Your team ran ChatGPT. The draft came back in 90 seconds.
Then someone had to spend 3 hours rewriting it because it read like a press release from 2003.
AI was supposed to save time. Instead, it created a new job: fixing robot garbage before anyone sees it.
Our team tested 47 content frameworks over six months. We tracked hours saved, edits required, and whether the output actually shipped. Most frameworks failed. Five passed.
These five quality standards solve the delegation problem. They let you hand work to AI without becoming the rewrite department.
How We Tested
We gave the same brief to five team members using different quality frameworks. Each brief had a specific output requirement: blog post, LinkedIn post, email sequence, ad copy, or sales page.
We measured:
Time to first draft
Edits required before shipping
Whether it passed brand voice review
Whether it actually got published (or died in revisions)
The frameworks that passed all four checks made this list.
What Made These Five Different
Most quality frameworks focus on detecting AI slop after it's written. These five prevent it during creation.
They give you criteria you can hand to your team before they write. That means fewer rewrites, faster shipping, and content that sounds like your brand instead of every other company using the same prompt.
What you're about to get:
All 5 quality standards with implementation checklists
When to use each one (and when to skip)
Real output examples showing before/after
Specific prompts that enforce each standard
We tested 47 frameworks. These 5 let you delegate without becoming the rewrite department.
Let’s go…
All prompts and checklists are available as downloads at the end of this article
1. The Human Review Mandate
What It Is: Every AI output requires a human editor who checks for three things: factual accuracy, brand voice alignment, and whether a real person would actually say this.
Why It Made the List: This is the baseline that separates usable content from liability. Publishers like Elsevier, Taylor & Francis, and Nature all mandate human review for AI-assisted content. The reason? AI hallucinates citations, invents statistics, and produces legally risky claims.
Best Use Case: Use this standard for anything published externally—blog posts, ads, social media, email campaigns. Skip it for internal brainstorming or rough outlines.
Pros:
Catches factual errors before they ship
Prevents brand voice drift
Creates accountability (someone owns the output)
Cons:
Requires editorial capacity (you need someone who knows your brand)
Slows down speed-to-publish if not systematized
How to Use It: Create a three-question checklist your editor runs on every AI draft:
Did I verify every claim with a primary source?
Would our CEO say this sentence out loud?
Does this solve a specific reader problem?
If any answer is "no," it goes back to the writer.
Before/After Example:
Before (AI output): "Our innovative platform leverages cutting-edge technology to facilitate seamless integration across multiple touchpoints, enabling organizations to optimize their workflow efficiency."
After (Human review applied): "Connect your email, calendar, and CRM. One login. No switching between tabs."
The human editor caught: vague claims ("innovative," "cutting-edge"), no specific benefit, and corporate-speak nobody says out loud.
Prompt That Enforces This Standard:
Write [content type] about [topic].
Before you write, answer these three questions:
1. What specific claim am I making that needs verification?
2. Would a real person say this sentence out loud at a coffee shop?
3. What problem does this solve for [target audience]?
Now write the content. After writing, verify every claim with a source.2. The E-E-A-T Framework
What It Is: Google's quality standard for content: Experience, Expertise, Authoritativeness, Trustworthiness. If AI wrote it without adding real human insight, it fails.
Why It Made the List: Google's 2025 algorithm update explicitly deprioritized AI content that lacks human expertise. Content that passes E-E-A-T ranks. Content that fails disappears.
Best Use Case: Use this for SEO-focused content, thought leadership, or anything in competitive search categories. Skip it for transactional emails or one-off social posts.
Pros:
Protects organic search rankings
Forces addition of unique insights (makes content defensible)
Creates differentiation from competitors using the same AI tools
Cons:
Requires subject matter expertise (can't outsource to junior writers)
Takes longer to produce than generic AI output
How to Use It: Before publishing, add one of these human-only elements:
A personal anecdote from someone on your team
A case study with real numbers from a real client
An original opinion on an industry debate
A data point you researched yourself
If the piece doesn't have at least one, it won't rank.
Before/After Example:
Before (AI generic output): "Email marketing remains an effective strategy for businesses. Studies show that email has a strong ROI and can drive customer engagement."
After (E-E-A-T applied): "We tested 12 email sequences last quarter. The one that opened with a customer success story (not a product pitch) had 3x higher reply rates. Here's why it worked..."
