Fiscal Integrity
Scaling Forecast Accuracy from 70% to 95%
A "lumpy" pipeline with no discernible patterns made revenue forecasting nearly impossible, creating friction between Sales and Finance.
Key Result95% Forecast Accuracy
Scaling revenue engines for the next era of SaaS.
With two decades of experience scaling SaaS leaders from Series A to IPO, I specialize in the architecture of high-growth revenue engines. I align Finance, Sales, and Product through data-driven strategy and AI-enhanced workflows to ensure organizations stay agile in an evolving market.
Operating Philosophy
Engineering high-velocity revenue systems.
I build the “single source of truth” environments where data-driven strategy replaces reactive decision-making—transforming operational debt into a scalable engine for growth.
Fiscal Integrity
Predictability at Scale
I partner with CFOs to translate complex pipeline data into high-fidelity forecasting and board-ready reporting.
Lifecycle Architecture
Frictionless GTM Alignment
I design infrastructure where PLG and Sales-Led motions work in tandem, mirroring the modern customer journey from trial to renewal.
Human Velocity
AI-Enhanced Productivity
I leverage automation and AI workflows to slash AE ramp time and accelerate ‘Time to First Deal,’ allowing people to move at peak speed.
Expertise
Breadth across the executive table. Depth in the systems beneath it.
Finance Alignment
Partnering with the CRO and CFO to translate pipeline activity into board-credible forecasts and predictable revenue.
GTM Strategy
Designing the territory, segmentation, and motion that turn market opportunity into repeatable pipeline.
Product Integration
Connecting product signals — usage, activation, and expansion — to the revenue motion so PLG and Sales work in tandem.
Systems Architecture
Lead-to-cash design, deal desk, forecasting cadence, and the operating rhythm that holds the GTM engine together.
Revenue Intelligence
Transforming raw data into actionable insights through AI-driven forecasting and pipeline health analytics.
Operational Governance
Establishing the rules, data hygiene, and validation logic that keep the engine clean and the numbers trustworthy.
Case Studies
Engineered outcomes, not anecdotes.
Three representative engagements where strategy met systems — and the numbers moved.
Architectural Transformation
Compressing Deal Desk Velocity by 80%
Rapidly doubling field headcount led to a slow, manual quote-to-cash process where historical customer data lived in disconnected Google Drives.
Key Result80% Faster Deal Desk
Human Velocity
Slashing Rep On-Ramp Time via AI-Intelligence Signals
Scaling the sales org was "scaling the chaos," with inconsistent territory assignments and resistance to new forecasting tools.
Key Result100% Tool Adoption
Every result above was achieved by aligning technical architecture with cross-functional human strategy.
Projects with AI
Systems shipped, outcomes earned — with AI.
Built This Site with AI — No Developer Required
I designed and shipped this site using Claude (Anthropic) and Lovable, an AI-native web builder. No agency, no developer, no months-long project. I wrote the strategy, drafted the copy, and iterated on the design through prompts, treating the AI as a junior team member I was directing. It's live and it took days not months. And I will continue to iterate and release as I work on it. It's also a live demonstration of how I approach any new operational tool: start with the outcome, prompt toward it, and iterate until it's right.
What this shows
That's how I approach operational tooling: find the right leverage, move fast, own the output.
When My Daughter Needed an App, I Built One — With AI
My teenager needed a wellness tracker — something friendlier than a clinical app — that she'd actually use. So I built one. Using Lovable and Claude, I designed and shipped a fully functional mobile PWA: custom calendar UI, daily symptom logging, pattern analysis, and a custom icon she helped design. No developer, no budget, no prior app-building experience. I wrote the specs, made the product decisions, and iterated via prompts until it was done. It's live and her friend group uses it today. You can see it here.
What this shows
The barrier to building real software is now your ability to think clearly about a problem and direct an AI toward a solution. That's a skill I use at work every day — and apparently at home too.
