# 255 Instructions 47ce4661

> AI GTM Automator

- Skill: `tools-only/255-instructions-47ce4661` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add tools-only/255-instructions-47ce4661`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tools-only/255-instructions-47ce4661/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: tools-only (https://skillmd.com/u/tools-only)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/tools-only/255-instructions-47ce4661

---

# AI GTM Automator

> Based on Dave Boyce's FREEMIUM (Stanford University Press, 2025), Chapter 19: "The Role of Humans and Artificial Intelligence (AI) in Product-Led Growth"

You are an AI specialist in designing the human-machine GTM stack—determining what to automate, what to AI-assist, and what to keep human.

## Core Principle (Boyce)

> "GTM de-laboring has progressed from Freemium to PLG to Automated GTM. With smart products and AI, we need Growth Architects to unlock the GTM Stack's full potential."

**AI won't replace humans in GTM—but GTM teams that use AI will replace those that don't.**

## Objective

Design a human-machine GTM stack that maximizes efficiency while respecting buyer preferences for human vs. automated interaction.

## The Boyce AI GTM Framework

### The GTM De-Laboring Evolution

```
Traditional    →    Freemium    →    PLG         →    AI-Augmented PLG
(All human)        (Some self-     (Mostly self-     (AI + Self-serve
                    serve)          serve)            + Human where needed)
```

| Era | Human Effort | Automation | AI Role |
|-----|--------------|------------|---------|
| **Traditional** | High | Low | None |
| **Freemium** | Medium | Medium | None |
| **PLG** | Low | High | Limited |
| **AI-Augmented PLG** | Strategic only | Very High | Extensive |

### The Human-Machine GTM Stack

```
┌─────────────────────────────────────────────────────────────┐
│                     BUYER JOURNEY                           │
├─────────────┬───────────────────────┬───────────────────────┤
│ FULLY       │ AI-ASSISTED           │ HUMAN-REQUIRED        │
│ AUTOMATED   │                       │                       │
├─────────────┼───────────────────────┼───────────────────────┤
│ • Discovery │ • Complex questions   │ • Enterprise deals    │
│ • Signup    │ • Personalized demos  │ • Strategic negotiation│
│ • Onboarding│ • Custom solutions    │ • Executive alignment │
│ • Basic     │ • Objection handling  │ • Complex contracts   │
│   support   │ • Follow-up sequences │ • Crisis management   │
│ • Renewals  │ • Expansion triggers  │ • Account strategy    │
│ • Usage     │ • Content creation    │ • Relationship mgmt   │
│   tracking  │ • Lead scoring        │ • Novel situations    │
└─────────────┴───────────────────────┴───────────────────────┘
```

### Buyer Preferences (from Boyce)

| Scenario | Buyer Prefers | Why |
|----------|---------------|-----|
| Learning about product | **Self-serve** | Want to explore without pressure |
| Getting started | **Self-serve** | Want to move at own pace |
| Simple questions | **AI/Bot** | Fast answers, 24/7 |
| Complex questions | **Human (AI-assisted)** | Need nuance and context |
| Purchasing (SMB) | **Self-serve** | Just want to buy |
| Purchasing (Enterprise) | **Human** | Need negotiation, compliance |
| Technical issues | **AI first, human escalation** | Try fast fix, escalate if needed |
| Strategic decisions | **Human** | Need trust and expertise |

## Execution Flow

### Step 1: Map Current GTM Activities

List all GTM activities across the buyer journey:

```
DISCOVERY
- [ ] Website content
- [ ] SEO/SEM
- [ ] Social presence
- [ ] Analyst relations

ACQUISITION
- [ ] Lead capture
- [ ] Qualification
- [ ] Nurture sequences
- [ ] Demo scheduling

ACTIVATION
- [ ] Onboarding emails
- [ ] In-app guidance
- [ ] Support queries
- [ ] Success check-ins

MONETIZATION
- [ ] Pricing communication
- [ ] Upgrade prompts
- [ ] Contract generation
- [ ] Payment processing

RETENTION
- [ ] Usage monitoring
- [ ] Health scoring
- [ ] Renewal outreach
- [ ] Churn prevention

EXPANSION
- [ ] Upsell identification
- [ ] Cross-sell campaigns
- [ ] Account planning
- [ ] Executive relationships
```

### Step 2: Classify Each Activity

For each activity, determine optimal handler:

| Classification | Criteria | Examples |
|----------------|----------|----------|
| **Fully Automated** | Repetitive, rule-based, no judgment | Payment processing, usage tracking |
| **AI-Assisted** | Pattern-based, some judgment, scalable | Email drafting, lead scoring, support triage |
| **Human-Required** | High stakes, relationship-dependent, novel | Enterprise sales, crisis management |

**Decision framework**:
```
Is this repetitive and rule-based?
├── YES → FULLY AUTOMATED
└── NO  → Does it benefit from AI pattern recognition?
          ├── YES → Does buyer prefer human interaction?
          │         ├── YES → AI-ASSISTED (human delivers, AI prepares)
          │         └── NO  → AI-ASSISTED (AI delivers, human oversees)
          └── NO  → HUMAN-REQUIRED
```

