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Reviewing AI Output Before It Ships

Reviewing AI Output Before It Ships

Armbrain and Claude draft things. Your job is quality control before it reaches the client. The CMO trusts that anything you approve is ready to send.


Why This Role Exists

AI is fast. It can draft an email in seconds, pull together a meeting brief in under a minute, and generate a campaign summary before your coffee gets cold. But speed without judgment is dangerous.

AI makes confident-sounding mistakes. It references meetings that didn't happen. It drifts away from a client's brand voice over time. It fills gaps in its knowledge with plausible-sounding filler. Your job is to catch all of that before anyone outside the team sees it.


Common AI Mistakes to Watch For

MistakeWhat It Looks LikeHow to Catch It
Made-up details"As we discussed in last Tuesday's call..." (there was no call)Cross-check dates against the calendar
Wrong toneToo formal for a casual client, too casual for a corporate oneRead it out loud - does it sound like your CMO talking to this person?
Generic filler"We're excited to leverage synergies to drive results"If it sounds like it could be about any client, it's filler
Outdated infoReferences an old campaign, a former team member, or last quarter's numbersCheck against recent meeting notes and Armbrain
Hallucinated metrics"Your traffic increased 23% last month" (it didn't)Verify any specific numbers against actual data
Name confusionUsing the wrong stakeholder name or mixing up client detailsConfirm names and roles against the client mind

The "Would the CMO Actually Say This?" Test

Before approving anything, read it through this filter: if your CMO walked into a room and said these exact words to this client, would it sound natural?

If the answer is no, something needs to change. Common failures:

You know your CMO's voice because you hear it every day. Trust that knowledge.


Brand Voice Drift

This is subtle and dangerous. When AI writes for a client over weeks and months, it slowly drifts away from the client's actual brand voice. It starts sounding more like "generic marketing AI" and less like the client.

Watch for:

When you notice drift, pull the brand voice to compare:

"Switch to Acme Corp"
"Show me Acme's brand voice"
Pulling up a client's brand voice to check AI output against it
Pulling up a client's brand voice to check AI output against it

Compare the stored voice guidelines against what the AI just produced. If they don't match, flag it. Over time, you'll develop an instinct for each client's voice and catch drift before it compounds.


What to Check in Each Type of Output

Email drafts:

Meeting briefs:

Client reports:

Content drafts:


When to Fix It Yourself vs. Flag It

Fix it yourself:

Flag for the CMO:

Verifying a factual claim in AI-generated content
Verifying a factual claim in AI-generated content

When you flag something, be specific: "The draft references a pricing discussion from March 15 but I don't see that on the calendar. Did this happen in a call I don't have notes for, or did the AI make it up?"


Building the Trust Loop

The goal is a simple workflow: AI drafts, you review, CMO sends. Over time, the CMO should be able to trust that if something made it past you, it's ready. That trust is earned by catching things early and being honest when you're not sure.

Store patterns you notice so the system improves:

"Quick note: AI keeps using 'leverage' in Acme drafts. Sarah has said twice she hates that word. Flag for brand voice update."

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