GTM Engineering
GTM Engineering is the discipline of composing AI, data, and software into revenue systems that work without armies of SDRs. This hub is the long-form education layer: definitional pillars, a learning path, copy-able playbooks, and a curated resource list.
The category definition: what GTM engineers actually build, why the role exists now, and how it differs from RevOps.
Read → PillarA taxonomy of the tools every GTM engineer touches — enrichment, orchestration, the LLM layer, CRM-as-database, monitoring.
Read → Curated guideA four-stage progression from your first Clay table to running production GTM systems. With linked resources at each stage.
Read → LibraryStep-by-step builds you can copy: waterfall enrichment, inbound routing, deanonymized visitor capture, AI SDR pipelines.
Read → LibraryDecision frameworks: how to vet a GTM tool, choosing your CRM at seed, what to measure in a stack audit, why most AI SDRs fail.
Read → Curated listBooks, newsletters, podcasts, communities, courses, and conferences worth your time — each with a one-line "why."
Read →Featured playbook
A practical guide to replacing gut-feel deal forecasting with an AI-powered confidence scoring layer built on Claude's API and HubSpot's engagement data. This playbook walks through the exact Claude prompt template, an n8n workflow that pulls…
Read the playbook →