Frameworks & field notes from the GTMhub Labs.
What we're learning, what we shipped, what didn't work. Original frameworks, primers, and case studies on the AI-native GTM stack. No takeaways for the sake of takeaways.
The AI-native GTM stack: a working architecture.
A framework for thinking about agents, workflows, and data in modern B2B revenue — and why most "AI for sales" tools fail the second they hit your CRM.
Signal-based outbound: detection, scoring, and acting
How to detect buying intent across 40+ data sources and trigger plays your reps will actually run. Scoring without overfitting.
Building a research agent for B2B sales
Inside the architecture of our account research agent: prompt routing, eval harness, hallucination guards.
Eval-driven GTM: stop shipping AI on vibes
A small evaluator + a 5% human sample is enough quality gating to ship AI into production GTM.
B2B paid benchmarks: Q1 2026 across 14 portfolios
CPL, ROAS, and channel-mix benchmarks across fintech, SaaS, healthcare, logistics. What "good" looks like by stage and segment.
A funding-signal alone moved reply rate 3.5x
One signal. Two weeks. Reply rate from 1.1% → 3.8% on triggered accounts. What we changed and what we didn't.
Email deliverability in 2026: the SendSure playbook
Continuous warmup, reputation monitoring, seed-list testing, auto-recovery. The actual mechanics of 89% inbox placement.
Attribution that survives privacy, ad blockers, and dark social
Multi-touch + self-reported + offline conversion uploads. The pragmatic attribution stack we ship to clients.
The 12 tools we install on every engagement
Outreach, Clay, Apollo, Clearbit, Gong, Snowflake, dbt, Hex, Slack, Linear, Notion, Langfuse. What each one does and what we replace.
Cutting CAC by 41% for a clinical-trial recruitment platform
Repositioned messaging, killed three paid channels, doubled down on signal-based outbound. 6 months. Anonymized.
Why we rejected an "AI SDR" pitch six times
Six VCs and three founders pitched us "AI SDRs." We said no every time. Here's the test we apply and why most fail it.
ABM at scale: how to run 4,000 accounts without templating
Tiering, signal-routing, persona-aware composition. The mechanical version of "personalization at scale" that actually personalizes.
The compounding-pipeline thesis
Why operations + product + content compound where one-off campaigns don't. The thesis behind every GTMhub engagement.
One working framework a week.
Original research, written down. No fluff, no takeaways for the sake of takeaways.