Strategy briefings from the fractional Go-To-Market operators. From the same bench we deploy into companies at the AI growth inflection.
▸ New briefing every Friday. No filler.
Most CEOs use AI to write emails. The real opportunity is a digital Chief of Staff that reads, researches, analyses and challenges your thinking before you decide. A ten-minute course — with copy-paste prompts you can run today.
Ten lessons to turn Claude from a writing assistant into an AI Executive Office — a Chief of Staff that reads, researches and challenges before you decide.
AI has made intelligence abundant; Amdahl's Law says the bottleneck simply moves. Why context — industry, customer, commercial, operational, human and temporal — becomes the most valuable asset, and the durable moat, in the age of AI.
Most AI makes companies faster. Very little AI makes companies grow. The productivity trap, the emerging Revenue Infrastructure layer, and the Data → Distribution → Deployment thesis behind the next decade of AI value.
The world holds roughly $500 trillion of accumulated wealth. AI does not invent a new economy — it rewires the existing one through a new stack. Where the next trillion dollars of value will actually be created, and who will capture it.
Every generation believes its technological revolution is unprecedented. Five centuries of evidence say otherwise. Eleven revolutions since 1450, each running the same five-stage cycle of discovery, speculation, overinvestment, correction, and infrastructure. AI is not breaking the pattern — it is following it.
Google's Q1 2026 earnings prove the seven-layer AI industrial stack — and reveal where it breaks. The hyperscalers built the engine; they have not built the cars, the dealerships, or the roads for the industries that will consume the intelligence. The largest unowned category in the AI economy.
Polsia. Medvi. Base44. A new class of companies designed around the idea that AI agents can run large parts of a business autonomously. Lessons from the autonomous enterprise movement that boards and Fortune 500 operators should be acting on now — what to import, what to ignore, and the limits the early evidence is exposing.
Why the next trillion-dollar companies won't be software firms — and what SpaceX's $28.5–29T total addressable market reveals about where economic value is actually migrating. The infrastructure underneath the intelligence economy is being built in plain sight.
Jensen Huang gave us a five-layer cake. Two layers later, the stack is seven. From raw electrons at the bottom to AI-native industries at the top — a single industrial map of where AI value originates, where it moves, and where it ultimately accrues. The Industry Go-To-Market layer is the substrate of how the economy decides what to buy, build, and back.
Seven layers, one direction of flow. Compute → Tokens → Intelligence → Digital Workers → Industry GTM → Industry Transformation → GDP. The canonical seven-layer framework for the AI industrial stack, and the companies disrupting each layer in mid-2026.
Cursor reached a $50B valuation faster than any product-led company in B2B history. The growth loop they built — and the precise mechanics of how usage, distribution, and pricing reinforce each other — is the most important PLG case study of the decade.
How OpenAI and Anthropic built radically different revenue engines — product-led growth vs enterprise-first sales — and what every B2B operator can learn from both. Combined annualised revenue: $55B+ from less than $8B fifteen months earlier.
The linear funnel was built for a world of human-run campaigns and batch outreach. That world is gone. What replaces it is signal-driven, AI-orchestrated, and continuous. A working model for the post-funnel revenue engine.
The revenue org you inherited was built for a world of human-run campaigns. A complete map of the modern GTM org — every role, every stage, and the decision logic for when fractional beats full-time and when it doesn't.
CRM, forecasting, and attribution were built for a human-speed funnel. What happens to the GTM stack when half your pipeline is touched by agents? A working architecture for the RevOps function that survives the transition.
Every serious publication has an Issue 001 that says what it is. Our editorial mission, the seven-category taxonomy, the cadence, the audience, and what makes this different from every other AI newsletter in your inbox.
How should I design my motion?
→ GTM StrategyHow is AI reshaping my GTM stack?
→ AI & the GTM StackHow do I lead a sales org?
→ Sales LeadershipHow do I run my RevOps function?
→ Revenue OperationsHow do I run demand and marketing?
→ Demand & MarketingWhat's happening in my industry?
→ Sector BriefingsEvery briefing in GTM Bench Review comes from the same bench of fractional operators we place into companies at the AI growth inflection. The analysis you read is a signal of what they're actually doing inside client engagements right now.
Strategy briefings on AI and Go-To-Market, from the fractional operators on the GTM Bench. New briefing every Friday.