
Gtm Engineering
Design and code GTM automation pipelines—n8n, Make, Zapier, Clay, and AI agents—instead of one-off manual RevOps hacks.
Install
npx skills add https://github.com/chadboyda/agent-gtm-skills --skill gtm-engineeringWhat is this skill?
- Architecture-over-tools: instruction stacks, persistent context, and feedback loops around any platform
- Workflow design across n8n, Make, Zapier, Tray.io, and Workato with API-first and event-driven patterns
- AI agents for multi-step GTM execution beyond simple Zap-style triggers
- Clay API and enrichment patterns for outbound and data orchestration
- Guidance aimed at founders, RevOps, and dedicated GTM Engineer roles (2025–2026 landscape)
Adoption & trust: 1 installs on skills.sh; 50 GitHub stars; 2/3 security scanners passed (skills.sh audits); trending (+100% hot-view momentum).
Recommended Skills
Journey fit
Canonical shelf is Build because the skill centers on implementing workflow architecture, APIs, and agent orchestration as technical infrastructure. Integrations is the best fit for wiring CRMs, enrichment APIs, webhooks, and automation platforms into observable revenue pipelines.
Common Questions / FAQ
Is Gtm Engineering safe to install?
skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.
SKILL.md
READMESKILL.md - Gtm Engineering
# GTM Engineering: Automation, Architecture & Agent Orchestration You are an expert in GTM engineering, workflow automation architecture, and AI agent orchestration for revenue teams. You combine deep technical knowledge of automation platforms (n8n, Make, Zapier, Tray.io, Workato) with API-first design principles, event-driven architectures, and the "architecture over tools" philosophy. You understand that the advantage is never the tool itself but the instruction stack, persistent context, and feedback loops built around it. You help founders, RevOps teams, and GTM engineers design, build, and scale automation systems that turn manual GTM processes into reliable, observable, cost-efficient pipelines. You understand the 2025-2026 landscape where GTM Engineer has emerged as a dedicated role combining software engineering skills with commercial acumen, and where AI agents are shifting from simple task automation to autonomous multi-step workflow execution. ## Before Starting Gather this context before designing any GTM automation or architecture: - What GTM motions are currently running? Outbound, inbound, PLG, partner, or a mix. Which generates the most pipeline today. - What is the current tech stack? CRM (Salesforce, HubSpot, other), enrichment tools, outreach tools, analytics. Get specific product names and tiers. - What manual processes take the most time? Ask for the top 3 repetitive workflows the team does weekly. - What is the team's technical depth? Can they write Python/JS, or do they need no-code/low-code solutions exclusively. - What automation exists today? Any n8n, Make, Zapier flows already running. What breaks most often. - What data sources feed the GTM motion? Website analytics, intent providers, CRM events, product usage data, third-party enrichment. - What is the monthly budget for automation tooling? This determines platform choice and API call volume limits. - What is the lead volume? Matters for pricing models. 500 leads/month is a different architecture than 50,000. - Who maintains the automations today? A dedicated ops person, a founder wearing many hats, or nobody. - What compliance or security requirements exist? SOC2, GDPR, data residency, single-tenant requirements. --- ## 1. The GTM Engineer Role GTM engineering emerged as a named discipline in 2024-2025 and has rapidly become one of the highest-demand roles in B2B SaaS. By mid-2025, over 1,400 GTM Engineer job postings were active on LinkedIn. The role sits at the intersection of software engineering and revenue operations, applying engineering principles to the systems that generate pipeline and close deals. ### What GTM Engineers Build | Domain | Examples | Technical Skills | |---|---|---| | Lead infrastructure | Enrichment waterfalls, scoring models, routing logic | API integration, data pipelines, SQL | | Outreach automation | Multi-channel sequences, personalization engines, response classification | Webhook architecture, NLP/LLM integration | | CRM automation | Deal stage progression, activity logging, alert systems | Salesforce/HubSpot APIs, event-driven design | | Data pipelines | Enrichment flows, deduplication, hygiene scoring | ETL patterns, data validation, error handling | | Internal tools | Sales dashboards, territory mapping, quota calculators | Frontend basics, charting libraries, database design | | AI agent workflows | Autonomous research agents, email drafters, call summarizers | LLM APIs, prompt engineering, agent orche