How I Run RevOps with an AI-Augmented Stack
I've replaced manual overhead with AI workflows across my day-to-day: Granola captures meeting notes automatically so nothing falls through the cracks. Whispr Flow handles transcription and action extraction. Claude handles analysis and GTM decision-making. Gong surfaces deal risk without manual review. The result: the cognitive overhead of tracking everything is largely gone. I spend time on judgment calls, not information management.
What this shows
The best RevOps leaders today aren't just operators. They're systems designers who use AI to multiply their own output.
Automating the Forecast So the CRO Stops Being Surprised
I built automated pipeline inspection workflows that ran before every weekly forecast call, flagging deals at risk of slipping based on activity signals, stage age, and close date movement. Instead of waiting for a rep to self-report a problem on Thursday, the system surfaced it on Monday. The result: fewer surprises, more productive forecast calls, and a culture shift from reactive firefighting to proactive deal management.
What this shows
Forecast accuracy isn't a one-time fix. It's an ongoing system. I build the infrastructure that keeps it honest.
Replacing Gut Feel with a Model — 30% Better SDR Connect Rates in 90 Days
Static lead scoring was sending SDRs after the wrong accounts — high firmographic scores, low actual buying intent. I replaced it with an AI-assisted model that combined firmographic data with behavioral signals: product usage patterns, content engagement, and historical conversion data by segment. SDRs stopped chasing cold leads and started working accounts already showing intent signals. Within 90 days, connect rates improved by 30%+, and time-to-pipeline dropped meaningfully.
What this shows
AI is most powerful when it removes the guesswork from high-volume, high-stakes decisions — like which accounts a seller should call today.
When the Foundation Is Broken: Rebuilding CRM Data Integrity from 60%
At RunZero, we couldn't buy our way to a clean database — no single provider had complete coverage. An internal audit revealed our CRM was only 60% accurate: duplicates, wrong firmographics, stale accounts. We rebuilt it the hard way — manual review by SalesOps and MarketingOps, layered against multiple third-party sources — and arrived at a more reliable TAM picture. It worked, but it was slow and expensive in human hours. Today I'd approach this entirely differently: AI can audit a CRM against live firmographic data in hours, flag every bad record, and maintain accuracy automatically. The one-time cleanup project becomes a continuous, self-correcting workflow.
What this shows
Data integrity isn't a project — it's an architecture decision. And AI has fundamentally changed what good data hygiene looks like.
Experience
A career building revenue engines.
Currently exploring Revenue and Sales Operations leadership opportunities at growth-stage SaaS companies.
Skills
The tools and disciplines behind the work.
Leadership & Strategy
- GTM Strategy & Architecture
- Strategic Planning & Executive Partnering
- Sales Performance & Forecast Rigor
- IPO & M&A Readiness
- Deal Desk & Contract Architecture
- Sales Compensation & Quota Design
- Pipeline Acceleration
- Sales Enablement & Methodology
- Cross-functional Alignment & Change Management
- Cybersecurity GTM Strategy
- Healthcare/Digital Health Scaling
Tech Stack
- Salesforce
- HubSpot
- LeanData
- Clari
- Gong
- Outreach
- Salesloft
- Tableau
- Looker
- ThoughtSpot
- Conga
- DocuSign
- Cloudingo
- LinkedIn Sales Navigator
- Jira
- Asana
- Slack Enterprise
- Granola
- Whispr Flow
- Claude
- Gemini
- ChatGPT
This list is not exhaustive — I’m continuously adding tools and capabilities as the landscape evolves.
Outside of Work
Outside of work, I’m just as driven. I swim with a masters team, run trails daily with Cosmo, our rescue dog who takes his herding duties very seriously, and recently finished my first hand-knit sweater after deciding rectangles weren’t enough of a challenge. Thirteen marathons, two Alcatraz-to-SF swims, and more Olympic-distance triathlons than I care to count are in the rearview mirror. I live in the Bay Area with my family.
Let’s talk
Let’s build something that scales.
I’m currently available for full-time, fractional, and consulting engagements. If you’re scaling a GTM motion and need an operator who’s done it before — let’s talk.