The human added: specific test (12 sequences), timeframe (last quarter), real metric (3x higher), and promised an explanation from actual experience.
Prompt That Enforces This Standard:
Write [content type] about [topic].
Before writing, include ONE of these human expertise elements:
- A case study: "We tested [X] and found [specific result]"
- A personal story: "When I [action], here's what happened..."
- An original take: "Most people think [X], but after [experience], I believe [Y]"
- First-party data: "Our analysis of [sample] showed [specific finding]"
Write the content with this element in the first 200 words.
3. The Voice Detection Layer
What It Is: A checklist that flags AI writing patterns: metronome pacing, banned words (delve, tapestry, realm), over-hedging, and meta commentary.
Why It Made the List: AI has telltale patterns that make content feel generic. This framework catches them before readers do. We built ours by analyzing 200+ pieces of AI slop and isolating the markers that always appear.
Best Use Case: Use this on any customer-facing content. Skip it for internal documentation or draft stage work.
Pros:
Catches "AI voice" that human editors miss
Prevents brand voice erosion over time
Takes 2 minutes to run per piece
Cons:
Requires initial setup (building your banned words list)
Can flag false positives if your human writers use similar patterns
How to Use It: Run this three-step check on every draft:
Search for banned words (delve, leverage, utilize, facilitate, robust). If found, delete and rewrite.
Read three random sentences out loud. If they're all the same length, vary the rhythm.
Look for meta commentary ("In this section, we will discuss..."). If found, delete and just say the thing.
Your goal: zero AI patterns in final output.
Before/After Example:
Before (AI patterns): "In today's competitive landscape, businesses must leverage innovative solutions to facilitate growth. This comprehensive approach enables organizations to optimize their operations and achieve their objectives."
After (Voice Detection applied): "Your competitors are moving faster. You need to move faster too. Here's how."
The check caught: "today's competitive landscape" (cliché), "leverage" (banned word), "facilitate" (banned word), "comprehensive" (AI filler), and metronome pacing (all sentences similar length).
Prompt That Enforces This Standard:
Write [content type] about [topic].
Rules:
1. NEVER use these words: delve, leverage, utilize, facilitate, robust, comprehensive, innovative, solutions, landscape, ecosystem
2. Vary sentence length. Mix short sentences (under 10 words) with longer ones (20+ words)
3. No meta commentary. Don't announce what you're about to say. Just say it.
4. Read it out loud. If it sounds like a press release, rewrite it.
Write conversationally. Pretend you're explaining this to a colleague over coffee.4. The Source Attribution Protocol
What It Is: A requirement that every claim AI generates must link back to a verifiable primary source. No source = delete the claim.
Why It Made the List: AI invents citations. It generates plausible-sounding statistics that don't exist. This protocol forces verification before publishing, which protects you from reputational and legal risk.
Best Use Case: Use this for anything with data, research, or expert claims. Skip it for opinion pieces or personal narratives.
Pros:
Eliminates hallucinated statistics
Builds credibility (readers trust sourced claims)
Protects against plagiarism accusations
Cons:
Time-intensive (someone has to verify every claim)
Can slow down production if not systematized
How to Use It: Before publishing, run this verification process:
Highlight every statistic, research finding, or expert quote
Google each one to find the original source
Replace any claim you can't verify with either: (a) a claim you can source, or (b) your own opinion
If you can't find a source in 5 minutes, the claim is probably fake. Delete it.
Before/After Example:
Before (AI hallucination): "According to recent studies, 73% of marketing teams report increased productivity when using AI tools. Research shows that companies save an average of 15 hours per week."
After (Source Attribution applied): "According to Salesforce's 2024 State of Marketing report, 51% of marketers use AI for content creation. Our team tracked our time for 8 weeks and saved 12 hours weekly on blog production."
The verification caught: The "73%" stat doesn't exist. The "15 hours" figure is fabricated. The editor replaced them with a real stat from Salesforce (verifiable) and first-party data from their own tracking (accountable).
Prompt That Enforces This Standard:
Write [content type] about [topic].
For every claim, statistic, or research finding:
1. Name the source (publication, organization, or researcher)
2. Include the year
3. Provide enough detail that I can verify it
Format: "According to [Source] ([Year]), [specific finding]."
