AI-Ready CMO
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Part 3: Define Your Brand Voice System

The Problem

AI content sounds like AI. Every post reads like it was written by the same enthusiastic intern who just discovered a thesaurus.

The solution isn't better prompts. It's a systematic voice ruleset that your agent enforces automatically — a validation layer that catches and rejects bad patterns before anything gets published.

Why 90% of AI Content Sounds the Same

Every large language model defaults to the same voice: enthusiastic, generic, packed with corporate jargon.

The Default AI Vocabulary

excitingrevolutionarygroundbreakingdelveunlockleveragegame-changercutting-edgetransformativeparadigmsynergyecosystem

Ask any LLM to write a LinkedIn post and you'll get these words. Every time. The output is technically correct but completely forgettable.

Asking “write naturally” does not work

The AI interprets “natural” as “slightly less corporate.” You still get the same vocabulary with a few contractions thrown in.

Building a RULESET works

A validation layer that literally rejects posts containing forbidden words before they ever get published. Rules are enforceable. Vibes are not.

Jenny's Approach

Every post Jenny generates goes through automated validation. If the text contains a forbidden word, it gets sent back to the LLM with explicit instructions to fix the violation. No human intervention required.

Jenny's Brand Voice Rules (Steal This)

These are the actual rules that govern every piece of content Jenny produces. Adapt them for your brand.

Universal Rules — Apply to Every Platform

0

ZERO emojis

Absolute zero tolerance. Regex catches every Unicode emoji range. No exceptions.

0

ZERO hashtags

Exception: Instagram allows max 3 and must include the brand hashtag.

0

ZERO third-party links

Only your own properties. Every outbound link must point to a domain you control.

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ZERO corporate jargon

synergyleverageecosystemdelveunlockrevolutionarygame-changerexcitinggroundbreakingparadigmdisruptivecutting-edgetransformative

Numbers always as numerals — 30%, not thirty percent

No rhetorical questions — state facts, don't ask vague questions to “engage”

1 sentence = 1 paragraph — short, scannable, punchy

Hook-driven opening — the first line decides if anyone reads the rest

Write as you speak — simple, plain, inclusive

Confidence over hedging — state facts, don't waffle

Platform-Specific Voice Tuning

The same article becomes 6 different posts. Each platform gets an “edginess scale” from 1 to 10 that controls how provocative the AI gets.

X (Twitter)

8.5/10

Sharp, punchy, opinionated

Max 280 chars, shortenings OK

LinkedIn

3.0/10

Professional but human

800-1200 chars, subtle sarcasm only

Instagram

5.0/10

Visual-first, caption supports image

Max 3 hashtags, "link in bio" CTA

Threads

5.5/10

Conversational, provocative

Keep SHORT: 400-600 chars

Facebook

6.5/10

Maximum clickbait hook (without being misleading)

600-900 chars, pattern interrupts

Bluesky

7.0/10

Clever, not corporate

300 chars total, internet-native

The Edginess Scale Concept

Each platform gets a number from 1 to 10 that controls how provocative the AI gets. This single number changes the entire character of the output.

LinkedIn at 3.0

Measured and professional. Data-driven observations. No hot takes.

X at 8.5

Bold claims and hot takes. Opinionated. Punchy. Designed to stop the scroll.

The Validation Layer — Your Quality Gate

Without automated enforcement, rules are just suggestions. The validation layer is what makes voice consistency possible at scale.

The Validation Loop

1

LLM generates post

Content is created based on source material and platform rules

2

Automated validation runs

Every check fires: emojis, hashtags, forbidden words, character limits, link policy

Pass

Post gets published

All checks passed. Content goes live.

Fail

Post goes back to LLM

Specific error instructions included in the retry prompt.

Loop continues until pass — or gets flagged for human review

Most posts pass on the 1st or 2nd attempt. Edge cases get escalated.

What the Validation Layer Checks

Emoji regex

Catches ALL Unicode emoji ranges — not just the common ones

Hashtag detection

Blocked on all platforms except Instagram (where max 3 are allowed)

Forbidden word scanning

Case-insensitive check against the full banned word list

Character limit enforcement

Includes URL shortening math for X — t.co makes every URL 23 chars regardless of original length

Link policy check

Only your own domain allowed. Third-party links get rejected automatically.

UTM parameter verification

Every link must have proper tracking parameters attached

Building Your Voice Document

Use this template to define your own brand voice system. Fill in each field and hand it to your agent as configuration.

Voice Document Template

Brand personality in 3 words

___, ___, ___

Forbidden words (list at least 10)

___

Emoji policy

ZeroLimitedPlatform-specific

Hashtag policy

ZeroBrand onlyPlatform limit

Link policy

Own domain onlyAny

Default tone (1-10 scale)

___

Platform overrides

X → ___

LinkedIn → ___

Instagram → ___

Threads → ___

Facebook → ___

Bluesky → ___

What You Just Learned

  • AI content sounds generic because there are no rules, not because the AI is bad
  • Build a ruleset: forbidden words, tone scale, platform-specific adjustments
  • Add a validation layer that automatically rejects bad output
  • The validation loop (generate → validate → fix → re-validate) is what makes quality consistent

Next: Your voice system is defined. Now let's build the content pipeline that turns source material into platform-ready posts.