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
Tag Archives: engineers
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
158: Jeff Lee: How Calm’s Billion customer message machine unites martech and engineering
Jeff built a billion-message marketing machine at Calm with three people. But it was a journey. Push notifications sparked a three-year battle until a new CPO, unburdened by notification trauma, green-lit the project in six weeks. It was a four-year battle for ML recommendations but the data tells an unexpected story. Jeff also shares tactics for winning over the most skeptical product and engineering teams. It starts with operational empathy by taking a stab at a working prototype of your idea but also recognizing that product and martech decisions often stem from personal bias that requires champions who have experienced positive outcomes.More
153: Sundar Swaminathan: How Uber measures the ROI of marketing according to their former Growth Marketing Data Science Lead
After leading Uber’s Marketing Data Science teams, Sundar shares insights that work for both tech giants and startups. Beyond uncovering that Meta ads generated zero incremental value (saving $30 million annually), they mastered measuring brand impact through geo testing and predicting LTV through first-week behaviors. Small companies can adapt these methods through strategic A/B testing and simplified attribution models, even with limited sample sizes. More
143: Danny Lambert: A guide to data transformation and building a warehouse-first martech stack
Marketers often feel like they’re battling a dragon when it comes to integrating data. We’re overwhelmed by technical jargon, stuck with outdated methods, and facing roadblocks from data teams. Danny walks us through his journey of cautiously entering the data world and the role dbt can play for marketing teams. Here’s how to get started with a warehouse-first martech stack.More
140: Jared DeLuca: Appcues’ Director of Ops on integrating demo bookings within your product and using AI to uncover incremental lifts
Jared takes us inside the mad but amazing world of martech at Appcues – the top product adoption SaaS on the planet. We cover his transition from demand gen to ops, how he’s integrated demo bookings within the product using RevenueHero, the difference between ops and revops. More
138: Erin Foxworthy: Snowflake’s Industry Lead on the future of data warehousing, from APIs to data sharing and a unified data layer
In this episode, Erin takes us on a ride through the merging worlds of martech, adtech, AI, and privacy, giving a bold glimpse into what’s next for customer data. We cover how you can use 1st party data for seed predictions, why it’s time you move on from APIs and adopt data sharing and what the unified data layer means for marketers.More
134: Jacqueline Freedman: Former leader at Grammarly and WeWork on how to become a trusted Martech advisor
Jacqueline straps on her jetpack and invites us to soar through the martech skies, teaching us how to navigate the journey of becoming an independent martech advisor. From hands-on execution tasks strategy and advisory projects and assembling a futuristic composable martech stack, we cover a lot of air miles. More
132: Ashleigh Johnson: Tales of a Marketing Technologist from Microsoft
Ashleigh gives us a glimpse into the enterprise world of martech, and it might not be what you’re expecting. We unpack rotational programs, internal personal networks, shadowing colleagues, robust documentation, AI deployment and empowering tool owners to make technology-driven decisions.More
129: Re: Why Martech is Actually for Engineers
Homegrown tools aren’t appealing to marketers, they’re hard to scale, most have a shitty UI and it’s not a recognisable martech tool you can add to your resume. Homegrown martech tools are even less appealing to engineers, they can’t stand the chaos of marketing. We’ll always need for cross-functional translators, disproving the claim that martech is actually only for engineers.More