

By foundations, I mean a clear, agreed-on positioning strategy and a validated messaging framework.

Without those, teams don’t have a shared, repeatable way to explain what they do, who they do it for, and how they do it differently, better, or uniquely. So when messaging passes between departments, as it should, it gets lost in translation.

When the foundation is strong on the other hand, everyone knows:

• What story they’re telling
• Where that story fits in the customer journey
• How to measure if it’s landing
• How to fix the output copy

That’s when messaging starts becoming a flywheel.

Step 3: Diagnose, don’t guess

When your foundation is in place, you can finally diagnose problems instead of guessing at symptoms.

Here’s how it looks across teams:

Once the system is in place, you can really scale your messaging, because you have a clear way to monitor it at every touch point.

Step 4: Keep everyone on the same road

As companies grow, messaging gets harder to control. New hires join, priorities shift, new competitors pop up, teams launch faster than they can sync.

But if your positioning and messaging systems are strong, you’ll always have a map to follow.

When everything ties back to a shared foundation, every touchpoint, from ad to demo to onboarding, sounds like it comes from the same brain. And when something breaks, you can trace the line back to the source and fix it fast.

That’s how you get fewer roundabouts, more clarity, and messaging that compounds.

TL;DR Messaging breaks when teams scale faster than their shared understanding. Fix the foundation — positioning + framework — and you fix everything downstream.

DISCOVERY

Here's why you're getting AI slop

As long as teams keep using ChatGPT to *write* before they *think*, I’m not worried about my job.
​
OpenAI’s usage data shows “Asking” beats “Doing” across most work tasks, except writing. That’s where people still go straight to “do it for me.”

Almost no one stops to ASK:
​
- What’s the idea here?
- Who’s this for?
- Why should anyone care?
- What am I missing?
- What is the AI missing?
- How can I fill in the gaps?
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That’s why most AI copy is crap.
​
Don’t ask it to write. Or at least not right out of the gate. And NEVER without the right context.
​
Ask it to help you think bigger, to find contradictions, to test messages, and to push back on your reasoning.

Why experts become stupid

I’ve been thinking about the gap between “translators” and “practitioners,” and why I try to sit in the middle, doing the work, then teaching the thinking. Convenience (of AI for example) pulls us toward the shallow end. Craft pulls us back.

I've enjoyed this article that nails it. Give it a read, then tell me what you think. Are you translating, practicing, or holding the line between both?

The answer is an important one, because it dictates your stance on whatever you produce.

RESONANCE

Confucius, The Analects

Have a great weekend!

Cheers,

Chris

Chris Silvestri Founder & conversion alchemist

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