GTM LABS
Free Playbook · 6 chapters

The AI-Powered
Growth Playbook.

A practical, no-hype playbook for using AI to drive predictable growth. Six chapters covering foundations, agent design, data infrastructure, lifecycle automation, and the case studies that proved it works.

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Developer-first growth, monthly.

One short, useful essay per month on developer marketing, AI-powered growth, and what's actually working in 2026. Unsubscribe anytime.

What's Inside

01

Welcome to AI-Powered Growth

Beyond the hype: the real impact of AI on business growth

  • Market opportunity — what AI growth is actually unlocking in 2026
  • The systematic approach (not random tools, but connected systems)
  • Building a growth-oriented AI team: Growth PM, ML Engineer, Data Engineer, Growth Marketer
02

Building Your AI Growth Foundation

Data-first mindset and the technology stack

  • Key data sources to map: behavioral, transactional, contextual, intent
  • Edge AI vs. centralized AI — when to use which
  • The personalization stack: data layer → AI processing → personalization engine → delivery → feedback loop
  • Recommended tools: Segment/Tealium CDPs, MLflow/Kubeflow MLOps, Arize/Fiddler monitoring
03

Designing Custom AI Agents

From off-the-shelf tools to bespoke automation

  • When to build vs. buy
  • Agent design patterns: ReAct, planning, tool-use, multi-agent orchestration
  • Frameworks worth knowing: LangGraph, AutoGen, CrewAI, Claude Agent SDK
  • Cost and latency trade-offs at scale
04

AI for Acquisition

Automated lead enrichment, scoring, and outbound

  • Inbound lead enrichment with technographic + behavioral signals
  • Multi-channel orchestration (LinkedIn + email + ads) without copy decay
  • Programmatic SEO at scale without slop
  • Conversational AI for early-stage qualification
05

AI for Retention & Expansion

Lifecycle automation that respects context

  • Behavior-based onboarding flows
  • Predictive churn signals and AI-triggered save plays
  • Upsell timing via usage-pattern analysis
  • Customer health scoring with composite signals
06

Production Case Studies

What worked, what failed, and what to copy

  • Wealthsimple's AI-powered knowledge management
  • AI personalization at fintech scale
  • DevTools companies using AI for community management + content
  • Open-source agent pipelines (the Origin pattern)

Where AI fits in your GTM stack

The hard call isn't "should we use AI" — it's "which workflows are safe to fully automate, which need a human in the loop, and which still need to be human-led." The lines below are how I split it inside actual production engagements.

Comparison of GTM tasks suitable for AI-led automation, hybrid AI plus human workflows, and human-led work across content production, lead enrichment, community monitoring, sales outreach, and analytics.
WorkflowAI-ledHybridHuman-led
Content productionRepurposing one post into 6 channels; SEO drafts; transcript cleanupOutline + first draft AI; angle, voice, opinion humanFounding-story essays, controversial POV, exec ghostwriting
Lead enrichmentTechnographic + firmographic appending; GitHub/Stack Overflow scraping; tieringAI tiers and drafts message; human approves before sendChampion-level account research; board-level intros
Community monitoring24/7 listening across Reddit/HN/Discord; sentiment classification; FAQ triageAI surfaces; DevRel chooses what to engage and howHigh-stakes incident response; founder-level engagement
Sales outreachSequence variant testing; deliverability monitoring; CRM syncAI drafts personalization; AE approves and sends from their inboxDiscovery calls; champion building; pricing negotiation
Analytics & reportingAnomaly detection; daily summaries; auto-generated dashboardsAI surfaces signals; PMM interprets and decides next experimentStrategic narrative for board decks; root-cause investigation

Split based on workflows I actually run inside the open-source DevRel Origin pipeline and the production retainer extension. Some hybrid rows move left (more AI) every quarter as model quality improves.

Want it installed?

AI-Powered Growth ($60K audit + $150K–$250K build) builds these systems for you as a two-phase project.

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