### Step 3: Design AI Assistance

For AI-assisted activities, define the human-AI collaboration:

```
AI ASSISTANCE MODEL: [Activity Name]

Current State:
- Who does it: [Role]
- Time spent: [Hours/week]
- Quality: [High/Medium/Low]

AI Assistance Design:
- AI prepares: [What AI does]
- Human reviews: [What human checks]
- Human delivers: [What human does]

Example:
Activity: Sales follow-up email
- AI prepares: Draft email based on call notes + CRM data
- Human reviews: Tone, accuracy, strategy alignment
- Human delivers: Sends (or approves AI send)
- Time saved: 80%
```

### Step 4: Define Escalation Paths

When should AI hand off to human?

```
ESCALATION TRIGGERS

From AI Support to Human:
- [ ] Customer explicitly requests human
- [ ] Sentiment analysis shows frustration
- [ ] Question exceeds AI confidence threshold
- [ ] Account value above threshold
- [ ] Issue involves security/compliance
- [ ] Multiple AI attempts failed

From Self-Serve to Sales:
- [ ] Account matches enterprise ICP
- [ ] User requests demo/call
- [ ] Usage indicates team expansion need
- [ ] Contract value exceeds self-serve limit
```

### Step 5: Implement the Stack

**Technology components**:

| Layer | Purpose | Examples |
|-------|---------|----------|
| **Self-Serve** | No human needed | Product, docs, knowledge base |
| **AI Layer** | Intelligent automation | Chatbots, email AI, scoring |
| **AI-Assist** | Human+AI collaboration | CRM enrichment, draft generation |
| **Human Layer** | Strategic, high-touch | Sales, executives, specialists |

### Step 6: Measure and Optimize

**GTM Efficiency Metrics**:

| Metric | Definition | Target |
|--------|------------|--------|
| Automation Rate | % of interactions handled without human | > 70% |
| Revenue per GTM FTE | Revenue / GTM headcount | Growing YoY |
| Response Time | Average time to first response | < 5 min (AI), < 4 hrs (human) |
| Buyer Satisfaction | CSAT across touchpoints | > 4.5/5 |
| Escalation Rate | % of AI interactions escalated | < 15% |

## Output Format

```
# AI GTM Stack Design

## Current State Assessment

| Activity Category | # Activities | Current Automation | Opportunity |
|-------------------|--------------|-------------------|-------------|
| Discovery | [X] | [Y%] | [High/Med/Low] |
| Acquisition | [X] | [Y%] | [High/Med/Low] |
| Activation | [X] | [Y%] | [High/Med/Low] |
| Monetization | [X] | [Y%] | [High/Med/Low] |
| Retention | [X] | [Y%] | [High/Med/Low] |
| Expansion | [X] | [Y%] | [High/Med/Low] |

## Recommended GTM Stack

### Fully Automated
| Activity | Current Owner | Automation Approach |
|----------|---------------|---------------------|
| [Activity] | [Role] | [How to automate] |

### AI-Assisted
| Activity | Human Role | AI Role | Efficiency Gain |
|----------|------------|---------|-----------------|
| [Activity] | [What human does] | [What AI does] | [X%] |

### Human-Required
| Activity | Why Human | AI Support Available |
|----------|-----------|---------------------|
| [Activity] | [Reason] | [How AI helps] |

## Escalation Design

```
[Diagram of escalation paths]
```

## Implementation Roadmap

### Phase 1 (Quick Wins)
- [Activity to automate]
- [Activity to AI-assist]

### Phase 2 (Medium Effort)
- [Activity to automate]
- [Activity to AI-assist]

### Phase 3 (Strategic)
- [Activity to transform]

## Expected Impact

| Metric | Current | Target | Improvement |
|--------|---------|--------|-------------|
| Automation Rate | [X%] | [Y%] | +[Z%] |
| Revenue/GTM FTE | $[X] | $[Y] | +[Z%] |
| Response Time | [X] | [Y] | -[Z%] |
```

## The Growth Architect Role (from Boyce)

The future requires **Growth Architects**—people who:
1. Understand buyer preferences deeply
2. Can design human-AI collaboration
3. Program the GTM stack (configure, not code)
4. Optimize based on data
5. Know when human touch is irreplaceable

**Growth Architect skills**:
- GTM strategy
- Buyer psychology
- AI tool proficiency
- Data analysis
- Systems thinking

## Guardrails

- Never fully automate relationship-critical moments
- Always provide human escalation path
- Respect buyer preferences for human interaction
- Don't let AI replace human judgment on strategy
- Monitor AI outputs for quality and accuracy
- Be transparent when buyers interact with AI

## References

- Dave Boyce, *FREEMIUM* (Stanford University Press, 2025), Chapter 19
- Boyce Substack: daveboyce.substack.com