Serving organizations outside traditional VC/PE ecosystems. Equitable operational expertise for self-funded companies in the $5M-$30M ARR range—including AI-first startups.
VC-backed companies have armies of operators. You deserve the same level of expertise— without the equity dilution or board complexity.
Built for companies where founders still drive the vision and own their decisions. No committee consensus required.
Efficient capital deployment. Every dollar counts. Growth strategies designed for profitability, not just top-line vanity metrics.
No hidden agendas. No portfolio priorities. Just focused expertise to help you scale your way, on your timeline.
Deep understanding of AI-native business models, product-led growth, and the unique GTM challenges of 2026's landscape.
AI-native companies face unique GTM challenges that traditional SaaS playbooks don't address. Usage-based pricing, product-led growth, and rapidly evolving buyer expectations require different operational expertise.
I've spent the past year working with AI-first startups to understand what actually works— and what's just hype. Let's build your revenue engine for the reality of 2026, not 2019.
Revenue Operations Excellence
Not through more headcount—through better processes, clearer metrics, tighter alignment, and strategically deployed AI agents that handle the operational load so your team can focus on what humans do best.
Built on Winning by Design principles, I establish foundational systems that don't just work today—they scale as you grow from 20 to 200+ people, and adapt as AI agents take on increasing operational responsibility within your revenue motion.
My approach to revenue operations centers on five interconnected capabilities. In 2026, each pillar has a human layer and an emerging AI-agent layer— knowing where to deploy which is the new operational discipline.
Enable teams to work better together across the revenue cycle.
Strengthen connections across functions—marketing, sales, CS, and product.
Drive strategic planning and execution with clarity on priorities and resources.
Harmonize metrics through RevOps instrumentation—one source of truth across the revenue org.
Align messaging across the organization—internally and externally.
The next frontier isn't AI-assisted workflows—it's AI agents that own discrete revenue processes end-to-end, escalating to humans only on exceptions. I help you identify, design, and deploy these automations within your existing stack—without over-engineering or over-spending.
Monitors CRM for stale deals, missing fields, and stage progression anomalies. Flags reps on exceptions and updates forecast categories automatically. Eliminates the weekly RevOps data cleanup cycle.
Tracks new customer product adoption against defined milestones. Triggers CS plays when engagement drops below threshold—before the customer raises a risk flag. Reduces time-to-value and early churn.
Compiles weekly and monthly revenue metrics from CRM, billing, and product data. Writes structured narrative summaries and distributes to stakeholders. Reclaims 4–8 hours/week of RevOps bandwidth.
Continuously monitors usage patterns, support tickets, and engagement signals across your customer base. Surfaces expansion-ready accounts to CS with context and suggested plays—before the QBR conversation.
Runs scenario models against pipeline data, historical conversion rates, and rep-submitted forecasts. Surfaces discrepancies and generates confidence-adjusted projections for leadership review.
Monitors public signals—competitor pricing pages, G2 reviews, job postings, press releases—and updates internal battlecards. Sales reps always have current intelligence without RevOps manually curating it.
The right time to deploy agents is after the underlying process is well-defined and instrumented—not before. That's the work we do together first.
I'm not here to double your outcomes—I'm here to 10x them through better systems, clearer processes, tighter execution, and AI agents that scale what your team already does well.
