236: What AI replaces in data work and when not to reach for it with Julie Beynon

Julie came into data sideways from content marketing and turned that into a 15-year career running lean data teams at some of the coolest martech startups in the landscape. In this episode she breaks down how they cloned their best analyst into an AI agent named JimBot, why she pushes back on AI projects without ever saying no, and how she gets companies to fund the invisible foundation work nobody claps for.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

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