The Black Swan in the Sales Funnel

We are offering a big discount (30% off our monthly price) if you pay for an annual membership in Bitcoin. Reach out to me!

---

You learn a few things working on Wall Street. You learn about risk, the dizzying asymmetry of it. You learn how quickly meticulously crafted models, elegant in their complexity, can be rendered useless by the one variable you couldn't, or wouldn't, see. In banking and later at the hedge fund I co-founded, we weren’t creating value; we were masters of relocating it, of pricing its future existence, of hedging against its sudden absence. We were building intricate ships in a bottle, perfect until the bottle itself gets knocked off the shelf.

Then I looked at tech. I saw passionate, creative minds not just moving value around, but creating it from scratch. It was the difference between betting on the weather and building the storm shelter. Seeing the exponential curves of machine learning capabilities, the plummeting cost of compute power—it was obvious. The real alpha was being forged in code. That’s where I needed to be.

So I traded my Bloomberg Terminal for a Jupyter Notebook. I became obsessed, diving into the deep end of machine learning, spending nights and weekends battling it out on Kaggle, building novel systems in hackathons, and devouring research papers like they were SEC filings. I took the quantitative rigor from finance and my nerdy side quests to gain technical ability and pointed it all at a new domain: the corporate revenue engine.

Because here’s the secret: a company’s GTM system is a complex adaptive system, just like the financial markets. And for a decade, most of them were being built with a staggering, unrecognized fragility.

My focus became singular: use a mix of strategy, analysis, and engineering to build powerful, efficient, and reliable revenue engines. This is the domain of RevOps. It’s about meshing GTM best practices with master data management, AI, and automation to build something that doesn't just work, but endures.

And looking at the last fifteen years of GTM evolution, it's a perfect story of fragility, crisis, and the painful, necessary birth of resilience.

Part I: The Age of Brittle Blueprints (2011 - 2018)

Rewind to the world post-2008. The financial system had just revealed its profound fragility. Out of that wreckage, a new engine of growth emerged: Software-as-a-Service. The "SaaS-Native Era" was born, and with it, a new orthodoxy for how to sell.

This was the Process-Driven Era (2011). If you were a founder, you were handed a playbook. It was likely dog-eared, highlighted, and treated as gospel. The new testament was Predictable Revenue. The strategy back then was Inside Sales. The church was Salesforce. Growth became a manufacturing problem. You build a conveyor belt, hire specialized workers to man each station, and turn the crank.

The characters in this play were new and hyper-specialized. You had the Sales Development Rep (SDR), whose entire world was a list of names and a call script. Their job was to qualify leads, book meetings, and pass them down the line to the Account Executive (AE), the "closer" Marketing’s job was to fill the top of this funnel with "MQLs" using the new magic of inbound marketing and rudimentary email automation.

It was beautifully simple. It was scalable. And it was incredibly brittle.

This system was optimized for a single, stable environment: a bull market with plentiful capital and a greenfield of unsuspecting customers. The mantra was scale over personalization. We were building systems that treated humans—both our employees and our customers—as uniform cogs.

I had a sales executive tell me to read this book as recently as 2022. Talk about “trying to win the last war”. Wild.

By 2015, we tried to make the cogs spin faster with Automation. Sales got sequencing tools. Marketing got Marketo. Customer Success, now its own formalized silo with CSMs, got its own platforms. Each function, in its own "Functional Isolation" optimized its piece of the conveyor belt. Marketing Ops, Sales Ops, CS Ops—they all built impressive, independent engines.

But they weren't connected. Integrators LOVED it. Consultants of all kinds, really.

It was a classic local optimization problem. A boondoggle in the making.

The system as a whole became a Frankenstein's monster of well-oiled limbs that didn't know how the others were moving. The customer journey felt it most, passed from one disconnected process to the next. The data, the lifeblood of any intelligent system, was fractured, duplicated, and often contradictory across these silos. We were accumulating a hidden debt, a systemic risk that was invisible on the quarterly growth reports. The engine was screaming, but the car wasn't going any faster.

