34-ai-marketing-os-global

# AI Marketing OS (Global)

This skill designs the operating system for AI-assisted marketing: source of truth, roles, skill chains, data loops, review cadence, and handoffs. The goal is to help a team use AI as an operating system, not as scattered one-off prompts.

## Information gathering

Read `.agents/product-marketing-context-global.md` if available. If the user has a plan, dashboard, SOP, Notion/Drive structure, ads report, or campaign brief, use it as input. Ask up to 4 questions: team structure, 90-day goal, current AI/tool stack, and biggest workflow pain. For detailed patterns, read `references/ai-marketing-os-playbook.md`.

## When to use

Use this skill when the user needs to:

- Build an AI Marketing OS for an SMB, agency, SaaS team, creator-led business, education business, service business, or B2B team.
- Audit how the team uses AI: repeated prompts, lost context, disconnected chats, weak reporting, or no source of truth.
- Design a Brand Hub, skill chain, role-based agent/project setup, MCP/connectors, and Notion/Drive second brain.
- Create daily, weekly, and monthly SOPs for content, performance, campaigns, reporting, and handoffs.

Do not use this skill for a single artifact. Use the relevant older skill instead: `00-marketing-plan-global`, `01-content-calendar-global`, `02-campaign-brief-global`, `05-ad-copy-global`, `07-marketing-report-global`, `10-reverse-kpi-global`, or `31-offer-design-global`.

## Principles

1. **Brand Hub is the source of truth.** Scattered context creates inconsistent agent output.
2. **Roles before tools.** Define Strategy, Campaign, Content, Design, Performance, and Sales/RevOps before choosing tools.
3. **Skill chains beat one-off prompts.** Every workflow should define input, skill, output, and next skill.
4. **Old data before new plans.** New plans should read previous reports, dashboards, bottlenecks, and lessons.
5. **Human approval at risk points.** Budget, claims, legal/privacy, brand voice, and campaign launch need review.
6. **Small cycles, steady review.** Daily check, weekly decision review, monthly retro, quarterly refresh.

## Workflow

### 1. Audit the current AI stack

Score maturity from 0-4:

| Level | Signal |
|-------|--------|
| 0 | Ad hoc AI use, no saved context |
| 1 | Prompt templates, but manual copy/paste |
| 2 | Context files and individual skills exist |
| 3 | Brand Hub, role workspaces, and review cadence exist |
| 4 | Connectors/data loops, dashboards, second brain, and governance exist |

If maturity is below 2, build foundation before adding automation.

### 2. Design the Brand Hub

Minimum Brand Hub:

1. Brand Guidelines: logo, color, typography, tone, voice, do/don't.
2. Customer Insight: persona, pain, trigger, objection, customer language.
3. Positioning & Offer: promise, proof, path, offer ladder.
4. Content Pillars: pillars, angles, source content, platform rules.
5. KPI Framework: revenue target, funnel KPI, benchmarks, decision rules.
6. Campaign Template: phases, budget split, asset list, approval flow.

When a file changes, update the relevant role workspaces.

### 3. Map role workspaces

| Role | Main work | Common repo skills |
|------|-----------|--------------------|
| Strategy | Market, offer, budget, KPI | 00, 08, 09, 10, 31 |
| Campaign Lead | Brief, timeline, assets, handoff, retro | 02, 07, 20, 34 |
| Content | Calendar, scripts, copy, UGC, email | 01, 04, 05, 06, 14 |
| Design | Visual brief, brand system, landing page | 12, 30 |
| Performance | Tracking, audit, reporting, data decisions | 03, 07, 13, 19, 21 |
| Sales/RevOps | Lead quality, handoff, outreach | 18, 33 |

If the user uses Claude Projects, ChatGPT Projects/GPTs, NotebookLM, Notion, Drive, or MCP, map each tool to these roles. Keep the system vendor-neutral unless the user has already chosen a stack.

### 4. Build skill chains

Default workflow chains:

| Workflow | Suggested chain |
|----------|-----------------|
| Brand/client onboarding | product-marketing-context-global -> 09 -> 08 -> 31 -> 10 -> 34 |
| Campaign launch | 02 -> 31 -> 10 -> 01/04/05/06 -> 12 -> 21 -> 07 |
| Weekly performance | 13 -> 03/21 -> 07 -> 34 updates Brand Hub |
| Content engine | 09 -> 01 -> 04/05/06 -> 15 -> 07 |

If previous-period data exists, read it before creating a new plan.

### 5. Set up data and second brain

Minimum stack:

- Storage: Drive/SharePoint/Dropbox for files and assets.
- Database: Notion/Coda/Sheets for resource table, campaign archive, case studies, and decision log.
- Analytics: Meta Ads, TikTok Ads, Google Ads, GA4, CRM, email, UTM.
- Connector layer: MCP or equivalent connectors for knowledge base, marketing analytics, design, email, and CRM.

Every important output needs owner, date, source, version, and next action.

### 6. Create operating cadence

| Cadence | Focus | Output |
|---------|-------|--------|
| Daily 15m | Spend, delivery, comments/inbox, tracking issues | Blocker list |
| Weekly 30-60m | KPI vs target, winners/losers, bottleneck, next actions | Weekly decision log |
| Monthly | Revenue, channel mix, offer, team load, Brand Hub changes | OS retro + roadmap |
| Quarterly | Market, positioning, offer ladder, tool stack | Strategy refresh |

### 7. Governance and risk

Check:

- Access: who can see customer data, ads data, CRM, and revenue.
- Claims and proof: do not let AI invent proof or regulated claims.
- Privacy: do not paste PII into unapproved tools.
- Prompt injection: be careful with websites, comments, inbox exports, and external files.
- Brand drift: compare new outputs against the Brand Hub.

## Output template

```markdown
# AI Marketing OS — [Business/team]

## 1. Current diagnosis
| Area | Level 0-4 | Evidence | Priority |

## 2. Brand Hub
| File | Status | Owner | Update cadence |

## 3. Role workspaces
| Role | Tool/workspace | Context loaded | Main output |

## 4. Skill chains
| Workflow | Skill chain | Required input | Output |

## 5. Data loop and connectors
| Data source | Tool/connecto