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
Tag Archives: AI agents
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
221: Jason Dobbs: You need Minimum Viable Readiness for AI because perfect data doesn’t exist
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
220: Alex Halliday: How to build content engineering systems that get cited and scale without slop
Alex breaks down what content engineering actually means: building the systems infrastructure to maintain quality, freshness, and brand accuracy across everything a company has ever put online. He makes the counterintuitive case that great content engineering puts more humans into the content process.More
219: Elizabeth Dobbs: Inside Databricks’ stack with 3 AI agents, 1 lakehouse, and 6 years of data work
Liz spent 6 years at Databricks building the data infrastructure before deploying any AI on top of it. She’s shipped 3 production agents (Marge, Tagatha, and Atlas) and she’ll tell you exactly what broke first and why the team kept going anyway. You’ll hear how a marketing lakehouse becomes the foundation that makes every agent actually work, why the agent label debate is a distraction.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
203: Jordan Resnick: How to distinguish fake traffic from real machine customers
Distinguishing fake traffic from real machine customers requires reading behavior. Jordan shows how AI-driven bots now scroll, click, and submit forms while inflating dashboards with activity that never converts. The signal lives in speed, sequencing, and follow-through. Teams that act protect the conversion point, block synthetic demand early, and report only after traffic earns trust.More
191: Aboli Gangreddiwar: Self healing data agents, hivemind memory curators and living documentation
Aboli and Phil explore AI agent use cases like self-healing data quality agents, AI hivemind memory curator, documentation agents and AI browsers and a bunch more!More
189: Aditi Uppal: How to capture, activate and measure voice of customer across go to market efforts
Aditi shows how five honest conversations can reshape how you read data, because customer language carries context that numbers miss. She points to overlooked signals like product usage trails, community chatter, sales recordings, and event conversations, then explains how to turn them into action through a simple pipeline of capture, tag, route, track, and activate. More