Part II: The Turkey Problem and the Thanksgiving Day Massacre (2019 - 2021)

Nassim Taleb describes the "Turkey Problem."

A turkey is fed by a farmer for a thousand days. Every day, its belief that the farmer is a benevolent friend is confirmed and reinforced. Its data models, based on a thousand data points, would predict an ever-improving future of free food. It gets fatter, more confident, more optimized for this wonderful environment. Then, the day before Thanksgiving, something entirely unexpected happens, and the turkey's understanding of the world is proven to be catastrophically wrong.

The SaaS GTM engine was that turkey.

The first sign of sickness came around 2019 with the Productivity Drop. The numbers just stopped working. You couldn't just hire more SDRs to hit your number anymore. The sheer complexity of the tech stack, the cognitive load on reps trying to navigate a dozen different tools, and the data fragmentation were grinding the gears. The human-driven systems, even with their siloed automation, had hit their scaling limit. The very processes that created growth were now strangling it. The turkey was feeling a little sluggish. This is where RevOps came from, to help this poor Turkey get moving.

Then came Thanksgiving.

The SaaS Crash of 2021 was the Black Swan event. The music stopped. The era of cheap money and growth-at-all-costs vanished overnight. Board decks changed from "How fast can we grow?" to "How long is our runway?".

Suddenly, the mandate wasn't just growth; it was Cost Constraints and efficiency.

The GTM machine, once a celebrated asset, was now seen as a bloated liability. "Reduce burn" became the new mantra. The brittleness of the system was laid bare. Companies realized their expensive, disconnected tech stack wasn't a well-oiled machine; it was a junk drawer of subscriptions. The siloed departments, each with their own budgets and fiefdoms, were now a massive operational drag.

Efficiency became the default, not by elegant design, but by brutal necessity. It was a painful, clarifying moment. The turkey had met the farmer's axe. The models were broken. It was time to build something that could survive the unexpected.

Part III: The Barbell Strategy for a New Era (2024)

In investing, Taleb advocates for a "barbell" strategy to deal with uncertainty. You avoid the risky, unpredictable middle and allocate your resources to two extremes: a large portion in extremely safe, robust assets, and a small portion in high-risk, high-reward ventures. You become resilient to negative shocks and open to positive ones.

The post-crash GTM evolution is a perfect embodiment of this. We are now in the AI-Native Era, and the winning strategy is a barbell.

This began with the 2024 "Applications" phase. AI started to assist GTM teams in narrow, practical ways. This is the "safe" end of our barbell. AI began taking over the high-volume, low-complexity tasks that humans are slow, expensive, and inconsistent at.

• AI assistants that listen to sales calls and automatically update the CRM with perfect notes.

• Systems that score and route leads with a speed and accuracy no sales manager could match.

• Platforms that draft hundreds of personalized outreach emails, freeing the SDR to focus on strategy and conversation.

This isn't about replacing humans. It's about making our base-level operations antifragile. We are taking human error, fatigue, and inconsistency out of the most predictable parts of the system. This allows for growth at a much higher velocity by creating "closed loops" where the system learns and refines itself without constant human tinkering.

The other end of the barbell is the high-value, complex, uniquely human work. The strategic account planning, the complex negotiation, the building of deep relationships. With AI handling the robotic work, our best people are freed to do their best work.

This is where my journey came full circle.

The systems I had been building, the proprietary data engineering techniques, the machine learning models trained on GTM data, were no longer theoretical exercises. They were the very tools needed to build this new, resilient engine. The discipline of financial modeling found its purpose in modeling GTM systems. The obsession with finding an edge in data found its home in RevOps. Building this requires skin in the game.

You can't just manage the process; you have to be able to architect the system, wrangle the data, and engineer the AI.

