Stop filtering B2B SaaS prospects by firmographics. Instead, vectorize the problem you solve - identify the variables that make it harder (scale, complexity, volatility), map your solution's sweet spot on each spectrum, and score companies by problem intensity. Companies that vectorize their ICP see 2-3x higher response rates by targeting acute pain instead of demographic fit.

High-volume outbound died when everyone adopted the same playbook. The constraint shifted from reach to relevance, but most GTM systems are still optimized for the wrong problem - sending more emails instead of building better context. This article breaks down why static ICP lists are dead, how signal-based ICS targeting actually works, and what GTM engineers need to build instead of blast.

GTM Engineering treats your go-to-market as a production system with constraints you can optimize, not an art practiced by talented individuals. Find the bottleneck blocking throughput, automate it, measure impact, move to the next one. Scale 2-3x output without scaling headcount.

Theory of Constraints applied to GTM: your system has one primary bottleneck determining throughput. Most teams optimize non-constraints (email templates, training, dashboards) which doesn't improve pipeline. Find the actual constraint, attack it, measure if it moved, attack the next one. Repeat until you hit target throughput.