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Notes from the intersection of AI and go-to-market.

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Marketing

AI reads your data before it reads your campaign.

An AI-personalized send congratulates a VP on the job title she left in 2021. The model did exactly what it was told. It read the record and acted on it. The record was the problem.

RevOps

Your pipeline gets a weekly review. Your AI doesn't.

Revenue orgs built a review ritual for every asset they own, then handed AI the workload of a team with the oversight of a vending machine. Here is the meeting that fixes it: who runs it, what's on the dashboard, and what triggers an intervention.

GTM

AI isn't killing IT services. It's killing the billable hour.

The same force squeezing the Big Four is squeezing the local MSP, just from the opposite end. AI is collapsing the billable hour, and the go-to-market motion built on it has to be rebuilt. Here is what replaces it.

Marketing

Your next 1,000 customers will ask an AI first. Does it name you?

Google AI Overviews now appear in 55% of searches. ChatGPT answers 800 million people a week. When a buyer describes their problem to an AI, your product either gets named or it doesn't. There is no page two.

AI

Your product is your GTM. The rest is damage control.

ChatGPT hit 100 million users with a URL and a product worth opening twice. The best go-to-market strategy is a product nobody wants to leave.

Marketing

AI didn't break demand gen. It just moved the job.

73% of B2B websites lost organic traffic last year. Meanwhile, 94% of marketers are using AI to produce more content. The math doesn't work. The job isn't content production anymore. It's demand detection.

RevOps

RevOps already knows how to manage AI. It's called pipeline.

Cold email reply rates dropped from 8.5% to 3.4% in five years. Most teams blame the channel. The real problem: nobody's measuring whether their AI is helping or just producing plausible text at scale.

GTM

AI isn't optimizing the funnel. It's dissolving it.

Gartner says your sales rep gets 5% of the buyer's decision-making time. Most teams are trying to make that 5% more efficient. They're solving the wrong problem.