Part IV: The Conductor and the Autonomous Orchestra (2026)

If the last few years were about giving individual musicians better instruments, the next phase is about hiring a world-class conductor and, eventually, teaching the orchestra to play itself.

The 2026 "Orchestrative" phase represents a profound shift. The AI "inflection point" isn't about a better AI application; it's about AI becoming the integrated, neurological system of the entire GTM motion. We move from siloed AI assisting siloed teams to a single, intelligent fabric woven through Marketing, Sales, and Customer Success.

Imagine this:

• AI analyzes marketing engagement and real-time buying signals. Instead of just creating a lead, it orchestrates the next best action. It might trigger a hyper-personalized ad, alert a specific AE with a tailored talk track, and simultaneously arm the CSM with pre-emptive information about the prospect's likely needs—all in a seamless, automated workflow.

The RevOps leader is no longer just a mechanic tuning disparate parts of an engine.

They are the conductor of this orchestra.

They aren't playing every instrument, but they are interpreting the music (the corporate strategy), setting the tempo, and ensuring the violins (Marketing AI), the cellos (Sales AI), and the percussion (CS AI) are all playing in perfect harmony to create a single, beautiful piece: the customer journey.

This naturally leads to the horizon the "Autonomous" GTM.

This is the phase where many get nervous, picturing a dystopian world of robot salespeople selling to other robots. That’s a failure of imagination. Autonomy isn't about replacing strategy; it's about executing it at a speed and scale impossible for humans. It's about building a GTM engine that is antifragile aka it adapts and thrives on volatility.

An autonomous system, operating under the "AI Mandate" won't be a single, all-knowing oracle. It will be a decentralized system of intelligent agents operating within simple, robust rules and frameworks set by human strategists.

• An autonomous pricing agent could adjust discount levels in real-time based on deal velocity, rep performance, and inventory of professional services, all within a floor and ceiling set by finance.

• An autonomous retention agent could detect patterns of declining product usage and automatically trigger a sequence of interventions, from a technical workshop to a personalized offer, without a human ever needing to run a report.

The human role becomes even more critical, but it elevates.

We move from being players on the field to being the architects of the game itself. We design the frameworks, set the objectives, and build the systems that learn, adapt, and execute.

The RevOps Artisan

My journey from the clean, theoretical world of finance to the messy, creative world of tech was a search for real value creation.

I found it in the architecture of growth itself. The evolution of the revenue engine is more than a timeline of technology; it's a story about our relationship with risk, complexity, and uncertainty.

For a decade, we built fragile, process-driven machines that worked beautifully until they were touched by the real world. The shocks of 2019 and 2021 forced an overdue reckoning. We are now in the midst of building something far more robust, intelligent, and resilient.

The future of revenue is an evolution of RevOps into Revenue Command and Control. This world belongs to the builders—the leaders who have skin in the game. The ones who can blend strategy, data science, and engineering. The ones who understand that you don't predict the future; you build a system that is robust enough to deliver it.

The goal is not to build a GTM machine that never fails. That is the old, fragile way of thinking. The goal is to build a revenue engine that learns from failure, that gets stronger from market shocks, and that turns the chaos of the real world into its own competitive advantage.

Friends: in addition to the 21% discount for becoming annual paid members, we are excited to announce an additional 10% discount when paying with Bitcoin. Reach out to me, these discounts stack on top of each other!

👋 Thank you for reading Mastering Revenue Operations.

To help continue our growth, please Like, Comment and Share this post.

I started this in November 2023 because revenue technology and revenue operations methodologies started evolving so rapidly I needed a focal point to coalesce ideas, outline revenue system blueprints, discuss go-to-market strategy amplified by operational alignment and logistical support, and all topics related to revenue operations.

Mastering Revenue Operations is a central hub for the intersection of strategy, technology and revenue operations. Our audience includes Fortune 500 Executives, RevOps Leaders, Venture Capitalists and Entrepreneurs.