If you don't have a verifiable source, either:
- Find one, or
- Replace it with my opinion (clearly labeled as opinion, not fact)
Write the content. I will verify every source before publishing.5. The Brand Voice Overlay
What It Is: A two-part system: (1) a voice DNA document that defines your brand's sentence structure, rhythm, and forbidden patterns, and (2) a post-production pass where you rewrite AI output to match your voice.
Why It Made the List: AI defaults to corporate-speak. This framework lets you use AI for structure and speed, then overlay your actual voice before publishing. It's the difference between "leverage solutions" and "fix the problem."
Best Use Case: Use this for high-visibility content: homepage copy, sales pages, key blog posts, ads. Skip it for FAQ pages or support documentation.
Pros:
Lets you use AI without sounding like AI
Creates consistency across your content library
Scales voice even as team grows
Cons:
Requires upfront work (building the voice DNA document)
Needs someone who can actually write in your brand voice
How to Use It:
Create your voice DNA doc: Pick 3-5 pieces of content that sound like your brand. Analyze sentence length, word choice, rhythm. Document patterns.
After AI generates a draft, rewrite the first paragraph in your voice.
Compare the AI version to your version. Identify what changed.
Apply those changes to the rest of the piece.
Your goal: readers can't tell which parts were AI-generated.
Before/After Example:
Before (AI generic): "Our platform offers comprehensive solutions for modern businesses seeking to optimize their digital marketing efforts. With advanced features and intuitive design, we enable teams to achieve their goals efficiently."
After (Brand Voice Overlay—e.g., casual, direct brand): "We built this for teams who don't have time to figure out another complicated tool. Login. Connect your accounts. Start running campaigns. That's it."
The overlay caught: corporate vocabulary ("comprehensive solutions," "optimize," "enable"), vague benefits ("achieve goals"), and formal structure. The brand voice prioritizes: short sentences, second-person address, concrete actions, and zero jargon.
Prompt That Enforces This Standard:
Write [content type] about [topic].
Match this brand voice:
- Sentence length: [e.g., "Mix of 5-15 words, with occasional fragments"]
- Tone: [e.g., "Direct, helpful colleague—not corporate"]
- Forbidden words: [Your banned words list]
- Point of view: [e.g., "Second person 'you,' first person plural 'we'"]
- Rhythm: [e.g., "Vary. Short punch. Then longer explanation."]
Example of our voice: "[Paste 2-3 sentences from your best content]"
Write in THIS voice, not generic corporate voice.Quick Reference: When to Use Which Standard
If You're Writing... | Use This Standard |
|---|---|
Blog post for SEO | E-E-A-T Framework + Source Attribution |
LinkedIn post | Voice Detection Layer + Brand Voice Overlay |
Email campaign | Human Review Mandate + Voice Detection |
Sales page | All five (high stakes = max quality control) |
Internal doc | Just Human Review Mandate (speed matters more) |
The pattern: external content gets more layers. Internal content gets speed.
Where This Leads
These standards aren't about blocking AI. They're about using it without the 3-hour rewrite tax.
Most teams treat AI output as final. That's the mistake. AI is a first draft. These five standards are what turn that draft into something you can actually publish.
The teams winning with AI aren't using better prompts. They're using better quality control.
My Take
We spent six months testing frameworks because we kept publishing content that sounded like everyone else. The problem wasn't the AI. It was that we didn't have criteria for "good enough to ship."
These five standards gave us that criteria.
Now our junior team members can run AI, apply the checklist, and ship content that sounds like our brand. We save time. They learn faster. And we don't sound like robots.
A or B:
A) If you're already using quality standards, which one catches the most problems?
B) If you're not using quality standards yet, which of these five would solve your biggest rewrite problem?
Download the Resources
Want these standards in checklist format?
📥 Download: Quality Standards Checklist
Print this and keep it visible during content review. Includes all 5 standards with quick-check questions.
📥 Download: Quality Standards Prompt Library
Copy-paste prompts that enforce each standard during content creation. Includes combo prompts for maximum quality control.
Both resources are free and in markdown or text for ease of use on all systems. Use them to train your team, onboard new writers, or systemize your quality control.
by DO
for the AdAI Ed. Team
