Growth & Systems Thinking
The Systems Behind $8B+ in Value Creation
Build data infrastructure before automation. Treat experimentation as an operating system. Measure everything against revenue. I've spent twelve years doing exactly that through three IPOs and PE exits.
The Thesis
GTM Engineering Isn't New to Me. I've Been Building It for a Decade.
Recent GTM frameworks describe a five-layer engineering stack and a thesis on systemic channel degradation. Both describe systems I've already built across three companies. The theory caught up to the practice.
"The hard part isn't writing the script anymore. The hard part is knowing what the script should do: which signals matter, which sequences of actions produce pipeline, which data is trustworthy enough to automate against."
— JA Westenberg, "The GTM Engineering Playbook" (2026)
At each company, I didn't inherit a playbook. I designed the system, chose which layers to build first, wired the measurement, and held myself accountable to pipeline and revenue through IPO preparation and board-level scrutiny.
Framework Mapping
The Five Layers of GTM Engineering, and What I Built at Each
The Playbook defines five deeply coupled layers. Pull one out and the others collapse. Here's how my work maps to each.
Framework
CRM hygiene, enrichment pipelines, identity resolution, warehouse as source of truth
What I Built
Built the Marketo + Salesforce + Bizible stack from scratch at XactlyCorp. Vista Equity cited it as a key asset in their $564M acquisition thesis.
CRM hygiene, enrichment pipelines, identity resolution, warehouse as source of truth
Built the Marketo + Salesforce + Bizible stack from scratch at XactlyCorp. Vista Equity cited it as a key asset in their $564M acquisition thesis.
Framework
ICP modeling from closed-won data, intent signals, account scoring, negative-case analysis
What I Built
6sense + Demandbase ABM engine targeting 50+ Fortune 500 accounts. $40M in ABM-attributed pipeline at XactlyCorp.
ICP modeling from closed-won data, intent signals, account scoring, negative-case analysis
6sense + Demandbase ABM engine targeting 50+ Fortune 500 accounts. $40M in ABM-attributed pipeline at XactlyCorp.
Framework
Relevance-first outreach, signal-triggered sequences, multi-channel orchestration
What I Built
$4M+ across 15+ platforms at Sumo Logic. AI personalization + predictive segmentation at SonarSource drove 586% pipeline growth.
Relevance-first outreach, signal-triggered sequences, multi-channel orchestration
$4M+ across 15+ platforms at Sumo Logic. AI personalization + predictive segmentation at SonarSource drove 586% pipeline growth.
Framework
Deterministic routing, qualification automation, handoff protocols, SLA management
What I Built
Designed hybrid PLG-to-enterprise handoff at SonarSource. Adopted company-wide across six regions as the standard operating model.
Deterministic routing, qualification automation, handoff protocols, SLA management
Designed hybrid PLG-to-enterprise handoff at SonarSource. Adopted company-wide across six regions as the standard operating model.
Framework
Multi-touch attribution, experiment tracking, anomaly alerting, board-level reporting
What I Built
Board reporting at Sumo Logic through IPO. 40+ significant experiment wins annually. 92% pipeline target attainment.
Multi-touch attribution, experiment tracking, anomaly alerting, board-level reporting
Board reporting at Sumo Logic through IPO. 40+ significant experiment wins annually. 92% pipeline target attainment.
"Get this layer right and everything else gets easier. Get it wrong and you'll spend the next two years compensating with increasingly baroque workarounds."
— On data infrastructure, "The GTM Engineering Playbook"
At XactlyCorp, there was no digital demand function, no martech stack, no attribution. I built the data layer first, then audience intelligence, then engagement. The sequence mattered. That foundation supported $80M+ in pipeline, 5x revenue growth, and an acquisition thesis that specifically cited the marketing technology infrastructure.
Strategic Context
Every Channel Is Degrading. Systems Thinkers Build What Compounds.
Organic reach collapsing. Outbound commoditized. Paid CPC up 15-18% annually. AI compressing channel lifecycles from years to months. Here's how the systems I've built address each structural failure.
Market Challenge
Cold outreach reply rates collapsed to 3.4%
AI personalization made every email competent and structurally identical. Volume-first automation poisoned domains and brand equity.
