The CMO Agent: Your AI Marketing Machine

Most knowledge workers know they should be building an audience. Most don’t because content creation takes time — research, drafting, editing, scheduling, engaging, analyzing. The CMO agent handles all of it.

The CMO is your AI marketing machine. It curates content 3x per day, drafts posts, manages your content calendar, runs engagement sprints, and reports what’s working. You set the brand voice once. The CMO executes it perpetually.

Persona & Philosophy

The CMO operates on one principle: consistent, high-quality content at scale without human bottlenecks.

• Curates the best content from your feeds 3x per day
• Drafts posts aligned with your voice and brand positioning
• Manages tiered autonomy — some things auto-post, others need approval
• Runs engagement sprints (reply-guy on X, comment on LinkedIn)
• Reports weekly: what worked, what didn’t, what to double down on

# CMO SOUL.md
name: "CMO"
model: "anthropic/claude-sonnet-4-6"
domain: "Content creation, social media, brand building, audience growth"
reports_to: "CEO (main)"
brand_voice: "Technical but accessible. No buzzwords. Real insights. Specific examples."
platforms: ["LinkedIn", "X (@Th3RealSocrates)"]

Domain: Your Entire Public Presence

📝 Content Creation

Drafts LinkedIn posts, X threads, and thought leadership pieces. Adapts voice per platform. Always has a 1-week content buffer ready.

📊 Curation

Monitors Reddit, HN, X, and newsletters 3x/day. Filters signal from noise. Builds a content pool for the CMO to draw from.

💬 Engagement

Reply-guy strategy on X. Meaningful comments on LinkedIn. Brand monitoring across platforms.

📈 Analytics

Tracks followers, engagement rate, top posts, growth trend. Weekly analytics report drives strategy adjustments.

Tiered Autonomy Model

The CMO doesn’t auto-post everything. Different content types have different autonomy levels:

Tier	Content Type	Approval	Rationale
Auto-post	Curated shares, retweets, scheduled pre-approved posts	None	Low-risk, pre-approved pattern
Auto-draft → Approve	Original thought leadership, personal stories	Human review	Represents JD’s voice directly
Auto-engage with guardrails	Comments/replies if confidence > 85%	None	Low-stakes, high-volume
Human-only	Career updates, controversial takes, anything personal	Full human	Brand risk too high to automate

This tiered model lets the CMO handle 80% of content operations autonomously while preserving human judgment for the 20% that matters most.

Caution

Get the tiered autonomy model wrong and you’ll either burn out approving every tweet or post something that damages your brand. Define clear boundaries for each tier upfront, and review the auto-post guardrails monthly.

Nested Agent Fleet

LinkedIn Growth Agent

agent: "linkedin-growth"
model: "anthropic/claude-sonnet-4-6"
type: Specialist (cron)
schedule: "3x/week (Mon, Wed, Fri)"
function: >
  Draft LinkedIn post from content pool or standing content themes.
  Format for LinkedIn (hooks, line breaks, hashtags).
  Submit to CMO for approval queue.
  After approval: schedule via LinkedIn native or post directly.
  Post-publish: engage with comments for first 2 hours.
  Log performance to linkedin/post-perf-YYYY-MM.json.

X Growth Agent

agent: "x-growth"
model: "anthropic/claude-sonnet-4-6"
type: Specialist (cron)
schedule: "Daily + 3 engagement sprints/day"
function: >
  Post 3-5 original tweets daily from content pool.
  Run reply-guy engagement (comment on top accounts in niche).
  Monitor mentions + reply.
  Log performance to x/tweet-perf-YYYY-MM.json.
platforms:
  account: "@Th3RealSocrates"
  niche: "AI agents in business"
  target_accounts: ["@AnthropicAI", "@OpenAI", "top AI founders"]

Content Curator

agent: "content-curator"
model: "anthropic/claude-haiku-4-5"
type: Specialist (cron)
schedule: "3x/day (6 AM, 12 PM, 6 PM)"
function: >
  Scan Reddit (r/MachineLearning, r/LocalLLaMA, r/artificial).
  Scan HN (top AI/tech stories).
  Scan X feed for key accounts.
  Filter: relevance to AI agents + JD's positioning.
  Write curated items to ~/clawd/shared/artifacts/cmo/curation/items-YYYY-MM-DD.json.
  Maintains rolling 7-day content pool.

Design Agent

agent: "design-worker"
model: "anthropic/claude-sonnet-4-5"
type: Worker (on-demand)
function: >
  Create LinkedIn infographics (HTML/CSS → Playwright → PDF/PNG).
  Create data visualizations for posts.
  Generate carousel slides for multi-image posts.
  Input: content brief + key data points.
  Output: image file + caption copy.

Brand Monitor

agent: "brand-monitor"
model: "anthropic/claude-haiku-4-5"
type: Specialist (cron)
schedule: "Daily"
function: >
  Track mentions of JD's name + handle across platforms.
  Identify engagement opportunities (people discussing JD's topics).
  Flag reputation issues immediately.
  Write mentions/log-YYYY-MM.json.

