Stéphane Hamel built the first web analytics QA tool back in 2006, watched an ad blocker quietly borrow his logic, and spent the next 20 years learning that tracking got harder to see every year while the industry got better at documenting it. Now he’s building MANTIS, a privacy observability platform that watches what a website actually does instead of what its policy claims.More
Category Archives: AI
234: How to run a marketing ops audit and turn it into a roadmap, with Kelsie Dube
Sharon walks through why taste is now codifiable, why originality still belongs to humans, and how she pulled a McKinsey-grade deck out of Claude by feeding it her own best work. We get into the lost generation of junior executors and the beekeeper mindset that separates orchestrators from busy bees.More
232: How taste can be codified into systems and is no longer a durable skill, and what’s next with Sharon Gai
Sharon walks through why taste is now codifiable, why originality still belongs to humans, and how she pulled a McKinsey-grade deck out of Claude by feeding it her own best work. We get into the lost generation of junior executors and the beekeeper mindset that separates orchestrators from busy bees.More
228: The Dispatch tower (The Dungeon of martech architecture, part 4)
Every vendor in your stack just turned on an agent. Your ESP has one. Your CDP has one. Your MAP has one. None of them know what the others are doing, none of them were told to check, and nobody volunteered to referee it. Welcome to the final floor.More
227: The Correlation masquerade (The Dungeon of martech architecture, part 3)
Your warehouse is clean, your agents are running, everything looks like it’s working, and that’s the trap. This floor is where AI mistakes correlation for causation and scales the mistake at machine speed, eroding revenue behind a green dashboard. We unpack the fix: holdouts, guardrails, and a causal context graph that proves what actually works.More
226: The Eye of context (The Dungeon of martech architecture, part 2)
Agents operating on data without anything to help them causes “believable nonsense.” Data quality stops agents from misrepresenting what the warehouse contains but you need context engineering to put the right meaning, rules, and situational information in front of the model at the right moment.More
225: The Fall of CRM gravity (The Dungeon of martech architecture, part 1)
At some point in the last decade, the CRM became a shared apartment with 19 roommates, each adding their own version of the source of truth. This episode argues for a cleaner path: raw data into the warehouse, transformation with tools like dbt, then activation through reverse ETL so definitions stay centralized and audiences stay portable. More
224: Keith Jones: How OpenAI’s GTM leader structures teams and spots standout candidates
Keith walks through the full restructuring journey of the GTM org at OpenAI and how GTM Systems ended up under finance. He shares his interview process, the two archtypes that make up his team as well as his filter for separating human candidates from AI-generated applications.More
223: Lindsay Rothlisberger: Inside Zapier’s AI Center of Excellence for GTM and how they manage context and skills
Lindsay walks through the 6-component AI governance model at Zapier: a golden path to Cursor, a structured shared brain in Google Drive, data policies built with the security team, a visibility layer powered by a custom Zapier agent, a context engineering strategy that fights context rot, and a red-yellow-green skills review gate.More
222: Ashley Langford: How senior MOps practitioners are navigating the 2026 job search
Jason breaks down the 5 non-negotiables of minimum viable readiness before you deploy any AI agent, explains why the marketing ops function is becoming more critical as AI takes over execution, and argues that unbounded AI autonomy creates more risk than warehouse data ever will. He also defends GTM engineering as a real discipline rather than a rebrand, and closes with a Dune analogy.More