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
Tag Archives: AI and Automation
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
214: Austin Hay: Claude Code is creating a new class of elite marketers and the mental models that make it click
You’ll be hard pressed to find someone that understands martech and is more advanced in their Claude Code journey than Austin Hay. He maps the 2 chasms separating most marketers from big AI leverage, makes the case for a new class of professional he calls the white collar super saiyan, and walks through the automations he’s actually built.More
212: Tobias Konitzer: The Causal AI revolution and the boomerang effect in marketing decision science
Tobi challenged marketing’s fixation on prediction. He has built highly accurate LTV models, but accuracy alone does not move revenue. Marketing is intervention. Correlation shows patterns; causality tells you what happens when you pull a lever. That shift reshapes experimentation, explains why dynamic allocation can outperform static A B tests, and highlights how self learning systems can backfire or get stuck in local maxima.More
181: Alison Albeck Lindland: Climb the AI literacy pyramid and stand out as a customer‑first marketer
Alison believes marketing careers thrive when you stay close to the people who buy from you, and at Movable Ink she has built that into the culture with a customer strategy team, advisory boards, and events that create real connections customers carry into new roles. More
179: Tiankai Feng: The comeback of data quality and how NLP is changing the data analyst role
Data governance feels like the Jedi Council, steady with its rules, while marketing ops moves like the Rebel Alliance, quick to adapt when perfect data never arrives. Tiankai believes progress comes from blending discipline with curiosity, bringing data in early as a partner, not a critic.More
177: Chris O’Neill: GrowthLoop CEO on how AI agent swarms and reinforcement learning boost velocity
Chris explains how leading marketing teams are deploying swarms of AI agents to automate campaign workflows with speed and precision. By assigning agents to tasks like segmentation, testing, and feedback collection, marketers build fast-moving loops that adapt in real time. More
176: Rajeev Nair: Causal AI and a unified measurement framework
Rajeev believes measurement only works when it’s unified or multi-modal, a stack that blends multi-touch attribution, incrementality, media mix modeling and causal AI, each used for the decision it fits. At Lifesight, that means using causal machine learning to surface hidden experiments in messy historical data and designing geo tests that reveal what actually drives lift. Attribution alone can’t tell you what changed outcomes.More
174: Joshua Kanter: A 4-time CMO on the case against data democratization
Joshua spent the earliest parts of his career buried in SQL, only to watch companies hand out dashboards and call it strategy. Teams skim charts to confirm hunches while ignoring what the data actually says. He believes access means nothing without translation. You need people who can turn vague business prompts into clear, interpretable answers.More