The Content Pipeline

The CMO runs a disciplined content pipeline — nothing gets posted ad hoc:

Curation (3x/day)
  Content Curator scans feeds
  ↓
  Filtered items → Content Pool

Content Pool
  ~/clawd/shared/artifacts/cmo/content-pool-status.json
  Rolling 7-day supply
  ↓

Weekly Planning (Sunday)
  CMO pulls from content pool + standing themes
  Creates content-calendar-YYYY-WW.md
  ↓

Draft Stage
  LinkedIn Growth or X Growth agents draft posts
  Submit to CMO approval queue if Tier 2
  ↓

Auto-approved (Tier 1)? → Publish immediately
Needs approval (Tier 2)? → Human reviews → Approve/Edit/Reject
  ↓

Published
  Post-publish engagement (2-hour window)
  Performance logged to JSON
  ↓

Weekly Analytics
  CMO aggregates: top posts, growth rate, engagement %
  Adjusts strategy for next week

Standing Orders

Order	Schedule	Description
Content Curation	3x daily	Curate → content pool → filter noise
Daily X Posts	Daily	3-5 tweets from content pool
Engagement Sprints	3x daily	Reply-guy on X, comments on LinkedIn
Weekly Content Calendar	Sunday	Plan next week’s posts
Weekly Analytics	Monday AM	Growth metrics, top posts, strategy adjustments
Monthly Strategy Review	1st of month	Comprehensive analytics, adjust positioning

Key Integrations

Integration	Tool	Use
X / Twitter	x-growth skill + browser automation	Post tweets, monitor mentions, reply-guy
LinkedIn	linkedin-growth skill + browser	Draft posts, post content, engage
Reddit	reddit-reader skill	Content curation source
HN	web_fetch + web_search	Content curation source
Infographics	HTML/CSS → Playwright → PNG	Visual content creation
LinkedIn Carousels	linkedin-carousel skill	Multi-slide posts
Video	ai-video skill	Short explainer videos

Reporting Artifacts

~/clawd/agents/cmo/artifacts/
├── content-calendar-YYYY-WW.md      # Weekly (Sunday)
├── weekly-analytics-YYYY-WW.md      # Weekly
├── brand-mentions-YYYY-WW.md        # Weekly

~/clawd/shared/dashboard/
├── social-analytics.json            # Daily
├── platform-metrics.json            # Daily
└── content-pool-status.json         # Daily

Per-platform artifacts:
├── linkedin/post-perf-YYYY-MM.json  # Per post
└── x/tweet-perf-YYYY-MM.json        # Per tweet

Analytics dashboard JSON:

{
  "lastUpdated": "2026-03-27T08:00:00Z",
  "linkedin": {
    "followers": 2847,
    "weeklyGrowth": 34,
    "weeklyGrowthPct": 1.2,
    "avgEngagementRate": 4.2,
    "postsThisWeek": 4,
    "topPost": { "title": "C-Suite AI Architecture", "impressions": 4200, "engagementRate": 6.8 }
  },
  "x": {
    "followers": 1243,
    "weeklyGrowth": 28,
    "weeklyGrowthPct": 2.3,
    "avgEngagementRate": 3.1,
    "tweetsThisWeek": 22,
    "impressionsThisWeek": 18400
  },
  "contentPipelineHealth": "green",
  "contentPoolDays": 9
}

CMO KPIs

Metric	Target
LinkedIn posts per week	3-5
X tweets per day	5+
LinkedIn engagement rate	>3%
X engagement rate	>2%
Content pipeline health	Always 1 week ahead
LinkedIn follower growth	>2% weekly
X follower growth	>2% weekly
Brand mentions processed	Same day

Configuration Example

{
  "agentId": "cmo",
  "name": "CMO",
  "model": "anthropic/claude-sonnet-4-6",
  "workspace": "~/clawd/agents/cmo",
  "heartbeat": {
    "enabled": true,
    "intervalMinutes": 60
  },
  "crons": [
    { "name": "content-curation-am", "schedule": "0 6 * * *", "task": "Curate content" },
    { "name": "content-curation-noon", "schedule": "0 12 * * *", "task": "Curate content" },
    { "name": "content-curation-pm", "schedule": "0 18 * * *", "task": "Curate content" },
    { "name": "weekly-calendar", "schedule": "0 10 * * 0", "task": "Create weekly content calendar" },
    { "name": "weekly-analytics", "schedule": "0 8 * * 1", "task": "Weekly analytics report" }
  ],
  "nestedAgents": ["linkedin-growth", "x-growth", "content-curator", "design-worker", "brand-monitor"],
  "reportsTo": "main",
  "tieredAutonomy": {
    "autoPost": ["curated-shares", "pre-approved"],
    "requiresApproval": ["original-thought-leadership", "personal-stories"],
    "humanOnly": ["career-updates", "controversial", "personal"]
  }
}

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Next: CIO Agent — AI intelligence, tech radar, and industry monitoring.

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About the author: JD Davenport builds AI agent systems at OpenClaw. Follow on LinkedIn for updates on building AI agents for business.

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