Systems Response
Relevance-first, signal-triggered engagement
At SonarSource: AI-powered predictive buyer segmentation with persona-specific paths for developer, security, and executive audiences. 586% pipeline increase. At Sumo Logic: education-first content for DevOps engineers who distrusted traditional marketing. 80% organic traffic growth. The signal was relevance, not volume.
Market Challenge
Paid ads hit diminishing returns at scale
Marginal CAC exceeds LTV before companies notice. Auction-based platforms drive competitors into negative unit economics.
Systems Response
Channel mix optimization with organic as counterweight
At XactlyCorp: 200% organic traffic growth YoY, cost-per-lead down 35%, freeing budget for ABM. At Sumo Logic: full P&L for $4M+ across 15+ platforms with board-level channel ROI transparency. Quarterly reallocation based on efficiency curves, not intuition.
Market Challenge
75% of the buyer journey happens before sales contact
Research happens in dark social. The traditional funnel optimizes for a process buyers have routed around.
Systems Response
Hybrid PLG/enterprise motion with self-serve paths
At SonarSource: self-serve-to-sales handoff connecting 7M+ developers to enterprise workflows. Intent signal architecture flagged when individual users exhibited enterprise buying patterns. The model became the company-wide GTM standard.
Operating Discipline
Experimentation as Operating System, Not Side Project
What the Frameworks Prescribe
Actual experimental rigor: control groups, sample sizes, statistical significance. Not 'we tried the new thing for two weeks and it felt better.'
Documenting hypotheses, results, and learnings systematically creates more value than any individual tool.
A few well-maintained dashboards with documented definitions beat a hundred ad-hoc reports.
What I Built
Sumo Logic: 40+ statistically significant wins per year across web, conversion flows, and creative. Velocity metrics measuring the pace of improvement itself. The culture extended into Product and Sales.
SonarSource: 158% conversion rate improvement. Testing frameworks influenced product roadmap priorities. Cross-functional operating standard.
XactlyCorp: Attribution framework built from scratch, rigorous enough for IPO preparation and board review.
"Imperfect experimentation beats no experimentation by a wide margin."
— "The GTM Engineering Playbook"
The Track Record
Three Systems, Three Liquidity Events
Each system was built for a specific growth phase. Each contributed to a value creation event. The pattern: data layer first, then intelligence, then engagement at scale, then relentless measurement.
2013 — 2018 · XactlyCorp
Built from zero. Designed for IPO scrutiny.
No digital demand function existed. Built the martech stack, attribution framework, ABM engine targeting 50+ Fortune 500 accounts, and the team (3 → 9). $80M+ influenced pipeline. 5x revenue growth, $25M to $125M ARR.
2019 — 2023 · Sumo Logic
Scaled the engine. $280M+ pipeline through IPO and PE exit.
Global website, 15+ digital platforms, $4M+ P&L. Board reporting, 40+ experiment wins per year, competitive positioning against Splunk, AWS Marketplace GTM strategy. 80% organic traffic growth.
2023 — 2025 · SonarSource
Rebuilt for the next order of magnitude.
Conversion systems rebuilt for a $300M+ ARR developer platform across six regions. AI personalization, hybrid PLG/enterprise motion, systematic experimentation. 586% pipeline growth. 158% conversion improvement. Go-to-market model adopted company-wide.
What I'm Building
PlayHero: From Operating Pattern to Operating System
The consensus in GTM strategy is shifting: engineering is less about code, more about architecture. Knowing what to build matters more than how. PlayHero codifies the patterns from $100M+ in pipeline across three IPO cycles into an AI-powered GTM operating system. Built with Cursor, Vercel, and modern AI tooling. Working code, not a concept deck.
What It Demonstrates
Technical Fluency
Full-stack TypeScript, shadcn/ui, Tailwind, Vercel edge. Hands-on building, not managing from a distance.
What It Demonstrates
Systems Codification
Encoding operational knowledge into repeatable tooling: pipeline accountability, experiment design, ICP modeling.
What It Demonstrates
Judgment as Product
The difference between knowing the playbook and having run it across $8B+ in outcomes, then building software from that experience.
The Takeaway
The Systems Thinker's Case
The market says channel tactics are commoditized, AI compressed the advantage cycle to months, and the only durable moats are judgment, systems architecture, and patience.
My career is the proof case. Five-layer GTM systems built from scratch, scaled through IPOs and PE acquisitions, held accountable to revenue.
I don't execute playbooks. I design the systems that generate them.