Five ideas, built from twenty years of doing this.
A repeatable point of view, not just a résumé — four on the marketing and growth side, one on revenue operations, the discipline that makes the other four trustworthy.
The AI-Lean Operating Model
How to redesign a marketing and revenue org chart around AI as the default operator, with a role-by-role breakdown of what stays human and what doesn’t. The result: a 3.5–5 FTE human team matches the output of a 6–8 person team. The metric that matters is revenue per FTE, not headcount.
The Cost-Center-to-Revenue-Center Playbook
A 90-day sequence, run in different forms three times over: attribution before anything else, a diagnostic funnel audit with no assumptions, then two high-impact initiatives instead of ten mediocre ones. The first-90-days move for any new revenue leader walking into an unproven function.
The Account Expansion Flywheel
Land → Bridge → Expand → Deepen, with revenue math attached at each stage — a $15K entry engagement growing into a $500K–$1M mature account. Backed by a real result: a 3× revenue lift from customers in a formal advocacy program.
Quality-Over-Volume ABM Math
An explicit rejection of the MQL-volume model: 10 accounts at $100K ACV beats 50 accounts at $20K. A general argument against vanity-metric marketing, and against how most B2B marketing teams still report success.
The Single-Source-of-Truth RevOps Model
The other half of “Revenue Architect”: designate one platform as the system of record, map every field and every data-entry point before touching a campaign, and treat data hygiene — opt-in validation, ping tests, dedup cycles — as a revenue function, not IT housekeeping. This is what makes Framework 01 trustworthy: AI run on bad CRM data just makes bad decisions faster.