Glossary

GTM engineering, agentic AI, and the Wisdom Stack vocabulary

Definitions of the core terms used across DrJoe.me. Designed for mid-market GTM leaders, founders, and revenue operators evaluating modern, AI-native sales models.

GTM Engineering: The discipline of designing, instrumenting, and optimizing a go-to-market system using agentic AI, structured pipeline management, and signal-based prospecting.
Agentic AI: Software agents that autonomously execute multi-step work such as prospect research, intent detection, and data enrichment.
The Wisdom Stack: Dr. Joe Breider's proprietary framework that integrates doctoral business research with 35 years of B2B sales leadership.
Signal-Based Prospecting: Outbound sales activity triggered by buyer signals such as funding events, leadership changes, layoffs, hiring patterns, technology adoption, or intent data.
SDR-to-AE Loop: A lean, engineered handoff process between Sales Development Representatives and Account Executives, designed for unit economics and high-fidelity pipeline.
Pipeline Velocity: The speed at which qualified opportunities move through defined sales stages to closed-won.
Leading Indicators: Forward-looking metrics that predict future revenue, such as qualified meetings booked, opportunity creation rate, and pipeline velocity.
Unit Economics: The per-deal or per-customer profitability lens applied to GTM motion, including CAC, LTV, payback period, and fully loaded cost per sales touch.
Fractional GTM Engineer: A part-time, embedded sales operations and AI orchestration leader who installs systems and agentic AI tooling without full-time headcount cost.
Revenue Contraction to Revenue Expansion: The strategic shift from cost-cutting and pipeline shrinkage post-layoff to engineered growth using existing tooling, leaner teams, and AI orchestration.